diff --git a/vaderSentiment/emoji_utf8_lexicon.txt b/vaderSentiment/emoji_utf8_lexicon.txt
index 5e1a91b..4ee676c 100644
--- a/vaderSentiment/emoji_utf8_lexicon.txt
+++ b/vaderSentiment/emoji_utf8_lexicon.txt
@@ -1,3570 +1,3570 @@
-😀	grinning face
-😁	beaming face with smiling eyes
-😂	face with tears of joy
-🤣	rolling on the floor laughing
-😃	grinning face with big eyes
-😄	grinning face with smiling eyes
-😅	grinning face with sweat
-😆	grinning squinting face
-😉	winking face
-😊	smiling face with smiling eyes
-😋	face savoring food
-😎	smiling face with sunglasses
-😍	smiling face with heart-eyes
-😘	face blowing a kiss
-🥰	smiling face with 3 hearts
-😗	kissing face
-😙	kissing face with smiling eyes
-😚	kissing face with closed eyes
-☺️	smiling face
-☺	smiling face
-🙂	slightly smiling face
-🤗	hugging face
-🤩	star-struck
-🤔	thinking face
-🤨	face with raised eyebrow
-😐	neutral face
-😑	expressionless face
-😶	face without mouth
-🙄	face with rolling eyes
-😏	smirking face
-😣	persevering face
-😥	sad but relieved face
-😮	face with open mouth
-🤐	zipper-mouth face
-😯	hushed face
-😪	sleepy face
-😫	tired face
-😴	sleeping face
-😌	relieved face
-😛	face with tongue
-😜	winking face with tongue
-😝	squinting face with tongue
-🤤	drooling face
-😒	unamused face
-😓	downcast face with sweat
-😔	pensive face
-😕	confused face
-🙃	upside-down face
-🤑	money-mouth face
-😲	astonished face
-☹️	frowning face
-☹	frowning face
-🙁	slightly frowning face
-😖	confounded face
-😞	disappointed face
-😟	worried face
-😤	face with steam from nose
-😢	crying face
-😭	loudly crying face
-😦	frowning face with open mouth
-😧	anguished face
-😨	fearful face
-😩	weary face
-🤯	exploding head
-😬	grimacing face
-😰	anxious face with sweat
-😱	face screaming in fear
-🥵	hot face
-🥶	cold face
-😳	flushed face
-🤪	zany face
-😵	dizzy face
-😡	pouting face
-😠	angry face
-🤬	face with symbols on mouth
-😷	face with medical mask
-🤒	face with thermometer
-🤕	face with head-bandage
-🤢	nauseated face
-🤮	face vomiting
-🤧	sneezing face
-😇	smiling face with halo
-🤠	cowboy hat face
-🥳	partying face
-🥴	woozy face
-🥺	pleading face
-🤥	lying face
-🤫	shushing face
-🤭	face with hand over mouth
-🧐	face with monocle
-🤓	nerd face
-😈	smiling face with horns
-👿	angry face with horns
-🤡	clown face
-👹	ogre
-👺	goblin
-💀	skull
-☠️	skull and crossbones
-☠	skull and crossbones
-👻	ghost
-👽	alien
-👾	alien monster
-🤖	robot face
-💩	pile of poo
-😺	grinning cat face
-😸	grinning cat face with smiling eyes
-😹	cat face with tears of joy
-😻	smiling cat face with heart-eyes
-😼	cat face with wry smile
-😽	kissing cat face
-🙀	weary cat face
-😿	crying cat face
-😾	pouting cat face
-🙈	see-no-evil monkey
-🙉	hear-no-evil monkey
-🙊	speak-no-evil monkey
-🏻	light skin tone
-🏼	medium-light skin tone
-🏽	medium skin tone
-🏾	medium-dark skin tone
-🏿	dark skin tone
-👶	baby
-👶🏻	baby: light skin tone
-👶🏼	baby: medium-light skin tone
-👶🏽	baby: medium skin tone
-👶🏾	baby: medium-dark skin tone
-👶🏿	baby: dark skin tone
-🧒	child
-🧒🏻	child: light skin tone
-🧒🏼	child: medium-light skin tone
-🧒🏽	child: medium skin tone
-🧒🏾	child: medium-dark skin tone
-🧒🏿	child: dark skin tone
-👦	boy
-👦🏻	boy: light skin tone
-👦🏼	boy: medium-light skin tone
-👦🏽	boy: medium skin tone
-👦🏾	boy: medium-dark skin tone
-👦🏿	boy: dark skin tone
-👧	girl
-👧🏻	girl: light skin tone
-👧🏼	girl: medium-light skin tone
-👧🏽	girl: medium skin tone
-👧🏾	girl: medium-dark skin tone
-👧🏿	girl: dark skin tone
-🧑	adult
-🧑🏻	adult: light skin tone
-🧑🏼	adult: medium-light skin tone
-🧑🏽	adult: medium skin tone
-🧑🏾	adult: medium-dark skin tone
-🧑🏿	adult: dark skin tone
-👨	man
-👨🏻	man: light skin tone
-👨🏼	man: medium-light skin tone
-👨🏽	man: medium skin tone
-👨🏾	man: medium-dark skin tone
-👨🏿	man: dark skin tone
-👩	woman
-👩🏻	woman: light skin tone
-👩🏼	woman: medium-light skin tone
-👩🏽	woman: medium skin tone
-👩🏾	woman: medium-dark skin tone
-👩🏿	woman: dark skin tone
-🧓	older adult
-🧓🏻	older adult: light skin tone
-🧓🏼	older adult: medium-light skin tone
-🧓🏽	older adult: medium skin tone
-🧓🏾	older adult: medium-dark skin tone
-🧓🏿	older adult: dark skin tone
-👴	old man
-👴🏻	old man: light skin tone
-👴🏼	old man: medium-light skin tone
-👴🏽	old man: medium skin tone
-👴🏾	old man: medium-dark skin tone
-👴🏿	old man: dark skin tone
-👵	old woman
-👵🏻	old woman: light skin tone
-👵🏼	old woman: medium-light skin tone
-👵🏽	old woman: medium skin tone
-👵🏾	old woman: medium-dark skin tone
-👵🏿	old woman: dark skin tone
-👨‍⚕️	man health worker
-👨‍⚕	man health worker
-👨🏻‍⚕️	man health worker: light skin tone
-👨🏻‍⚕	man health worker: light skin tone
-👨🏼‍⚕️	man health worker: medium-light skin tone
-👨🏼‍⚕	man health worker: medium-light skin tone
-👨🏽‍⚕️	man health worker: medium skin tone
-👨🏽‍⚕	man health worker: medium skin tone
-👨🏾‍⚕️	man health worker: medium-dark skin tone
-👨🏾‍⚕	man health worker: medium-dark skin tone
-👨🏿‍⚕️	man health worker: dark skin tone
-👨🏿‍⚕	man health worker: dark skin tone
-👩‍⚕️	woman health worker
-👩‍⚕	woman health worker
-👩🏻‍⚕️	woman health worker: light skin tone
-👩🏻‍⚕	woman health worker: light skin tone
-👩🏼‍⚕️	woman health worker: medium-light skin tone
-👩🏼‍⚕	woman health worker: medium-light skin tone
-👩🏽‍⚕️	woman health worker: medium skin tone
-👩🏽‍⚕	woman health worker: medium skin tone
-👩🏾‍⚕️	woman health worker: medium-dark skin tone
-👩🏾‍⚕	woman health worker: medium-dark skin tone
-👩🏿‍⚕️	woman health worker: dark skin tone
-👩🏿‍⚕	woman health worker: dark skin tone
-👨‍🎓	man student
-👨🏻‍🎓	man student: light skin tone
-👨🏼‍🎓	man student: medium-light skin tone
-👨🏽‍🎓	man student: medium skin tone
-👨🏾‍🎓	man student: medium-dark skin tone
-👨🏿‍🎓	man student: dark skin tone
-👩‍🎓	woman student
-👩🏻‍🎓	woman student: light skin tone
-👩🏼‍🎓	woman student: medium-light skin tone
-👩🏽‍🎓	woman student: medium skin tone
-👩🏾‍🎓	woman student: medium-dark skin tone
-👩🏿‍🎓	woman student: dark skin tone
-👨‍🏫	man teacher
-👨🏻‍🏫	man teacher: light skin tone
-👨🏼‍🏫	man teacher: medium-light skin tone
-👨🏽‍🏫	man teacher: medium skin tone
-👨🏾‍🏫	man teacher: medium-dark skin tone
-👨🏿‍🏫	man teacher: dark skin tone
-👩‍🏫	woman teacher
-👩🏻‍🏫	woman teacher: light skin tone
-👩🏼‍🏫	woman teacher: medium-light skin tone
-👩🏽‍🏫	woman teacher: medium skin tone
-👩🏾‍🏫	woman teacher: medium-dark skin tone
-👩🏿‍🏫	woman teacher: dark skin tone
-👨‍⚖️	man judge
-👨‍⚖	man judge
-👨🏻‍⚖️	man judge: light skin tone
-👨🏻‍⚖	man judge: light skin tone
-👨🏼‍⚖️	man judge: medium-light skin tone
-👨🏼‍⚖	man judge: medium-light skin tone
-👨🏽‍⚖️	man judge: medium skin tone
-👨🏽‍⚖	man judge: medium skin tone
-👨🏾‍⚖️	man judge: medium-dark skin tone
-👨🏾‍⚖	man judge: medium-dark skin tone
-👨🏿‍⚖️	man judge: dark skin tone
-👨🏿‍⚖	man judge: dark skin tone
-👩‍⚖️	woman judge
-👩‍⚖	woman judge
-👩🏻‍⚖️	woman judge: light skin tone
-👩🏻‍⚖	woman judge: light skin tone
-👩🏼‍⚖️	woman judge: medium-light skin tone
-👩🏼‍⚖	woman judge: medium-light skin tone
-👩🏽‍⚖️	woman judge: medium skin tone
-👩🏽‍⚖	woman judge: medium skin tone
-👩🏾‍⚖️	woman judge: medium-dark skin tone
-👩🏾‍⚖	woman judge: medium-dark skin tone
-👩🏿‍⚖️	woman judge: dark skin tone
-👩🏿‍⚖	woman judge: dark skin tone
-👨‍🌾	man farmer
-👨🏻‍🌾	man farmer: light skin tone
-👨🏼‍🌾	man farmer: medium-light skin tone
-👨🏽‍🌾	man farmer: medium skin tone
-👨🏾‍🌾	man farmer: medium-dark skin tone
-👨🏿‍🌾	man farmer: dark skin tone
-👩‍🌾	woman farmer
-👩🏻‍🌾	woman farmer: light skin tone
-👩🏼‍🌾	woman farmer: medium-light skin tone
-👩🏽‍🌾	woman farmer: medium skin tone
-👩🏾‍🌾	woman farmer: medium-dark skin tone
-👩🏿‍🌾	woman farmer: dark skin tone
-👨‍🍳	man cook
-👨🏻‍🍳	man cook: light skin tone
-👨🏼‍🍳	man cook: medium-light skin tone
-👨🏽‍🍳	man cook: medium skin tone
-👨🏾‍🍳	man cook: medium-dark skin tone
-👨🏿‍🍳	man cook: dark skin tone
-👩‍🍳	woman cook
-👩🏻‍🍳	woman cook: light skin tone
-👩🏼‍🍳	woman cook: medium-light skin tone
-👩🏽‍🍳	woman cook: medium skin tone
-👩🏾‍🍳	woman cook: medium-dark skin tone
-👩🏿‍🍳	woman cook: dark skin tone
-👨‍🔧	man mechanic
-👨🏻‍🔧	man mechanic: light skin tone
-👨🏼‍🔧	man mechanic: medium-light skin tone
-👨🏽‍🔧	man mechanic: medium skin tone
-👨🏾‍🔧	man mechanic: medium-dark skin tone
-👨🏿‍🔧	man mechanic: dark skin tone
-👩‍🔧	woman mechanic
-👩🏻‍🔧	woman mechanic: light skin tone
-👩🏼‍🔧	woman mechanic: medium-light skin tone
-👩🏽‍🔧	woman mechanic: medium skin tone
-👩🏾‍🔧	woman mechanic: medium-dark skin tone
-👩🏿‍🔧	woman mechanic: dark skin tone
-👨‍🏭	man factory worker
-👨🏻‍🏭	man factory worker: light skin tone
-👨🏼‍🏭	man factory worker: medium-light skin tone
-👨🏽‍🏭	man factory worker: medium skin tone
-👨🏾‍🏭	man factory worker: medium-dark skin tone
-👨🏿‍🏭	man factory worker: dark skin tone
-👩‍🏭	woman factory worker
-👩🏻‍🏭	woman factory worker: light skin tone
-👩🏼‍🏭	woman factory worker: medium-light skin tone
-👩🏽‍🏭	woman factory worker: medium skin tone
-👩🏾‍🏭	woman factory worker: medium-dark skin tone
-👩🏿‍🏭	woman factory worker: dark skin tone
-👨‍💼	man office worker
-👨🏻‍💼	man office worker: light skin tone
-👨🏼‍💼	man office worker: medium-light skin tone
-👨🏽‍💼	man office worker: medium skin tone
-👨🏾‍💼	man office worker: medium-dark skin tone
-👨🏿‍💼	man office worker: dark skin tone
-👩‍💼	woman office worker
-👩🏻‍💼	woman office worker: light skin tone
-👩🏼‍💼	woman office worker: medium-light skin tone
-👩🏽‍💼	woman office worker: medium skin tone
-👩🏾‍💼	woman office worker: medium-dark skin tone
-👩🏿‍💼	woman office worker: dark skin tone
-👨‍🔬	man scientist
-👨🏻‍🔬	man scientist: light skin tone
-👨🏼‍🔬	man scientist: medium-light skin tone
-👨🏽‍🔬	man scientist: medium skin tone
-👨🏾‍🔬	man scientist: medium-dark skin tone
-👨🏿‍🔬	man scientist: dark skin tone
-👩‍🔬	woman scientist
-👩🏻‍🔬	woman scientist: light skin tone
-👩🏼‍🔬	woman scientist: medium-light skin tone
-👩🏽‍🔬	woman scientist: medium skin tone
-👩🏾‍🔬	woman scientist: medium-dark skin tone
-👩🏿‍🔬	woman scientist: dark skin tone
-👨‍💻	man technologist
-👨🏻‍💻	man technologist: light skin tone
-👨🏼‍💻	man technologist: medium-light skin tone
-👨🏽‍💻	man technologist: medium skin tone
-👨🏾‍💻	man technologist: medium-dark skin tone
-👨🏿‍💻	man technologist: dark skin tone
-👩‍💻	woman technologist
-👩🏻‍💻	woman technologist: light skin tone
-👩🏼‍💻	woman technologist: medium-light skin tone
-👩🏽‍💻	woman technologist: medium skin tone
-👩🏾‍💻	woman technologist: medium-dark skin tone
-👩🏿‍💻	woman technologist: dark skin tone
-👨‍🎤	man singer
-👨🏻‍🎤	man singer: light skin tone
-👨🏼‍🎤	man singer: medium-light skin tone
-👨🏽‍🎤	man singer: medium skin tone
-👨🏾‍🎤	man singer: medium-dark skin tone
-👨🏿‍🎤	man singer: dark skin tone
-👩‍🎤	woman singer
-👩🏻‍🎤	woman singer: light skin tone
-👩🏼‍🎤	woman singer: medium-light skin tone
-👩🏽‍🎤	woman singer: medium skin tone
-👩🏾‍🎤	woman singer: medium-dark skin tone
-👩🏿‍🎤	woman singer: dark skin tone
-👨‍🎨	man artist
-👨🏻‍🎨	man artist: light skin tone
-👨🏼‍🎨	man artist: medium-light skin tone
-👨🏽‍🎨	man artist: medium skin tone
-👨🏾‍🎨	man artist: medium-dark skin tone
-👨🏿‍🎨	man artist: dark skin tone
-👩‍🎨	woman artist
-👩🏻‍🎨	woman artist: light skin tone
-👩🏼‍🎨	woman artist: medium-light skin tone
-👩🏽‍🎨	woman artist: medium skin tone
-👩🏾‍🎨	woman artist: medium-dark skin tone
-👩🏿‍🎨	woman artist: dark skin tone
-👨‍✈️	man pilot
-👨‍✈	man pilot
-👨🏻‍✈️	man pilot: light skin tone
-👨🏻‍✈	man pilot: light skin tone
-👨🏼‍✈️	man pilot: medium-light skin tone
-👨🏼‍✈	man pilot: medium-light skin tone
-👨🏽‍✈️	man pilot: medium skin tone
-👨🏽‍✈	man pilot: medium skin tone
-👨🏾‍✈️	man pilot: medium-dark skin tone
-👨🏾‍✈	man pilot: medium-dark skin tone
-👨🏿‍✈️	man pilot: dark skin tone
-👨🏿‍✈	man pilot: dark skin tone
-👩‍✈️	woman pilot
-👩‍✈	woman pilot
-👩🏻‍✈️	woman pilot: light skin tone
-👩🏻‍✈	woman pilot: light skin tone
-👩🏼‍✈️	woman pilot: medium-light skin tone
-👩🏼‍✈	woman pilot: medium-light skin tone
-👩🏽‍✈️	woman pilot: medium skin tone
-👩🏽‍✈	woman pilot: medium skin tone
-👩🏾‍✈️	woman pilot: medium-dark skin tone
-👩🏾‍✈	woman pilot: medium-dark skin tone
-👩🏿‍✈️	woman pilot: dark skin tone
-👩🏿‍✈	woman pilot: dark skin tone
-👨‍🚀	man astronaut
-👨🏻‍🚀	man astronaut: light skin tone
-👨🏼‍🚀	man astronaut: medium-light skin tone
-👨🏽‍🚀	man astronaut: medium skin tone
-👨🏾‍🚀	man astronaut: medium-dark skin tone
-👨🏿‍🚀	man astronaut: dark skin tone
-👩‍🚀	woman astronaut
-👩🏻‍🚀	woman astronaut: light skin tone
-👩🏼‍🚀	woman astronaut: medium-light skin tone
-👩🏽‍🚀	woman astronaut: medium skin tone
-👩🏾‍🚀	woman astronaut: medium-dark skin tone
-👩🏿‍🚀	woman astronaut: dark skin tone
-👨‍🚒	man firefighter
-👨🏻‍🚒	man firefighter: light skin tone
-👨🏼‍🚒	man firefighter: medium-light skin tone
-👨🏽‍🚒	man firefighter: medium skin tone
-👨🏾‍🚒	man firefighter: medium-dark skin tone
-👨🏿‍🚒	man firefighter: dark skin tone
-👩‍🚒	woman firefighter
-👩🏻‍🚒	woman firefighter: light skin tone
-👩🏼‍🚒	woman firefighter: medium-light skin tone
-👩🏽‍🚒	woman firefighter: medium skin tone
-👩🏾‍🚒	woman firefighter: medium-dark skin tone
-👩🏿‍🚒	woman firefighter: dark skin tone
-👮	police officer
-👮🏻	police officer: light skin tone
-👮🏼	police officer: medium-light skin tone
-👮🏽	police officer: medium skin tone
-👮🏾	police officer: medium-dark skin tone
-👮🏿	police officer: dark skin tone
-👮‍♂️	man police officer
-👮‍♂	man police officer
-👮🏻‍♂️	man police officer: light skin tone
-👮🏻‍♂	man police officer: light skin tone
-👮🏼‍♂️	man police officer: medium-light skin tone
-👮🏼‍♂	man police officer: medium-light skin tone
-👮🏽‍♂️	man police officer: medium skin tone
-👮🏽‍♂	man police officer: medium skin tone
-👮🏾‍♂️	man police officer: medium-dark skin tone
-👮🏾‍♂	man police officer: medium-dark skin tone
-👮🏿‍♂️	man police officer: dark skin tone
-👮🏿‍♂	man police officer: dark skin tone
-👮‍♀️	woman police officer
-👮‍♀	woman police officer
-👮🏻‍♀️	woman police officer: light skin tone
-👮🏻‍♀	woman police officer: light skin tone
-👮🏼‍♀️	woman police officer: medium-light skin tone
-👮🏼‍♀	woman police officer: medium-light skin tone
-👮🏽‍♀️	woman police officer: medium skin tone
-👮🏽‍♀	woman police officer: medium skin tone
-👮🏾‍♀️	woman police officer: medium-dark skin tone
-👮🏾‍♀	woman police officer: medium-dark skin tone
-👮🏿‍♀️	woman police officer: dark skin tone
-👮🏿‍♀	woman police officer: dark skin tone
-🕵️	detective
-🕵	detective
-🕵🏻	detective: light skin tone
-🕵🏼	detective: medium-light skin tone
-🕵🏽	detective: medium skin tone
-🕵🏾	detective: medium-dark skin tone
-🕵🏿	detective: dark skin tone
-🕵️‍♂️	man detective
-🕵‍♂️	man detective
-🕵️‍♂	man detective
-🕵‍♂	man detective
-🕵🏻‍♂️	man detective: light skin tone
-🕵🏻‍♂	man detective: light skin tone
-🕵🏼‍♂️	man detective: medium-light skin tone
-🕵🏼‍♂	man detective: medium-light skin tone
-🕵🏽‍♂️	man detective: medium skin tone
-🕵🏽‍♂	man detective: medium skin tone
-🕵🏾‍♂️	man detective: medium-dark skin tone
-🕵🏾‍♂	man detective: medium-dark skin tone
-🕵🏿‍♂️	man detective: dark skin tone
-🕵🏿‍♂	man detective: dark skin tone
-🕵️‍♀️	woman detective
-🕵‍♀️	woman detective
-🕵️‍♀	woman detective
-🕵‍♀	woman detective
-🕵🏻‍♀️	woman detective: light skin tone
-🕵🏻‍♀	woman detective: light skin tone
-🕵🏼‍♀️	woman detective: medium-light skin tone
-🕵🏼‍♀	woman detective: medium-light skin tone
-🕵🏽‍♀️	woman detective: medium skin tone
-🕵🏽‍♀	woman detective: medium skin tone
-🕵🏾‍♀️	woman detective: medium-dark skin tone
-🕵🏾‍♀	woman detective: medium-dark skin tone
-🕵🏿‍♀️	woman detective: dark skin tone
-🕵🏿‍♀	woman detective: dark skin tone
-💂	guard
-💂🏻	guard: light skin tone
-💂🏼	guard: medium-light skin tone
-💂🏽	guard: medium skin tone
-💂🏾	guard: medium-dark skin tone
-💂🏿	guard: dark skin tone
-💂‍♂️	man guard
-💂‍♂	man guard
-💂🏻‍♂️	man guard: light skin tone
-💂🏻‍♂	man guard: light skin tone
-💂🏼‍♂️	man guard: medium-light skin tone
-💂🏼‍♂	man guard: medium-light skin tone
-💂🏽‍♂️	man guard: medium skin tone
-💂🏽‍♂	man guard: medium skin tone
-💂🏾‍♂️	man guard: medium-dark skin tone
-💂🏾‍♂	man guard: medium-dark skin tone
-💂🏿‍♂️	man guard: dark skin tone
-💂🏿‍♂	man guard: dark skin tone
-💂‍♀️	woman guard
-💂‍♀	woman guard
-💂🏻‍♀️	woman guard: light skin tone
-💂🏻‍♀	woman guard: light skin tone
-💂🏼‍♀️	woman guard: medium-light skin tone
-💂🏼‍♀	woman guard: medium-light skin tone
-💂🏽‍♀️	woman guard: medium skin tone
-💂🏽‍♀	woman guard: medium skin tone
-💂🏾‍♀️	woman guard: medium-dark skin tone
-💂🏾‍♀	woman guard: medium-dark skin tone
-💂🏿‍♀️	woman guard: dark skin tone
-💂🏿‍♀	woman guard: dark skin tone
-👷	construction worker
-👷🏻	construction worker: light skin tone
-👷🏼	construction worker: medium-light skin tone
-👷🏽	construction worker: medium skin tone
-👷🏾	construction worker: medium-dark skin tone
-👷🏿	construction worker: dark skin tone
-👷‍♂️	man construction worker
-👷‍♂	man construction worker
-👷🏻‍♂️	man construction worker: light skin tone
-👷🏻‍♂	man construction worker: light skin tone
-👷🏼‍♂️	man construction worker: medium-light skin tone
-👷🏼‍♂	man construction worker: medium-light skin tone
-👷🏽‍♂️	man construction worker: medium skin tone
-👷🏽‍♂	man construction worker: medium skin tone
-👷🏾‍♂️	man construction worker: medium-dark skin tone
-👷🏾‍♂	man construction worker: medium-dark skin tone
-👷🏿‍♂️	man construction worker: dark skin tone
-👷🏿‍♂	man construction worker: dark skin tone
-👷‍♀️	woman construction worker
-👷‍♀	woman construction worker
-👷🏻‍♀️	woman construction worker: light skin tone
-👷🏻‍♀	woman construction worker: light skin tone
-👷🏼‍♀️	woman construction worker: medium-light skin tone
-👷🏼‍♀	woman construction worker: medium-light skin tone
-👷🏽‍♀️	woman construction worker: medium skin tone
-👷🏽‍♀	woman construction worker: medium skin tone
-👷🏾‍♀️	woman construction worker: medium-dark skin tone
-👷🏾‍♀	woman construction worker: medium-dark skin tone
-👷🏿‍♀️	woman construction worker: dark skin tone
-👷🏿‍♀	woman construction worker: dark skin tone
-🤴	prince
-🤴🏻	prince: light skin tone
-🤴🏼	prince: medium-light skin tone
-🤴🏽	prince: medium skin tone
-🤴🏾	prince: medium-dark skin tone
-🤴🏿	prince: dark skin tone
-👸	princess
-👸🏻	princess: light skin tone
-👸🏼	princess: medium-light skin tone
-👸🏽	princess: medium skin tone
-👸🏾	princess: medium-dark skin tone
-👸🏿	princess: dark skin tone
-👳	person wearing turban
-👳🏻	person wearing turban: light skin tone
-👳🏼	person wearing turban: medium-light skin tone
-👳🏽	person wearing turban: medium skin tone
-👳🏾	person wearing turban: medium-dark skin tone
-👳🏿	person wearing turban: dark skin tone
-👳‍♂️	man wearing turban
-👳‍♂	man wearing turban
-👳🏻‍♂️	man wearing turban: light skin tone
-👳🏻‍♂	man wearing turban: light skin tone
-👳🏼‍♂️	man wearing turban: medium-light skin tone
-👳🏼‍♂	man wearing turban: medium-light skin tone
-👳🏽‍♂️	man wearing turban: medium skin tone
-👳🏽‍♂	man wearing turban: medium skin tone
-👳🏾‍♂️	man wearing turban: medium-dark skin tone
-👳🏾‍♂	man wearing turban: medium-dark skin tone
-👳🏿‍♂️	man wearing turban: dark skin tone
-👳🏿‍♂	man wearing turban: dark skin tone
-👳‍♀️	woman wearing turban
-👳‍♀	woman wearing turban
-👳🏻‍♀️	woman wearing turban: light skin tone
-👳🏻‍♀	woman wearing turban: light skin tone
-👳🏼‍♀️	woman wearing turban: medium-light skin tone
-👳🏼‍♀	woman wearing turban: medium-light skin tone
-👳🏽‍♀️	woman wearing turban: medium skin tone
-👳🏽‍♀	woman wearing turban: medium skin tone
-👳🏾‍♀️	woman wearing turban: medium-dark skin tone
-👳🏾‍♀	woman wearing turban: medium-dark skin tone
-👳🏿‍♀️	woman wearing turban: dark skin tone
-👳🏿‍♀	woman wearing turban: dark skin tone
-👲	man with Chinese cap
-👲🏻	man with Chinese cap: light skin tone
-👲🏼	man with Chinese cap: medium-light skin tone
-👲🏽	man with Chinese cap: medium skin tone
-👲🏾	man with Chinese cap: medium-dark skin tone
-👲🏿	man with Chinese cap: dark skin tone
-🧕	woman with headscarf
-🧕🏻	woman with headscarf: light skin tone
-🧕🏼	woman with headscarf: medium-light skin tone
-🧕🏽	woman with headscarf: medium skin tone
-🧕🏾	woman with headscarf: medium-dark skin tone
-🧕🏿	woman with headscarf: dark skin tone
-🧔	bearded person
-🧔🏻	bearded person: light skin tone
-🧔🏼	bearded person: medium-light skin tone
-🧔🏽	bearded person: medium skin tone
-🧔🏾	bearded person: medium-dark skin tone
-🧔🏿	bearded person: dark skin tone
-👱	blond-haired person
-👱🏻	blond-haired person: light skin tone
-👱🏼	blond-haired person: medium-light skin tone
-👱🏽	blond-haired person: medium skin tone
-👱🏾	blond-haired person: medium-dark skin tone
-👱🏿	blond-haired person: dark skin tone
-👱‍♂️	blond-haired man
-👱‍♂	blond-haired man
-👱🏻‍♂️	blond-haired man: light skin tone
-👱🏻‍♂	blond-haired man: light skin tone
-👱🏼‍♂️	blond-haired man: medium-light skin tone
-👱🏼‍♂	blond-haired man: medium-light skin tone
-👱🏽‍♂️	blond-haired man: medium skin tone
-👱🏽‍♂	blond-haired man: medium skin tone
-👱🏾‍♂️	blond-haired man: medium-dark skin tone
-👱🏾‍♂	blond-haired man: medium-dark skin tone
-👱🏿‍♂️	blond-haired man: dark skin tone
-👱🏿‍♂	blond-haired man: dark skin tone
-👱‍♀️	blond-haired woman
-👱‍♀	blond-haired woman
-👱🏻‍♀️	blond-haired woman: light skin tone
-👱🏻‍♀	blond-haired woman: light skin tone
-👱🏼‍♀️	blond-haired woman: medium-light skin tone
-👱🏼‍♀	blond-haired woman: medium-light skin tone
-👱🏽‍♀️	blond-haired woman: medium skin tone
-👱🏽‍♀	blond-haired woman: medium skin tone
-👱🏾‍♀️	blond-haired woman: medium-dark skin tone
-👱🏾‍♀	blond-haired woman: medium-dark skin tone
-👱🏿‍♀️	blond-haired woman: dark skin tone
-👱🏿‍♀	blond-haired woman: dark skin tone
-👨‍🦰	man, red haired
-👨🏻‍🦰	man, red haired: light skin tone
-👨🏼‍🦰	man, red haired: medium-light skin tone
-👨🏽‍🦰	man, red haired: medium skin tone
-👨🏾‍🦰	man, red haired: medium-dark skin tone
-👨🏿‍🦰	man, red haired: dark skin tone
-👩‍🦰	woman, red haired
-👩🏻‍🦰	woman, red haired: light skin tone
-👩🏼‍🦰	woman, red haired: medium-light skin tone
-👩🏽‍🦰	woman, red haired: medium skin tone
-👩🏾‍🦰	woman, red haired: medium-dark skin tone
-👩🏿‍🦰	woman, red haired: dark skin tone
-👨‍🦱	man, curly haired
-👨🏻‍🦱	man, curly haired: light skin tone
-👨🏼‍🦱	man, curly haired: medium-light skin tone
-👨🏽‍🦱	man, curly haired: medium skin tone
-👨🏾‍🦱	man, curly haired: medium-dark skin tone
-👨🏿‍🦱	man, curly haired: dark skin tone
-👩‍🦱	woman, curly haired
-👩🏻‍🦱	woman, curly haired: light skin tone
-👩🏼‍🦱	woman, curly haired: medium-light skin tone
-👩🏽‍🦱	woman, curly haired: medium skin tone
-👩🏾‍🦱	woman, curly haired: medium-dark skin tone
-👩🏿‍🦱	woman, curly haired: dark skin tone
-👨‍🦲	man, bald
-👨🏻‍🦲	man, bald: light skin tone
-👨🏼‍🦲	man, bald: medium-light skin tone
-👨🏽‍🦲	man, bald: medium skin tone
-👨🏾‍🦲	man, bald: medium-dark skin tone
-👨🏿‍🦲	man, bald: dark skin tone
-👩‍🦲	woman, bald
-👩🏻‍🦲	woman, bald: light skin tone
-👩🏼‍🦲	woman, bald: medium-light skin tone
-👩🏽‍🦲	woman, bald: medium skin tone
-👩🏾‍🦲	woman, bald: medium-dark skin tone
-👩🏿‍🦲	woman, bald: dark skin tone
-👨‍🦳	man, white haired
-👨🏻‍🦳	man, white haired: light skin tone
-👨🏼‍🦳	man, white haired: medium-light skin tone
-👨🏽‍🦳	man, white haired: medium skin tone
-👨🏾‍🦳	man, white haired: medium-dark skin tone
-👨🏿‍🦳	man, white haired: dark skin tone
-👩‍🦳	woman, white haired
-👩🏻‍🦳	woman, white haired: light skin tone
-👩🏼‍🦳	woman, white haired: medium-light skin tone
-👩🏽‍🦳	woman, white haired: medium skin tone
-👩🏾‍🦳	woman, white haired: medium-dark skin tone
-👩🏿‍🦳	woman, white haired: dark skin tone
-🤵	man in tuxedo
-🤵🏻	man in tuxedo: light skin tone
-🤵🏼	man in tuxedo: medium-light skin tone
-🤵🏽	man in tuxedo: medium skin tone
-🤵🏾	man in tuxedo: medium-dark skin tone
-🤵🏿	man in tuxedo: dark skin tone
-👰	bride with veil
-👰🏻	bride with veil: light skin tone
-👰🏼	bride with veil: medium-light skin tone
-👰🏽	bride with veil: medium skin tone
-👰🏾	bride with veil: medium-dark skin tone
-👰🏿	bride with veil: dark skin tone
-🤰	pregnant woman
-🤰🏻	pregnant woman: light skin tone
-🤰🏼	pregnant woman: medium-light skin tone
-🤰🏽	pregnant woman: medium skin tone
-🤰🏾	pregnant woman: medium-dark skin tone
-🤰🏿	pregnant woman: dark skin tone
-🤱	breast-feeding
-🤱🏻	breast-feeding: light skin tone
-🤱🏼	breast-feeding: medium-light skin tone
-🤱🏽	breast-feeding: medium skin tone
-🤱🏾	breast-feeding: medium-dark skin tone
-🤱🏿	breast-feeding: dark skin tone
-👼	baby angel
-👼🏻	baby angel: light skin tone
-👼🏼	baby angel: medium-light skin tone
-👼🏽	baby angel: medium skin tone
-👼🏾	baby angel: medium-dark skin tone
-👼🏿	baby angel: dark skin tone
-🎅	Santa Claus
-🎅🏻	Santa Claus: light skin tone
-🎅🏼	Santa Claus: medium-light skin tone
-🎅🏽	Santa Claus: medium skin tone
-🎅🏾	Santa Claus: medium-dark skin tone
-🎅🏿	Santa Claus: dark skin tone
-🤶	Mrs. Claus
-🤶🏻	Mrs. Claus: light skin tone
-🤶🏼	Mrs. Claus: medium-light skin tone
-🤶🏽	Mrs. Claus: medium skin tone
-🤶🏾	Mrs. Claus: medium-dark skin tone
-🤶🏿	Mrs. Claus: dark skin tone
-🦸	superhero
-🦸🏻	superhero: light skin tone
-🦸🏼	superhero: medium-light skin tone
-🦸🏽	superhero: medium skin tone
-🦸🏾	superhero: medium-dark skin tone
-🦸🏿	superhero: dark skin tone
-🦸‍♀️	woman superhero
-🦸‍♀	woman superhero
-🦸🏻‍♀️	woman superhero: light skin tone
-🦸🏻‍♀	woman superhero: light skin tone
-🦸🏼‍♀️	woman superhero: medium-light skin tone
-🦸🏼‍♀	woman superhero: medium-light skin tone
-🦸🏽‍♀️	woman superhero: medium skin tone
-🦸🏽‍♀	woman superhero: medium skin tone
-🦸🏾‍♀️	woman superhero: medium-dark skin tone
-🦸🏾‍♀	woman superhero: medium-dark skin tone
-🦸🏿‍♀️	woman superhero: dark skin tone
-🦸🏿‍♀	woman superhero: dark skin tone
-🦸‍♂️	man superhero
-🦸‍♂	man superhero
-🦸🏻‍♂️	man superhero: light skin tone
-🦸🏻‍♂	man superhero: light skin tone
-🦸🏼‍♂️	man superhero: medium-light skin tone
-🦸🏼‍♂	man superhero: medium-light skin tone
-🦸🏽‍♂️	man superhero: medium skin tone
-🦸🏽‍♂	man superhero: medium skin tone
-🦸🏾‍♂️	man superhero: medium-dark skin tone
-🦸🏾‍♂	man superhero: medium-dark skin tone
-🦸🏿‍♂️	man superhero: dark skin tone
-🦸🏿‍♂	man superhero: dark skin tone
-🦹	supervillain
-🦹🏻	supervillain: light skin tone
-🦹🏼	supervillain: medium-light skin tone
-🦹🏽	supervillain: medium skin tone
-🦹🏾	supervillain: medium-dark skin tone
-🦹🏿	supervillain: dark skin tone
-🦹‍♀️	woman supervillain
-🦹‍♀	woman supervillain
-🦹🏻‍♀️	woman supervillain: light skin tone
-🦹🏻‍♀	woman supervillain: light skin tone
-🦹🏼‍♀️	woman supervillain: medium-light skin tone
-🦹🏼‍♀	woman supervillain: medium-light skin tone
-🦹🏽‍♀️	woman supervillain: medium skin tone
-🦹🏽‍♀	woman supervillain: medium skin tone
-🦹🏾‍♀️	woman supervillain: medium-dark skin tone
-🦹🏾‍♀	woman supervillain: medium-dark skin tone
-🦹🏿‍♀️	woman supervillain: dark skin tone
-🦹🏿‍♀	woman supervillain: dark skin tone
-🦹‍♂️	man supervillain
-🦹‍♂	man supervillain
-🦹🏻‍♂️	man supervillain: light skin tone
-🦹🏻‍♂	man supervillain: light skin tone
-🦹🏼‍♂️	man supervillain: medium-light skin tone
-🦹🏼‍♂	man supervillain: medium-light skin tone
-🦹🏽‍♂️	man supervillain: medium skin tone
-🦹🏽‍♂	man supervillain: medium skin tone
-🦹🏾‍♂️	man supervillain: medium-dark skin tone
-🦹🏾‍♂	man supervillain: medium-dark skin tone
-🦹🏿‍♂️	man supervillain: dark skin tone
-🦹🏿‍♂	man supervillain: dark skin tone
-🧙	mage
-🧙🏻	mage: light skin tone
-🧙🏼	mage: medium-light skin tone
-🧙🏽	mage: medium skin tone
-🧙🏾	mage: medium-dark skin tone
-🧙🏿	mage: dark skin tone
-🧙‍♀️	woman mage
-🧙‍♀	woman mage
-🧙🏻‍♀️	woman mage: light skin tone
-🧙🏻‍♀	woman mage: light skin tone
-🧙🏼‍♀️	woman mage: medium-light skin tone
-🧙🏼‍♀	woman mage: medium-light skin tone
-🧙🏽‍♀️	woman mage: medium skin tone
-🧙🏽‍♀	woman mage: medium skin tone
-🧙🏾‍♀️	woman mage: medium-dark skin tone
-🧙🏾‍♀	woman mage: medium-dark skin tone
-🧙🏿‍♀️	woman mage: dark skin tone
-🧙🏿‍♀	woman mage: dark skin tone
-🧙‍♂️	man mage
-🧙‍♂	man mage
-🧙🏻‍♂️	man mage: light skin tone
-🧙🏻‍♂	man mage: light skin tone
-🧙🏼‍♂️	man mage: medium-light skin tone
-🧙🏼‍♂	man mage: medium-light skin tone
-🧙🏽‍♂️	man mage: medium skin tone
-🧙🏽‍♂	man mage: medium skin tone
-🧙🏾‍♂️	man mage: medium-dark skin tone
-🧙🏾‍♂	man mage: medium-dark skin tone
-🧙🏿‍♂️	man mage: dark skin tone
-🧙🏿‍♂	man mage: dark skin tone
-🧚	fairy
-🧚🏻	fairy: light skin tone
-🧚🏼	fairy: medium-light skin tone
-🧚🏽	fairy: medium skin tone
-🧚🏾	fairy: medium-dark skin tone
-🧚🏿	fairy: dark skin tone
-🧚‍♀️	woman fairy
-🧚‍♀	woman fairy
-🧚🏻‍♀️	woman fairy: light skin tone
-🧚🏻‍♀	woman fairy: light skin tone
-🧚🏼‍♀️	woman fairy: medium-light skin tone
-🧚🏼‍♀	woman fairy: medium-light skin tone
-🧚🏽‍♀️	woman fairy: medium skin tone
-🧚🏽‍♀	woman fairy: medium skin tone
-🧚🏾‍♀️	woman fairy: medium-dark skin tone
-🧚🏾‍♀	woman fairy: medium-dark skin tone
-🧚🏿‍♀️	woman fairy: dark skin tone
-🧚🏿‍♀	woman fairy: dark skin tone
-🧚‍♂️	man fairy
-🧚‍♂	man fairy
-🧚🏻‍♂️	man fairy: light skin tone
-🧚🏻‍♂	man fairy: light skin tone
-🧚🏼‍♂️	man fairy: medium-light skin tone
-🧚🏼‍♂	man fairy: medium-light skin tone
-🧚🏽‍♂️	man fairy: medium skin tone
-🧚🏽‍♂	man fairy: medium skin tone
-🧚🏾‍♂️	man fairy: medium-dark skin tone
-🧚🏾‍♂	man fairy: medium-dark skin tone
-🧚🏿‍♂️	man fairy: dark skin tone
-🧚🏿‍♂	man fairy: dark skin tone
-🧛	vampire
-🧛🏻	vampire: light skin tone
-🧛🏼	vampire: medium-light skin tone
-🧛🏽	vampire: medium skin tone
-🧛🏾	vampire: medium-dark skin tone
-🧛🏿	vampire: dark skin tone
-🧛‍♀️	woman vampire
-🧛‍♀	woman vampire
-🧛🏻‍♀️	woman vampire: light skin tone
-🧛🏻‍♀	woman vampire: light skin tone
-🧛🏼‍♀️	woman vampire: medium-light skin tone
-🧛🏼‍♀	woman vampire: medium-light skin tone
-🧛🏽‍♀️	woman vampire: medium skin tone
-🧛🏽‍♀	woman vampire: medium skin tone
-🧛🏾‍♀️	woman vampire: medium-dark skin tone
-🧛🏾‍♀	woman vampire: medium-dark skin tone
-🧛🏿‍♀️	woman vampire: dark skin tone
-🧛🏿‍♀	woman vampire: dark skin tone
-🧛‍♂️	man vampire
-🧛‍♂	man vampire
-🧛🏻‍♂️	man vampire: light skin tone
-🧛🏻‍♂	man vampire: light skin tone
-🧛🏼‍♂️	man vampire: medium-light skin tone
-🧛🏼‍♂	man vampire: medium-light skin tone
-🧛🏽‍♂️	man vampire: medium skin tone
-🧛🏽‍♂	man vampire: medium skin tone
-🧛🏾‍♂️	man vampire: medium-dark skin tone
-🧛🏾‍♂	man vampire: medium-dark skin tone
-🧛🏿‍♂️	man vampire: dark skin tone
-🧛🏿‍♂	man vampire: dark skin tone
-🧜	merperson
-🧜🏻	merperson: light skin tone
-🧜🏼	merperson: medium-light skin tone
-🧜🏽	merperson: medium skin tone
-🧜🏾	merperson: medium-dark skin tone
-🧜🏿	merperson: dark skin tone
-🧜‍♀️	mermaid
-🧜‍♀	mermaid
-🧜🏻‍♀️	mermaid: light skin tone
-🧜🏻‍♀	mermaid: light skin tone
-🧜🏼‍♀️	mermaid: medium-light skin tone
-🧜🏼‍♀	mermaid: medium-light skin tone
-🧜🏽‍♀️	mermaid: medium skin tone
-🧜🏽‍♀	mermaid: medium skin tone
-🧜🏾‍♀️	mermaid: medium-dark skin tone
-🧜🏾‍♀	mermaid: medium-dark skin tone
-🧜🏿‍♀️	mermaid: dark skin tone
-🧜🏿‍♀	mermaid: dark skin tone
-🧜‍♂️	merman
-🧜‍♂	merman
-🧜🏻‍♂️	merman: light skin tone
-🧜🏻‍♂	merman: light skin tone
-🧜🏼‍♂️	merman: medium-light skin tone
-🧜🏼‍♂	merman: medium-light skin tone
-🧜🏽‍♂️	merman: medium skin tone
-🧜🏽‍♂	merman: medium skin tone
-🧜🏾‍♂️	merman: medium-dark skin tone
-🧜🏾‍♂	merman: medium-dark skin tone
-🧜🏿‍♂️	merman: dark skin tone
-🧜🏿‍♂	merman: dark skin tone
-🧝	elf
-🧝🏻	elf: light skin tone
-🧝🏼	elf: medium-light skin tone
-🧝🏽	elf: medium skin tone
-🧝🏾	elf: medium-dark skin tone
-🧝🏿	elf: dark skin tone
-🧝‍♀️	woman elf
-🧝‍♀	woman elf
-🧝🏻‍♀️	woman elf: light skin tone
-🧝🏻‍♀	woman elf: light skin tone
-🧝🏼‍♀️	woman elf: medium-light skin tone
-🧝🏼‍♀	woman elf: medium-light skin tone
-🧝🏽‍♀️	woman elf: medium skin tone
-🧝🏽‍♀	woman elf: medium skin tone
-🧝🏾‍♀️	woman elf: medium-dark skin tone
-🧝🏾‍♀	woman elf: medium-dark skin tone
-🧝🏿‍♀️	woman elf: dark skin tone
-🧝🏿‍♀	woman elf: dark skin tone
-🧝‍♂️	man elf
-🧝‍♂	man elf
-🧝🏻‍♂️	man elf: light skin tone
-🧝🏻‍♂	man elf: light skin tone
-🧝🏼‍♂️	man elf: medium-light skin tone
-🧝🏼‍♂	man elf: medium-light skin tone
-🧝🏽‍♂️	man elf: medium skin tone
-🧝🏽‍♂	man elf: medium skin tone
-🧝🏾‍♂️	man elf: medium-dark skin tone
-🧝🏾‍♂	man elf: medium-dark skin tone
-🧝🏿‍♂️	man elf: dark skin tone
-🧝🏿‍♂	man elf: dark skin tone
-🧞	genie
-🧞‍♀️	woman genie
-🧞‍♀	woman genie
-🧞‍♂️	man genie
-🧞‍♂	man genie
-🧟	zombie
-🧟‍♀️	woman zombie
-🧟‍♀	woman zombie
-🧟‍♂️	man zombie
-🧟‍♂	man zombie
-🙍	person frowning
-🙍🏻	person frowning: light skin tone
-🙍🏼	person frowning: medium-light skin tone
-🙍🏽	person frowning: medium skin tone
-🙍🏾	person frowning: medium-dark skin tone
-🙍🏿	person frowning: dark skin tone
-🙍‍♂️	man frowning
-🙍‍♂	man frowning
-🙍🏻‍♂️	man frowning: light skin tone
-🙍🏻‍♂	man frowning: light skin tone
-🙍🏼‍♂️	man frowning: medium-light skin tone
-🙍🏼‍♂	man frowning: medium-light skin tone
-🙍🏽‍♂️	man frowning: medium skin tone
-🙍🏽‍♂	man frowning: medium skin tone
-🙍🏾‍♂️	man frowning: medium-dark skin tone
-🙍🏾‍♂	man frowning: medium-dark skin tone
-🙍🏿‍♂️	man frowning: dark skin tone
-🙍🏿‍♂	man frowning: dark skin tone
-🙍‍♀️	woman frowning
-🙍‍♀	woman frowning
-🙍🏻‍♀️	woman frowning: light skin tone
-🙍🏻‍♀	woman frowning: light skin tone
-🙍🏼‍♀️	woman frowning: medium-light skin tone
-🙍🏼‍♀	woman frowning: medium-light skin tone
-🙍🏽‍♀️	woman frowning: medium skin tone
-🙍🏽‍♀	woman frowning: medium skin tone
-🙍🏾‍♀️	woman frowning: medium-dark skin tone
-🙍🏾‍♀	woman frowning: medium-dark skin tone
-🙍🏿‍♀️	woman frowning: dark skin tone
-🙍🏿‍♀	woman frowning: dark skin tone
-🙎	person pouting
-🙎🏻	person pouting: light skin tone
-🙎🏼	person pouting: medium-light skin tone
-🙎🏽	person pouting: medium skin tone
-🙎🏾	person pouting: medium-dark skin tone
-🙎🏿	person pouting: dark skin tone
-🙎‍♂️	man pouting
-🙎‍♂	man pouting
-🙎🏻‍♂️	man pouting: light skin tone
-🙎🏻‍♂	man pouting: light skin tone
-🙎🏼‍♂️	man pouting: medium-light skin tone
-🙎🏼‍♂	man pouting: medium-light skin tone
-🙎🏽‍♂️	man pouting: medium skin tone
-🙎🏽‍♂	man pouting: medium skin tone
-🙎🏾‍♂️	man pouting: medium-dark skin tone
-🙎🏾‍♂	man pouting: medium-dark skin tone
-🙎🏿‍♂️	man pouting: dark skin tone
-🙎🏿‍♂	man pouting: dark skin tone
-🙎‍♀️	woman pouting
-🙎‍♀	woman pouting
-🙎🏻‍♀️	woman pouting: light skin tone
-🙎🏻‍♀	woman pouting: light skin tone
-🙎🏼‍♀️	woman pouting: medium-light skin tone
-🙎🏼‍♀	woman pouting: medium-light skin tone
-🙎🏽‍♀️	woman pouting: medium skin tone
-🙎🏽‍♀	woman pouting: medium skin tone
-🙎🏾‍♀️	woman pouting: medium-dark skin tone
-🙎🏾‍♀	woman pouting: medium-dark skin tone
-🙎🏿‍♀️	woman pouting: dark skin tone
-🙎🏿‍♀	woman pouting: dark skin tone
-🙅	person gesturing NO
-🙅🏻	person gesturing NO: light skin tone
-🙅🏼	person gesturing NO: medium-light skin tone
-🙅🏽	person gesturing NO: medium skin tone
-🙅🏾	person gesturing NO: medium-dark skin tone
-🙅🏿	person gesturing NO: dark skin tone
-🙅‍♂️	man gesturing NO
-🙅‍♂	man gesturing NO
-🙅🏻‍♂️	man gesturing NO: light skin tone
-🙅🏻‍♂	man gesturing NO: light skin tone
-🙅🏼‍♂️	man gesturing NO: medium-light skin tone
-🙅🏼‍♂	man gesturing NO: medium-light skin tone
-🙅🏽‍♂️	man gesturing NO: medium skin tone
-🙅🏽‍♂	man gesturing NO: medium skin tone
-🙅🏾‍♂️	man gesturing NO: medium-dark skin tone
-🙅🏾‍♂	man gesturing NO: medium-dark skin tone
-🙅🏿‍♂️	man gesturing NO: dark skin tone
-🙅🏿‍♂	man gesturing NO: dark skin tone
-🙅‍♀️	woman gesturing NO
-🙅‍♀	woman gesturing NO
-🙅🏻‍♀️	woman gesturing NO: light skin tone
-🙅🏻‍♀	woman gesturing NO: light skin tone
-🙅🏼‍♀️	woman gesturing NO: medium-light skin tone
-🙅🏼‍♀	woman gesturing NO: medium-light skin tone
-🙅🏽‍♀️	woman gesturing NO: medium skin tone
-🙅🏽‍♀	woman gesturing NO: medium skin tone
-🙅🏾‍♀️	woman gesturing NO: medium-dark skin tone
-🙅🏾‍♀	woman gesturing NO: medium-dark skin tone
-🙅🏿‍♀️	woman gesturing NO: dark skin tone
-🙅🏿‍♀	woman gesturing NO: dark skin tone
-🙆	person gesturing OK
-🙆🏻	person gesturing OK: light skin tone
-🙆🏼	person gesturing OK: medium-light skin tone
-🙆🏽	person gesturing OK: medium skin tone
-🙆🏾	person gesturing OK: medium-dark skin tone
-🙆🏿	person gesturing OK: dark skin tone
-🙆‍♂️	man gesturing OK
-🙆‍♂	man gesturing OK
-🙆🏻‍♂️	man gesturing OK: light skin tone
-🙆🏻‍♂	man gesturing OK: light skin tone
-🙆🏼‍♂️	man gesturing OK: medium-light skin tone
-🙆🏼‍♂	man gesturing OK: medium-light skin tone
-🙆🏽‍♂️	man gesturing OK: medium skin tone
-🙆🏽‍♂	man gesturing OK: medium skin tone
-🙆🏾‍♂️	man gesturing OK: medium-dark skin tone
-🙆🏾‍♂	man gesturing OK: medium-dark skin tone
-🙆🏿‍♂️	man gesturing OK: dark skin tone
-🙆🏿‍♂	man gesturing OK: dark skin tone
-🙆‍♀️	woman gesturing OK
-🙆‍♀	woman gesturing OK
-🙆🏻‍♀️	woman gesturing OK: light skin tone
-🙆🏻‍♀	woman gesturing OK: light skin tone
-🙆🏼‍♀️	woman gesturing OK: medium-light skin tone
-🙆🏼‍♀	woman gesturing OK: medium-light skin tone
-🙆🏽‍♀️	woman gesturing OK: medium skin tone
-🙆🏽‍♀	woman gesturing OK: medium skin tone
-🙆🏾‍♀️	woman gesturing OK: medium-dark skin tone
-🙆🏾‍♀	woman gesturing OK: medium-dark skin tone
-🙆🏿‍♀️	woman gesturing OK: dark skin tone
-🙆🏿‍♀	woman gesturing OK: dark skin tone
-💁	person tipping hand
-💁🏻	person tipping hand: light skin tone
-💁🏼	person tipping hand: medium-light skin tone
-💁🏽	person tipping hand: medium skin tone
-💁🏾	person tipping hand: medium-dark skin tone
-💁🏿	person tipping hand: dark skin tone
-💁‍♂️	man tipping hand
-💁‍♂	man tipping hand
-💁🏻‍♂️	man tipping hand: light skin tone
-💁🏻‍♂	man tipping hand: light skin tone
-💁🏼‍♂️	man tipping hand: medium-light skin tone
-💁🏼‍♂	man tipping hand: medium-light skin tone
-💁🏽‍♂️	man tipping hand: medium skin tone
-💁🏽‍♂	man tipping hand: medium skin tone
-💁🏾‍♂️	man tipping hand: medium-dark skin tone
-💁🏾‍♂	man tipping hand: medium-dark skin tone
-💁🏿‍♂️	man tipping hand: dark skin tone
-💁🏿‍♂	man tipping hand: dark skin tone
-💁‍♀️	woman tipping hand
-💁‍♀	woman tipping hand
-💁🏻‍♀️	woman tipping hand: light skin tone
-💁🏻‍♀	woman tipping hand: light skin tone
-💁🏼‍♀️	woman tipping hand: medium-light skin tone
-💁🏼‍♀	woman tipping hand: medium-light skin tone
-💁🏽‍♀️	woman tipping hand: medium skin tone
-💁🏽‍♀	woman tipping hand: medium skin tone
-💁🏾‍♀️	woman tipping hand: medium-dark skin tone
-💁🏾‍♀	woman tipping hand: medium-dark skin tone
-💁🏿‍♀️	woman tipping hand: dark skin tone
-💁🏿‍♀	woman tipping hand: dark skin tone
-🙋	person raising hand
-🙋🏻	person raising hand: light skin tone
-🙋🏼	person raising hand: medium-light skin tone
-🙋🏽	person raising hand: medium skin tone
-🙋🏾	person raising hand: medium-dark skin tone
-🙋🏿	person raising hand: dark skin tone
-🙋‍♂️	man raising hand
-🙋‍♂	man raising hand
-🙋🏻‍♂️	man raising hand: light skin tone
-🙋🏻‍♂	man raising hand: light skin tone
-🙋🏼‍♂️	man raising hand: medium-light skin tone
-🙋🏼‍♂	man raising hand: medium-light skin tone
-🙋🏽‍♂️	man raising hand: medium skin tone
-🙋🏽‍♂	man raising hand: medium skin tone
-🙋🏾‍♂️	man raising hand: medium-dark skin tone
-🙋🏾‍♂	man raising hand: medium-dark skin tone
-🙋🏿‍♂️	man raising hand: dark skin tone
-🙋🏿‍♂	man raising hand: dark skin tone
-🙋‍♀️	woman raising hand
-🙋‍♀	woman raising hand
-🙋🏻‍♀️	woman raising hand: light skin tone
-🙋🏻‍♀	woman raising hand: light skin tone
-🙋🏼‍♀️	woman raising hand: medium-light skin tone
-🙋🏼‍♀	woman raising hand: medium-light skin tone
-🙋🏽‍♀️	woman raising hand: medium skin tone
-🙋🏽‍♀	woman raising hand: medium skin tone
-🙋🏾‍♀️	woman raising hand: medium-dark skin tone
-🙋🏾‍♀	woman raising hand: medium-dark skin tone
-🙋🏿‍♀️	woman raising hand: dark skin tone
-🙋🏿‍♀	woman raising hand: dark skin tone
-🙇	person bowing
-🙇🏻	person bowing: light skin tone
-🙇🏼	person bowing: medium-light skin tone
-🙇🏽	person bowing: medium skin tone
-🙇🏾	person bowing: medium-dark skin tone
-🙇🏿	person bowing: dark skin tone
-🙇‍♂️	man bowing
-🙇‍♂	man bowing
-🙇🏻‍♂️	man bowing: light skin tone
-🙇🏻‍♂	man bowing: light skin tone
-🙇🏼‍♂️	man bowing: medium-light skin tone
-🙇🏼‍♂	man bowing: medium-light skin tone
-🙇🏽‍♂️	man bowing: medium skin tone
-🙇🏽‍♂	man bowing: medium skin tone
-🙇🏾‍♂️	man bowing: medium-dark skin tone
-🙇🏾‍♂	man bowing: medium-dark skin tone
-🙇🏿‍♂️	man bowing: dark skin tone
-🙇🏿‍♂	man bowing: dark skin tone
-🙇‍♀️	woman bowing
-🙇‍♀	woman bowing
-🙇🏻‍♀️	woman bowing: light skin tone
-🙇🏻‍♀	woman bowing: light skin tone
-🙇🏼‍♀️	woman bowing: medium-light skin tone
-🙇🏼‍♀	woman bowing: medium-light skin tone
-🙇🏽‍♀️	woman bowing: medium skin tone
-🙇🏽‍♀	woman bowing: medium skin tone
-🙇🏾‍♀️	woman bowing: medium-dark skin tone
-🙇🏾‍♀	woman bowing: medium-dark skin tone
-🙇🏿‍♀️	woman bowing: dark skin tone
-🙇🏿‍♀	woman bowing: dark skin tone
-🤦	person facepalming
-🤦🏻	person facepalming: light skin tone
-🤦🏼	person facepalming: medium-light skin tone
-🤦🏽	person facepalming: medium skin tone
-🤦🏾	person facepalming: medium-dark skin tone
-🤦🏿	person facepalming: dark skin tone
-🤦‍♂️	man facepalming
-🤦‍♂	man facepalming
-🤦🏻‍♂️	man facepalming: light skin tone
-🤦🏻‍♂	man facepalming: light skin tone
-🤦🏼‍♂️	man facepalming: medium-light skin tone
-🤦🏼‍♂	man facepalming: medium-light skin tone
-🤦🏽‍♂️	man facepalming: medium skin tone
-🤦🏽‍♂	man facepalming: medium skin tone
-🤦🏾‍♂️	man facepalming: medium-dark skin tone
-🤦🏾‍♂	man facepalming: medium-dark skin tone
-🤦🏿‍♂️	man facepalming: dark skin tone
-🤦🏿‍♂	man facepalming: dark skin tone
-🤦‍♀️	woman facepalming
-🤦‍♀	woman facepalming
-🤦🏻‍♀️	woman facepalming: light skin tone
-🤦🏻‍♀	woman facepalming: light skin tone
-🤦🏼‍♀️	woman facepalming: medium-light skin tone
-🤦🏼‍♀	woman facepalming: medium-light skin tone
-🤦🏽‍♀️	woman facepalming: medium skin tone
-🤦🏽‍♀	woman facepalming: medium skin tone
-🤦🏾‍♀️	woman facepalming: medium-dark skin tone
-🤦🏾‍♀	woman facepalming: medium-dark skin tone
-🤦🏿‍♀️	woman facepalming: dark skin tone
-🤦🏿‍♀	woman facepalming: dark skin tone
-🤷	person shrugging
-🤷🏻	person shrugging: light skin tone
-🤷🏼	person shrugging: medium-light skin tone
-🤷🏽	person shrugging: medium skin tone
-🤷🏾	person shrugging: medium-dark skin tone
-🤷🏿	person shrugging: dark skin tone
-🤷‍♂️	man shrugging
-🤷‍♂	man shrugging
-🤷🏻‍♂️	man shrugging: light skin tone
-🤷🏻‍♂	man shrugging: light skin tone
-🤷🏼‍♂️	man shrugging: medium-light skin tone
-🤷🏼‍♂	man shrugging: medium-light skin tone
-🤷🏽‍♂️	man shrugging: medium skin tone
-🤷🏽‍♂	man shrugging: medium skin tone
-🤷🏾‍♂️	man shrugging: medium-dark skin tone
-🤷🏾‍♂	man shrugging: medium-dark skin tone
-🤷🏿‍♂️	man shrugging: dark skin tone
-🤷🏿‍♂	man shrugging: dark skin tone
-🤷‍♀️	woman shrugging
-🤷‍♀	woman shrugging
-🤷🏻‍♀️	woman shrugging: light skin tone
-🤷🏻‍♀	woman shrugging: light skin tone
-🤷🏼‍♀️	woman shrugging: medium-light skin tone
-🤷🏼‍♀	woman shrugging: medium-light skin tone
-🤷🏽‍♀️	woman shrugging: medium skin tone
-🤷🏽‍♀	woman shrugging: medium skin tone
-🤷🏾‍♀️	woman shrugging: medium-dark skin tone
-🤷🏾‍♀	woman shrugging: medium-dark skin tone
-🤷🏿‍♀️	woman shrugging: dark skin tone
-🤷🏿‍♀	woman shrugging: dark skin tone
-💆	person getting massage
-💆🏻	person getting massage: light skin tone
-💆🏼	person getting massage: medium-light skin tone
-💆🏽	person getting massage: medium skin tone
-💆🏾	person getting massage: medium-dark skin tone
-💆🏿	person getting massage: dark skin tone
-💆‍♂️	man getting massage
-💆‍♂	man getting massage
-💆🏻‍♂️	man getting massage: light skin tone
-💆🏻‍♂	man getting massage: light skin tone
-💆🏼‍♂️	man getting massage: medium-light skin tone
-💆🏼‍♂	man getting massage: medium-light skin tone
-💆🏽‍♂️	man getting massage: medium skin tone
-💆🏽‍♂	man getting massage: medium skin tone
-💆🏾‍♂️	man getting massage: medium-dark skin tone
-💆🏾‍♂	man getting massage: medium-dark skin tone
-💆🏿‍♂️	man getting massage: dark skin tone
-💆🏿‍♂	man getting massage: dark skin tone
-💆‍♀️	woman getting massage
-💆‍♀	woman getting massage
-💆🏻‍♀️	woman getting massage: light skin tone
-💆🏻‍♀	woman getting massage: light skin tone
-💆🏼‍♀️	woman getting massage: medium-light skin tone
-💆🏼‍♀	woman getting massage: medium-light skin tone
-💆🏽‍♀️	woman getting massage: medium skin tone
-💆🏽‍♀	woman getting massage: medium skin tone
-💆🏾‍♀️	woman getting massage: medium-dark skin tone
-💆🏾‍♀	woman getting massage: medium-dark skin tone
-💆🏿‍♀️	woman getting massage: dark skin tone
-💆🏿‍♀	woman getting massage: dark skin tone
-💇	person getting haircut
-💇🏻	person getting haircut: light skin tone
-💇🏼	person getting haircut: medium-light skin tone
-💇🏽	person getting haircut: medium skin tone
-💇🏾	person getting haircut: medium-dark skin tone
-💇🏿	person getting haircut: dark skin tone
-💇‍♂️	man getting haircut
-💇‍♂	man getting haircut
-💇🏻‍♂️	man getting haircut: light skin tone
-💇🏻‍♂	man getting haircut: light skin tone
-💇🏼‍♂️	man getting haircut: medium-light skin tone
-💇🏼‍♂	man getting haircut: medium-light skin tone
-💇🏽‍♂️	man getting haircut: medium skin tone
-💇🏽‍♂	man getting haircut: medium skin tone
-💇🏾‍♂️	man getting haircut: medium-dark skin tone
-💇🏾‍♂	man getting haircut: medium-dark skin tone
-💇🏿‍♂️	man getting haircut: dark skin tone
-💇🏿‍♂	man getting haircut: dark skin tone
-💇‍♀️	woman getting haircut
-💇‍♀	woman getting haircut
-💇🏻‍♀️	woman getting haircut: light skin tone
-💇🏻‍♀	woman getting haircut: light skin tone
-💇🏼‍♀️	woman getting haircut: medium-light skin tone
-💇🏼‍♀	woman getting haircut: medium-light skin tone
-💇🏽‍♀️	woman getting haircut: medium skin tone
-💇🏽‍♀	woman getting haircut: medium skin tone
-💇🏾‍♀️	woman getting haircut: medium-dark skin tone
-💇🏾‍♀	woman getting haircut: medium-dark skin tone
-💇🏿‍♀️	woman getting haircut: dark skin tone
-💇🏿‍♀	woman getting haircut: dark skin tone
-🚶	person walking
-🚶🏻	person walking: light skin tone
-🚶🏼	person walking: medium-light skin tone
-🚶🏽	person walking: medium skin tone
-🚶🏾	person walking: medium-dark skin tone
-🚶🏿	person walking: dark skin tone
-🚶‍♂️	man walking
-🚶‍♂	man walking
-🚶🏻‍♂️	man walking: light skin tone
-🚶🏻‍♂	man walking: light skin tone
-🚶🏼‍♂️	man walking: medium-light skin tone
-🚶🏼‍♂	man walking: medium-light skin tone
-🚶🏽‍♂️	man walking: medium skin tone
-🚶🏽‍♂	man walking: medium skin tone
-🚶🏾‍♂️	man walking: medium-dark skin tone
-🚶🏾‍♂	man walking: medium-dark skin tone
-🚶🏿‍♂️	man walking: dark skin tone
-🚶🏿‍♂	man walking: dark skin tone
-🚶‍♀️	woman walking
-🚶‍♀	woman walking
-🚶🏻‍♀️	woman walking: light skin tone
-🚶🏻‍♀	woman walking: light skin tone
-🚶🏼‍♀️	woman walking: medium-light skin tone
-🚶🏼‍♀	woman walking: medium-light skin tone
-🚶🏽‍♀️	woman walking: medium skin tone
-🚶🏽‍♀	woman walking: medium skin tone
-🚶🏾‍♀️	woman walking: medium-dark skin tone
-🚶🏾‍♀	woman walking: medium-dark skin tone
-🚶🏿‍♀️	woman walking: dark skin tone
-🚶🏿‍♀	woman walking: dark skin tone
-🏃	person running
-🏃🏻	person running: light skin tone
-🏃🏼	person running: medium-light skin tone
-🏃🏽	person running: medium skin tone
-🏃🏾	person running: medium-dark skin tone
-🏃🏿	person running: dark skin tone
-🏃‍♂️	man running
-🏃‍♂	man running
-🏃🏻‍♂️	man running: light skin tone
-🏃🏻‍♂	man running: light skin tone
-🏃🏼‍♂️	man running: medium-light skin tone
-🏃🏼‍♂	man running: medium-light skin tone
-🏃🏽‍♂️	man running: medium skin tone
-🏃🏽‍♂	man running: medium skin tone
-🏃🏾‍♂️	man running: medium-dark skin tone
-🏃🏾‍♂	man running: medium-dark skin tone
-🏃🏿‍♂️	man running: dark skin tone
-🏃🏿‍♂	man running: dark skin tone
-🏃‍♀️	woman running
-🏃‍♀	woman running
-🏃🏻‍♀️	woman running: light skin tone
-🏃🏻‍♀	woman running: light skin tone
-🏃🏼‍♀️	woman running: medium-light skin tone
-🏃🏼‍♀	woman running: medium-light skin tone
-🏃🏽‍♀️	woman running: medium skin tone
-🏃🏽‍♀	woman running: medium skin tone
-🏃🏾‍♀️	woman running: medium-dark skin tone
-🏃🏾‍♀	woman running: medium-dark skin tone
-🏃🏿‍♀️	woman running: dark skin tone
-🏃🏿‍♀	woman running: dark skin tone
-💃	woman dancing
-💃🏻	woman dancing: light skin tone
-💃🏼	woman dancing: medium-light skin tone
-💃🏽	woman dancing: medium skin tone
-💃🏾	woman dancing: medium-dark skin tone
-💃🏿	woman dancing: dark skin tone
-🕺	man dancing
-🕺🏻	man dancing: light skin tone
-🕺🏼	man dancing: medium-light skin tone
-🕺🏽	man dancing: medium skin tone
-🕺🏾	man dancing: medium-dark skin tone
-🕺🏿	man dancing: dark skin tone
-👯	people with bunny ears
-👯‍♂️	men with bunny ears
-👯‍♂	men with bunny ears
-👯‍♀️	women with bunny ears
-👯‍♀	women with bunny ears
-🧖	person in steamy room
-🧖🏻	person in steamy room: light skin tone
-🧖🏼	person in steamy room: medium-light skin tone
-🧖🏽	person in steamy room: medium skin tone
-🧖🏾	person in steamy room: medium-dark skin tone
-🧖🏿	person in steamy room: dark skin tone
-🧖‍♀️	woman in steamy room
-🧖‍♀	woman in steamy room
-🧖🏻‍♀️	woman in steamy room: light skin tone
-🧖🏻‍♀	woman in steamy room: light skin tone
-🧖🏼‍♀️	woman in steamy room: medium-light skin tone
-🧖🏼‍♀	woman in steamy room: medium-light skin tone
-🧖🏽‍♀️	woman in steamy room: medium skin tone
-🧖🏽‍♀	woman in steamy room: medium skin tone
-🧖🏾‍♀️	woman in steamy room: medium-dark skin tone
-🧖🏾‍♀	woman in steamy room: medium-dark skin tone
-🧖🏿‍♀️	woman in steamy room: dark skin tone
-🧖🏿‍♀	woman in steamy room: dark skin tone
-🧖‍♂️	man in steamy room
-🧖‍♂	man in steamy room
-🧖🏻‍♂️	man in steamy room: light skin tone
-🧖🏻‍♂	man in steamy room: light skin tone
-🧖🏼‍♂️	man in steamy room: medium-light skin tone
-🧖🏼‍♂	man in steamy room: medium-light skin tone
-🧖🏽‍♂️	man in steamy room: medium skin tone
-🧖🏽‍♂	man in steamy room: medium skin tone
-🧖🏾‍♂️	man in steamy room: medium-dark skin tone
-🧖🏾‍♂	man in steamy room: medium-dark skin tone
-🧖🏿‍♂️	man in steamy room: dark skin tone
-🧖🏿‍♂	man in steamy room: dark skin tone
-🧗	person climbing
-🧗🏻	person climbing: light skin tone
-🧗🏼	person climbing: medium-light skin tone
-🧗🏽	person climbing: medium skin tone
-🧗🏾	person climbing: medium-dark skin tone
-🧗🏿	person climbing: dark skin tone
-🧗‍♀️	woman climbing
-🧗‍♀	woman climbing
-🧗🏻‍♀️	woman climbing: light skin tone
-🧗🏻‍♀	woman climbing: light skin tone
-🧗🏼‍♀️	woman climbing: medium-light skin tone
-🧗🏼‍♀	woman climbing: medium-light skin tone
-🧗🏽‍♀️	woman climbing: medium skin tone
-🧗🏽‍♀	woman climbing: medium skin tone
-🧗🏾‍♀️	woman climbing: medium-dark skin tone
-🧗🏾‍♀	woman climbing: medium-dark skin tone
-🧗🏿‍♀️	woman climbing: dark skin tone
-🧗🏿‍♀	woman climbing: dark skin tone
-🧗‍♂️	man climbing
-🧗‍♂	man climbing
-🧗🏻‍♂️	man climbing: light skin tone
-🧗🏻‍♂	man climbing: light skin tone
-🧗🏼‍♂️	man climbing: medium-light skin tone
-🧗🏼‍♂	man climbing: medium-light skin tone
-🧗🏽‍♂️	man climbing: medium skin tone
-🧗🏽‍♂	man climbing: medium skin tone
-🧗🏾‍♂️	man climbing: medium-dark skin tone
-🧗🏾‍♂	man climbing: medium-dark skin tone
-🧗🏿‍♂️	man climbing: dark skin tone
-🧗🏿‍♂	man climbing: dark skin tone
-🧘	person in lotus position
-🧘🏻	person in lotus position: light skin tone
-🧘🏼	person in lotus position: medium-light skin tone
-🧘🏽	person in lotus position: medium skin tone
-🧘🏾	person in lotus position: medium-dark skin tone
-🧘🏿	person in lotus position: dark skin tone
-🧘‍♀️	woman in lotus position
-🧘‍♀	woman in lotus position
-🧘🏻‍♀️	woman in lotus position: light skin tone
-🧘🏻‍♀	woman in lotus position: light skin tone
-🧘🏼‍♀️	woman in lotus position: medium-light skin tone
-🧘🏼‍♀	woman in lotus position: medium-light skin tone
-🧘🏽‍♀️	woman in lotus position: medium skin tone
-🧘🏽‍♀	woman in lotus position: medium skin tone
-🧘🏾‍♀️	woman in lotus position: medium-dark skin tone
-🧘🏾‍♀	woman in lotus position: medium-dark skin tone
-🧘🏿‍♀️	woman in lotus position: dark skin tone
-🧘🏿‍♀	woman in lotus position: dark skin tone
-🧘‍♂️	man in lotus position
-🧘‍♂	man in lotus position
-🧘🏻‍♂️	man in lotus position: light skin tone
-🧘🏻‍♂	man in lotus position: light skin tone
-🧘🏼‍♂️	man in lotus position: medium-light skin tone
-🧘🏼‍♂	man in lotus position: medium-light skin tone
-🧘🏽‍♂️	man in lotus position: medium skin tone
-🧘🏽‍♂	man in lotus position: medium skin tone
-🧘🏾‍♂️	man in lotus position: medium-dark skin tone
-🧘🏾‍♂	man in lotus position: medium-dark skin tone
-🧘🏿‍♂️	man in lotus position: dark skin tone
-🧘🏿‍♂	man in lotus position: dark skin tone
-🛀	person taking bath
-🛀🏻	person taking bath: light skin tone
-🛀🏼	person taking bath: medium-light skin tone
-🛀🏽	person taking bath: medium skin tone
-🛀🏾	person taking bath: medium-dark skin tone
-🛀🏿	person taking bath: dark skin tone
-🛌	person in bed
-🛌🏻	person in bed: light skin tone
-🛌🏼	person in bed: medium-light skin tone
-🛌🏽	person in bed: medium skin tone
-🛌🏾	person in bed: medium-dark skin tone
-🛌🏿	person in bed: dark skin tone
-🕴️	man in suit levitating
-🕴	man in suit levitating
-🕴🏻	man in suit levitating: light skin tone
-🕴🏼	man in suit levitating: medium-light skin tone
-🕴🏽	man in suit levitating: medium skin tone
-🕴🏾	man in suit levitating: medium-dark skin tone
-🕴🏿	man in suit levitating: dark skin tone
-🗣️	speaking head
-🗣	speaking head
-👤	bust in silhouette
-👥	busts in silhouette
-🤺	person fencing
-🏇	horse racing
-🏇🏻	horse racing: light skin tone
-🏇🏼	horse racing: medium-light skin tone
-🏇🏽	horse racing: medium skin tone
-🏇🏾	horse racing: medium-dark skin tone
-🏇🏿	horse racing: dark skin tone
-⛷️	skier
-⛷	skier
-🏂	snowboarder
-🏂🏻	snowboarder: light skin tone
-🏂🏼	snowboarder: medium-light skin tone
-🏂🏽	snowboarder: medium skin tone
-🏂🏾	snowboarder: medium-dark skin tone
-🏂🏿	snowboarder: dark skin tone
-🏌️	person golfing
-🏌	person golfing
-🏌🏻	person golfing: light skin tone
-🏌🏼	person golfing: medium-light skin tone
-🏌🏽	person golfing: medium skin tone
-🏌🏾	person golfing: medium-dark skin tone
-🏌🏿	person golfing: dark skin tone
-🏌️‍♂️	man golfing
-🏌‍♂️	man golfing
-🏌️‍♂	man golfing
-🏌‍♂	man golfing
-🏌🏻‍♂️	man golfing: light skin tone
-🏌🏻‍♂	man golfing: light skin tone
-🏌🏼‍♂️	man golfing: medium-light skin tone
-🏌🏼‍♂	man golfing: medium-light skin tone
-🏌🏽‍♂️	man golfing: medium skin tone
-🏌🏽‍♂	man golfing: medium skin tone
-🏌🏾‍♂️	man golfing: medium-dark skin tone
-🏌🏾‍♂	man golfing: medium-dark skin tone
-🏌🏿‍♂️	man golfing: dark skin tone
-🏌🏿‍♂	man golfing: dark skin tone
-🏌️‍♀️	woman golfing
-🏌‍♀️	woman golfing
-🏌️‍♀	woman golfing
-🏌‍♀	woman golfing
-🏌🏻‍♀️	woman golfing: light skin tone
-🏌🏻‍♀	woman golfing: light skin tone
-🏌🏼‍♀️	woman golfing: medium-light skin tone
-🏌🏼‍♀	woman golfing: medium-light skin tone
-🏌🏽‍♀️	woman golfing: medium skin tone
-🏌🏽‍♀	woman golfing: medium skin tone
-🏌🏾‍♀️	woman golfing: medium-dark skin tone
-🏌🏾‍♀	woman golfing: medium-dark skin tone
-🏌🏿‍♀️	woman golfing: dark skin tone
-🏌🏿‍♀	woman golfing: dark skin tone
-🏄	person surfing
-🏄🏻	person surfing: light skin tone
-🏄🏼	person surfing: medium-light skin tone
-🏄🏽	person surfing: medium skin tone
-🏄🏾	person surfing: medium-dark skin tone
-🏄🏿	person surfing: dark skin tone
-🏄‍♂️	man surfing
-🏄‍♂	man surfing
-🏄🏻‍♂️	man surfing: light skin tone
-🏄🏻‍♂	man surfing: light skin tone
-🏄🏼‍♂️	man surfing: medium-light skin tone
-🏄🏼‍♂	man surfing: medium-light skin tone
-🏄🏽‍♂️	man surfing: medium skin tone
-🏄🏽‍♂	man surfing: medium skin tone
-🏄🏾‍♂️	man surfing: medium-dark skin tone
-🏄🏾‍♂	man surfing: medium-dark skin tone
-🏄🏿‍♂️	man surfing: dark skin tone
-🏄🏿‍♂	man surfing: dark skin tone
-🏄‍♀️	woman surfing
-🏄‍♀	woman surfing
-🏄🏻‍♀️	woman surfing: light skin tone
-🏄🏻‍♀	woman surfing: light skin tone
-🏄🏼‍♀️	woman surfing: medium-light skin tone
-🏄🏼‍♀	woman surfing: medium-light skin tone
-🏄🏽‍♀️	woman surfing: medium skin tone
-🏄🏽‍♀	woman surfing: medium skin tone
-🏄🏾‍♀️	woman surfing: medium-dark skin tone
-🏄🏾‍♀	woman surfing: medium-dark skin tone
-🏄🏿‍♀️	woman surfing: dark skin tone
-🏄🏿‍♀	woman surfing: dark skin tone
-🚣	person rowing boat
-🚣🏻	person rowing boat: light skin tone
-🚣🏼	person rowing boat: medium-light skin tone
-🚣🏽	person rowing boat: medium skin tone
-🚣🏾	person rowing boat: medium-dark skin tone
-🚣🏿	person rowing boat: dark skin tone
-🚣‍♂️	man rowing boat
-🚣‍♂	man rowing boat
-🚣🏻‍♂️	man rowing boat: light skin tone
-🚣🏻‍♂	man rowing boat: light skin tone
-🚣🏼‍♂️	man rowing boat: medium-light skin tone
-🚣🏼‍♂	man rowing boat: medium-light skin tone
-🚣🏽‍♂️	man rowing boat: medium skin tone
-🚣🏽‍♂	man rowing boat: medium skin tone
-🚣🏾‍♂️	man rowing boat: medium-dark skin tone
-🚣🏾‍♂	man rowing boat: medium-dark skin tone
-🚣🏿‍♂️	man rowing boat: dark skin tone
-🚣🏿‍♂	man rowing boat: dark skin tone
-🚣‍♀️	woman rowing boat
-🚣‍♀	woman rowing boat
-🚣🏻‍♀️	woman rowing boat: light skin tone
-🚣🏻‍♀	woman rowing boat: light skin tone
-🚣🏼‍♀️	woman rowing boat: medium-light skin tone
-🚣🏼‍♀	woman rowing boat: medium-light skin tone
-🚣🏽‍♀️	woman rowing boat: medium skin tone
-🚣🏽‍♀	woman rowing boat: medium skin tone
-🚣🏾‍♀️	woman rowing boat: medium-dark skin tone
-🚣🏾‍♀	woman rowing boat: medium-dark skin tone
-🚣🏿‍♀️	woman rowing boat: dark skin tone
-🚣🏿‍♀	woman rowing boat: dark skin tone
-🏊	person swimming
-🏊🏻	person swimming: light skin tone
-🏊🏼	person swimming: medium-light skin tone
-🏊🏽	person swimming: medium skin tone
-🏊🏾	person swimming: medium-dark skin tone
-🏊🏿	person swimming: dark skin tone
-🏊‍♂️	man swimming
-🏊‍♂	man swimming
-🏊🏻‍♂️	man swimming: light skin tone
-🏊🏻‍♂	man swimming: light skin tone
-🏊🏼‍♂️	man swimming: medium-light skin tone
-🏊🏼‍♂	man swimming: medium-light skin tone
-🏊🏽‍♂️	man swimming: medium skin tone
-🏊🏽‍♂	man swimming: medium skin tone
-🏊🏾‍♂️	man swimming: medium-dark skin tone
-🏊🏾‍♂	man swimming: medium-dark skin tone
-🏊🏿‍♂️	man swimming: dark skin tone
-🏊🏿‍♂	man swimming: dark skin tone
-🏊‍♀️	woman swimming
-🏊‍♀	woman swimming
-🏊🏻‍♀️	woman swimming: light skin tone
-🏊🏻‍♀	woman swimming: light skin tone
-🏊🏼‍♀️	woman swimming: medium-light skin tone
-🏊🏼‍♀	woman swimming: medium-light skin tone
-🏊🏽‍♀️	woman swimming: medium skin tone
-🏊🏽‍♀	woman swimming: medium skin tone
-🏊🏾‍♀️	woman swimming: medium-dark skin tone
-🏊🏾‍♀	woman swimming: medium-dark skin tone
-🏊🏿‍♀️	woman swimming: dark skin tone
-🏊🏿‍♀	woman swimming: dark skin tone
-⛹️	person bouncing ball
-⛹	person bouncing ball
-⛹🏻	person bouncing ball: light skin tone
-⛹🏼	person bouncing ball: medium-light skin tone
-⛹🏽	person bouncing ball: medium skin tone
-⛹🏾	person bouncing ball: medium-dark skin tone
-⛹🏿	person bouncing ball: dark skin tone
-⛹️‍♂️	man bouncing ball
-⛹‍♂️	man bouncing ball
-⛹️‍♂	man bouncing ball
-⛹‍♂	man bouncing ball
-⛹🏻‍♂️	man bouncing ball: light skin tone
-⛹🏻‍♂	man bouncing ball: light skin tone
-⛹🏼‍♂️	man bouncing ball: medium-light skin tone
-⛹🏼‍♂	man bouncing ball: medium-light skin tone
-⛹🏽‍♂️	man bouncing ball: medium skin tone
-⛹🏽‍♂	man bouncing ball: medium skin tone
-⛹🏾‍♂️	man bouncing ball: medium-dark skin tone
-⛹🏾‍♂	man bouncing ball: medium-dark skin tone
-⛹🏿‍♂️	man bouncing ball: dark skin tone
-⛹🏿‍♂	man bouncing ball: dark skin tone
-⛹️‍♀️	woman bouncing ball
-⛹‍♀️	woman bouncing ball
-⛹️‍♀	woman bouncing ball
-⛹‍♀	woman bouncing ball
-⛹🏻‍♀️	woman bouncing ball: light skin tone
-⛹🏻‍♀	woman bouncing ball: light skin tone
-⛹🏼‍♀️	woman bouncing ball: medium-light skin tone
-⛹🏼‍♀	woman bouncing ball: medium-light skin tone
-⛹🏽‍♀️	woman bouncing ball: medium skin tone
-⛹🏽‍♀	woman bouncing ball: medium skin tone
-⛹🏾‍♀️	woman bouncing ball: medium-dark skin tone
-⛹🏾‍♀	woman bouncing ball: medium-dark skin tone
-⛹🏿‍♀️	woman bouncing ball: dark skin tone
-⛹🏿‍♀	woman bouncing ball: dark skin tone
-🏋️	person lifting weights
-🏋	person lifting weights
-🏋🏻	person lifting weights: light skin tone
-🏋🏼	person lifting weights: medium-light skin tone
-🏋🏽	person lifting weights: medium skin tone
-🏋🏾	person lifting weights: medium-dark skin tone
-🏋🏿	person lifting weights: dark skin tone
-🏋️‍♂️	man lifting weights
-🏋‍♂️	man lifting weights
-🏋️‍♂	man lifting weights
-🏋‍♂	man lifting weights
-🏋🏻‍♂️	man lifting weights: light skin tone
-🏋🏻‍♂	man lifting weights: light skin tone
-🏋🏼‍♂️	man lifting weights: medium-light skin tone
-🏋🏼‍♂	man lifting weights: medium-light skin tone
-🏋🏽‍♂️	man lifting weights: medium skin tone
-🏋🏽‍♂	man lifting weights: medium skin tone
-🏋🏾‍♂️	man lifting weights: medium-dark skin tone
-🏋🏾‍♂	man lifting weights: medium-dark skin tone
-🏋🏿‍♂️	man lifting weights: dark skin tone
-🏋🏿‍♂	man lifting weights: dark skin tone
-🏋️‍♀️	woman lifting weights
-🏋‍♀️	woman lifting weights
-🏋️‍♀	woman lifting weights
-🏋‍♀	woman lifting weights
-🏋🏻‍♀️	woman lifting weights: light skin tone
-🏋🏻‍♀	woman lifting weights: light skin tone
-🏋🏼‍♀️	woman lifting weights: medium-light skin tone
-🏋🏼‍♀	woman lifting weights: medium-light skin tone
-🏋🏽‍♀️	woman lifting weights: medium skin tone
-🏋🏽‍♀	woman lifting weights: medium skin tone
-🏋🏾‍♀️	woman lifting weights: medium-dark skin tone
-🏋🏾‍♀	woman lifting weights: medium-dark skin tone
-🏋🏿‍♀️	woman lifting weights: dark skin tone
-🏋🏿‍♀	woman lifting weights: dark skin tone
-🚴	person biking
-🚴🏻	person biking: light skin tone
-🚴🏼	person biking: medium-light skin tone
-🚴🏽	person biking: medium skin tone
-🚴🏾	person biking: medium-dark skin tone
-🚴🏿	person biking: dark skin tone
-🚴‍♂️	man biking
-🚴‍♂	man biking
-🚴🏻‍♂️	man biking: light skin tone
-🚴🏻‍♂	man biking: light skin tone
-🚴🏼‍♂️	man biking: medium-light skin tone
-🚴🏼‍♂	man biking: medium-light skin tone
-🚴🏽‍♂️	man biking: medium skin tone
-🚴🏽‍♂	man biking: medium skin tone
-🚴🏾‍♂️	man biking: medium-dark skin tone
-🚴🏾‍♂	man biking: medium-dark skin tone
-🚴🏿‍♂️	man biking: dark skin tone
-🚴🏿‍♂	man biking: dark skin tone
-🚴‍♀️	woman biking
-🚴‍♀	woman biking
-🚴🏻‍♀️	woman biking: light skin tone
-🚴🏻‍♀	woman biking: light skin tone
-🚴🏼‍♀️	woman biking: medium-light skin tone
-🚴🏼‍♀	woman biking: medium-light skin tone
-🚴🏽‍♀️	woman biking: medium skin tone
-🚴🏽‍♀	woman biking: medium skin tone
-🚴🏾‍♀️	woman biking: medium-dark skin tone
-🚴🏾‍♀	woman biking: medium-dark skin tone
-🚴🏿‍♀️	woman biking: dark skin tone
-🚴🏿‍♀	woman biking: dark skin tone
-🚵	person mountain biking
-🚵🏻	person mountain biking: light skin tone
-🚵🏼	person mountain biking: medium-light skin tone
-🚵🏽	person mountain biking: medium skin tone
-🚵🏾	person mountain biking: medium-dark skin tone
-🚵🏿	person mountain biking: dark skin tone
-🚵‍♂️	man mountain biking
-🚵‍♂	man mountain biking
-🚵🏻‍♂️	man mountain biking: light skin tone
-🚵🏻‍♂	man mountain biking: light skin tone
-🚵🏼‍♂️	man mountain biking: medium-light skin tone
-🚵🏼‍♂	man mountain biking: medium-light skin tone
-🚵🏽‍♂️	man mountain biking: medium skin tone
-🚵🏽‍♂	man mountain biking: medium skin tone
-🚵🏾‍♂️	man mountain biking: medium-dark skin tone
-🚵🏾‍♂	man mountain biking: medium-dark skin tone
-🚵🏿‍♂️	man mountain biking: dark skin tone
-🚵🏿‍♂	man mountain biking: dark skin tone
-🚵‍♀️	woman mountain biking
-🚵‍♀	woman mountain biking
-🚵🏻‍♀️	woman mountain biking: light skin tone
-🚵🏻‍♀	woman mountain biking: light skin tone
-🚵🏼‍♀️	woman mountain biking: medium-light skin tone
-🚵🏼‍♀	woman mountain biking: medium-light skin tone
-🚵🏽‍♀️	woman mountain biking: medium skin tone
-🚵🏽‍♀	woman mountain biking: medium skin tone
-🚵🏾‍♀️	woman mountain biking: medium-dark skin tone
-🚵🏾‍♀	woman mountain biking: medium-dark skin tone
-🚵🏿‍♀️	woman mountain biking: dark skin tone
-🚵🏿‍♀	woman mountain biking: dark skin tone
-🏎️	racing car
-🏎	racing car
-🏍️	motorcycle
-🏍	motorcycle
-🤸	person cartwheeling
-🤸🏻	person cartwheeling: light skin tone
-🤸🏼	person cartwheeling: medium-light skin tone
-🤸🏽	person cartwheeling: medium skin tone
-🤸🏾	person cartwheeling: medium-dark skin tone
-🤸🏿	person cartwheeling: dark skin tone
-🤸‍♂️	man cartwheeling
-🤸‍♂	man cartwheeling
-🤸🏻‍♂️	man cartwheeling: light skin tone
-🤸🏻‍♂	man cartwheeling: light skin tone
-🤸🏼‍♂️	man cartwheeling: medium-light skin tone
-🤸🏼‍♂	man cartwheeling: medium-light skin tone
-🤸🏽‍♂️	man cartwheeling: medium skin tone
-🤸🏽‍♂	man cartwheeling: medium skin tone
-🤸🏾‍♂️	man cartwheeling: medium-dark skin tone
-🤸🏾‍♂	man cartwheeling: medium-dark skin tone
-🤸🏿‍♂️	man cartwheeling: dark skin tone
-🤸🏿‍♂	man cartwheeling: dark skin tone
-🤸‍♀️	woman cartwheeling
-🤸‍♀	woman cartwheeling
-🤸🏻‍♀️	woman cartwheeling: light skin tone
-🤸🏻‍♀	woman cartwheeling: light skin tone
-🤸🏼‍♀️	woman cartwheeling: medium-light skin tone
-🤸🏼‍♀	woman cartwheeling: medium-light skin tone
-🤸🏽‍♀️	woman cartwheeling: medium skin tone
-🤸🏽‍♀	woman cartwheeling: medium skin tone
-🤸🏾‍♀️	woman cartwheeling: medium-dark skin tone
-🤸🏾‍♀	woman cartwheeling: medium-dark skin tone
-🤸🏿‍♀️	woman cartwheeling: dark skin tone
-🤸🏿‍♀	woman cartwheeling: dark skin tone
-🤼	people wrestling
-🤼‍♂️	men wrestling
-🤼‍♂	men wrestling
-🤼‍♀️	women wrestling
-🤼‍♀	women wrestling
-🤽	person playing water polo
-🤽🏻	person playing water polo: light skin tone
-🤽🏼	person playing water polo: medium-light skin tone
-🤽🏽	person playing water polo: medium skin tone
-🤽🏾	person playing water polo: medium-dark skin tone
-🤽🏿	person playing water polo: dark skin tone
-🤽‍♂️	man playing water polo
-🤽‍♂	man playing water polo
-🤽🏻‍♂️	man playing water polo: light skin tone
-🤽🏻‍♂	man playing water polo: light skin tone
-🤽🏼‍♂️	man playing water polo: medium-light skin tone
-🤽🏼‍♂	man playing water polo: medium-light skin tone
-🤽🏽‍♂️	man playing water polo: medium skin tone
-🤽🏽‍♂	man playing water polo: medium skin tone
-🤽🏾‍♂️	man playing water polo: medium-dark skin tone
-🤽🏾‍♂	man playing water polo: medium-dark skin tone
-🤽🏿‍♂️	man playing water polo: dark skin tone
-🤽🏿‍♂	man playing water polo: dark skin tone
-🤽‍♀️	woman playing water polo
-🤽‍♀	woman playing water polo
-🤽🏻‍♀️	woman playing water polo: light skin tone
-🤽🏻‍♀	woman playing water polo: light skin tone
-🤽🏼‍♀️	woman playing water polo: medium-light skin tone
-🤽🏼‍♀	woman playing water polo: medium-light skin tone
-🤽🏽‍♀️	woman playing water polo: medium skin tone
-🤽🏽‍♀	woman playing water polo: medium skin tone
-🤽🏾‍♀️	woman playing water polo: medium-dark skin tone
-🤽🏾‍♀	woman playing water polo: medium-dark skin tone
-🤽🏿‍♀️	woman playing water polo: dark skin tone
-🤽🏿‍♀	woman playing water polo: dark skin tone
-🤾	person playing handball
-🤾🏻	person playing handball: light skin tone
-🤾🏼	person playing handball: medium-light skin tone
-🤾🏽	person playing handball: medium skin tone
-🤾🏾	person playing handball: medium-dark skin tone
-🤾🏿	person playing handball: dark skin tone
-🤾‍♂️	man playing handball
-🤾‍♂	man playing handball
-🤾🏻‍♂️	man playing handball: light skin tone
-🤾🏻‍♂	man playing handball: light skin tone
-🤾🏼‍♂️	man playing handball: medium-light skin tone
-🤾🏼‍♂	man playing handball: medium-light skin tone
-🤾🏽‍♂️	man playing handball: medium skin tone
-🤾🏽‍♂	man playing handball: medium skin tone
-🤾🏾‍♂️	man playing handball: medium-dark skin tone
-🤾🏾‍♂	man playing handball: medium-dark skin tone
-🤾🏿‍♂️	man playing handball: dark skin tone
-🤾🏿‍♂	man playing handball: dark skin tone
-🤾‍♀️	woman playing handball
-🤾‍♀	woman playing handball
-🤾🏻‍♀️	woman playing handball: light skin tone
-🤾🏻‍♀	woman playing handball: light skin tone
-🤾🏼‍♀️	woman playing handball: medium-light skin tone
-🤾🏼‍♀	woman playing handball: medium-light skin tone
-🤾🏽‍♀️	woman playing handball: medium skin tone
-🤾🏽‍♀	woman playing handball: medium skin tone
-🤾🏾‍♀️	woman playing handball: medium-dark skin tone
-🤾🏾‍♀	woman playing handball: medium-dark skin tone
-🤾🏿‍♀️	woman playing handball: dark skin tone
-🤾🏿‍♀	woman playing handball: dark skin tone
-🤹	person juggling
-🤹🏻	person juggling: light skin tone
-🤹🏼	person juggling: medium-light skin tone
-🤹🏽	person juggling: medium skin tone
-🤹🏾	person juggling: medium-dark skin tone
-🤹🏿	person juggling: dark skin tone
-🤹‍♂️	man juggling
-🤹‍♂	man juggling
-🤹🏻‍♂️	man juggling: light skin tone
-🤹🏻‍♂	man juggling: light skin tone
-🤹🏼‍♂️	man juggling: medium-light skin tone
-🤹🏼‍♂	man juggling: medium-light skin tone
-🤹🏽‍♂️	man juggling: medium skin tone
-🤹🏽‍♂	man juggling: medium skin tone
-🤹🏾‍♂️	man juggling: medium-dark skin tone
-🤹🏾‍♂	man juggling: medium-dark skin tone
-🤹🏿‍♂️	man juggling: dark skin tone
-🤹🏿‍♂	man juggling: dark skin tone
-🤹‍♀️	woman juggling
-🤹‍♀	woman juggling
-🤹🏻‍♀️	woman juggling: light skin tone
-🤹🏻‍♀	woman juggling: light skin tone
-🤹🏼‍♀️	woman juggling: medium-light skin tone
-🤹🏼‍♀	woman juggling: medium-light skin tone
-🤹🏽‍♀️	woman juggling: medium skin tone
-🤹🏽‍♀	woman juggling: medium skin tone
-🤹🏾‍♀️	woman juggling: medium-dark skin tone
-🤹🏾‍♀	woman juggling: medium-dark skin tone
-🤹🏿‍♀️	woman juggling: dark skin tone
-🤹🏿‍♀	woman juggling: dark skin tone
-👫	man and woman holding hands
-👬	two men holding hands
-👭	two women holding hands
-💏	kiss
-👩‍❤️‍💋‍👨	kiss: woman, man
-👩‍❤‍💋‍👨	kiss: woman, man
-👨‍❤️‍💋‍👨	kiss: man, man
-👨‍❤‍💋‍👨	kiss: man, man
-👩‍❤️‍💋‍👩	kiss: woman, woman
-👩‍❤‍💋‍👩	kiss: woman, woman
-💑	couple with heart
-👩‍❤️‍👨	couple with heart: woman, man
-👩‍❤‍👨	couple with heart: woman, man
-👨‍❤️‍👨	couple with heart: man, man
-👨‍❤‍👨	couple with heart: man, man
-👩‍❤️‍👩	couple with heart: woman, woman
-👩‍❤‍👩	couple with heart: woman, woman
-👪	family
-👨‍👩‍👦	family: man, woman, boy
-👨‍👩‍👧	family: man, woman, girl
-👨‍👩‍👧‍👦	family: man, woman, girl, boy
-👨‍👩‍👦‍👦	family: man, woman, boy, boy
-👨‍👩‍👧‍👧	family: man, woman, girl, girl
-👨‍👨‍👦	family: man, man, boy
-👨‍👨‍👧	family: man, man, girl
-👨‍👨‍👧‍👦	family: man, man, girl, boy
-👨‍👨‍👦‍👦	family: man, man, boy, boy
-👨‍👨‍👧‍👧	family: man, man, girl, girl
-👩‍👩‍👦	family: woman, woman, boy
-👩‍👩‍👧	family: woman, woman, girl
-👩‍👩‍👧‍👦	family: woman, woman, girl, boy
-👩‍👩‍👦‍👦	family: woman, woman, boy, boy
-👩‍👩‍👧‍👧	family: woman, woman, girl, girl
-👨‍👦	family: man, boy
-👨‍👦‍👦	family: man, boy, boy
-👨‍👧	family: man, girl
-👨‍👧‍👦	family: man, girl, boy
-👨‍👧‍👧	family: man, girl, girl
-👩‍👦	family: woman, boy
-👩‍👦‍👦	family: woman, boy, boy
-👩‍👧	family: woman, girl
-👩‍👧‍👦	family: woman, girl, boy
-👩‍👧‍👧	family: woman, girl, girl
-🤳	selfie
-🤳🏻	selfie: light skin tone
-🤳🏼	selfie: medium-light skin tone
-🤳🏽	selfie: medium skin tone
-🤳🏾	selfie: medium-dark skin tone
-🤳🏿	selfie: dark skin tone
-💪	flexed biceps
-💪🏻	flexed biceps: light skin tone
-💪🏼	flexed biceps: medium-light skin tone
-💪🏽	flexed biceps: medium skin tone
-💪🏾	flexed biceps: medium-dark skin tone
-💪🏿	flexed biceps: dark skin tone
-🦵	leg
-🦵🏻	leg: light skin tone
-🦵🏼	leg: medium-light skin tone
-🦵🏽	leg: medium skin tone
-🦵🏾	leg: medium-dark skin tone
-🦵🏿	leg: dark skin tone
-🦶	foot
-🦶🏻	foot: light skin tone
-🦶🏼	foot: medium-light skin tone
-🦶🏽	foot: medium skin tone
-🦶🏾	foot: medium-dark skin tone
-🦶🏿	foot: dark skin tone
-👈	backhand index pointing left
-👈🏻	backhand index pointing left: light skin tone
-👈🏼	backhand index pointing left: medium-light skin tone
-👈🏽	backhand index pointing left: medium skin tone
-👈🏾	backhand index pointing left: medium-dark skin tone
-👈🏿	backhand index pointing left: dark skin tone
-👉	backhand index pointing right
-👉🏻	backhand index pointing right: light skin tone
-👉🏼	backhand index pointing right: medium-light skin tone
-👉🏽	backhand index pointing right: medium skin tone
-👉🏾	backhand index pointing right: medium-dark skin tone
-👉🏿	backhand index pointing right: dark skin tone
-☝️	index pointing up
-☝	index pointing up
-☝🏻	index pointing up: light skin tone
-☝🏼	index pointing up: medium-light skin tone
-☝🏽	index pointing up: medium skin tone
-☝🏾	index pointing up: medium-dark skin tone
-☝🏿	index pointing up: dark skin tone
-👆	backhand index pointing up
-👆🏻	backhand index pointing up: light skin tone
-👆🏼	backhand index pointing up: medium-light skin tone
-👆🏽	backhand index pointing up: medium skin tone
-👆🏾	backhand index pointing up: medium-dark skin tone
-👆🏿	backhand index pointing up: dark skin tone
-🖕	middle finger
-🖕🏻	middle finger: light skin tone
-🖕🏼	middle finger: medium-light skin tone
-🖕🏽	middle finger: medium skin tone
-🖕🏾	middle finger: medium-dark skin tone
-🖕🏿	middle finger: dark skin tone
-👇	backhand index pointing down
-👇🏻	backhand index pointing down: light skin tone
-👇🏼	backhand index pointing down: medium-light skin tone
-👇🏽	backhand index pointing down: medium skin tone
-👇🏾	backhand index pointing down: medium-dark skin tone
-👇🏿	backhand index pointing down: dark skin tone
-✌️	victory hand
-✌	victory hand
-✌🏻	victory hand: light skin tone
-✌🏼	victory hand: medium-light skin tone
-✌🏽	victory hand: medium skin tone
-✌🏾	victory hand: medium-dark skin tone
-✌🏿	victory hand: dark skin tone
-🤞	crossed fingers
-🤞🏻	crossed fingers: light skin tone
-🤞🏼	crossed fingers: medium-light skin tone
-🤞🏽	crossed fingers: medium skin tone
-🤞🏾	crossed fingers: medium-dark skin tone
-🤞🏿	crossed fingers: dark skin tone
-🖖	vulcan salute
-🖖🏻	vulcan salute: light skin tone
-🖖🏼	vulcan salute: medium-light skin tone
-🖖🏽	vulcan salute: medium skin tone
-🖖🏾	vulcan salute: medium-dark skin tone
-🖖🏿	vulcan salute: dark skin tone
-🤘	sign of the horns
-🤘🏻	sign of the horns: light skin tone
-🤘🏼	sign of the horns: medium-light skin tone
-🤘🏽	sign of the horns: medium skin tone
-🤘🏾	sign of the horns: medium-dark skin tone
-🤘🏿	sign of the horns: dark skin tone
-🤙	call me hand
-🤙🏻	call me hand: light skin tone
-🤙🏼	call me hand: medium-light skin tone
-🤙🏽	call me hand: medium skin tone
-🤙🏾	call me hand: medium-dark skin tone
-🤙🏿	call me hand: dark skin tone
-🖐️	hand with fingers splayed
-🖐	hand with fingers splayed
-🖐🏻	hand with fingers splayed: light skin tone
-🖐🏼	hand with fingers splayed: medium-light skin tone
-🖐🏽	hand with fingers splayed: medium skin tone
-🖐🏾	hand with fingers splayed: medium-dark skin tone
-🖐🏿	hand with fingers splayed: dark skin tone
-✋	raised hand
-✋🏻	raised hand: light skin tone
-✋🏼	raised hand: medium-light skin tone
-✋🏽	raised hand: medium skin tone
-✋🏾	raised hand: medium-dark skin tone
-✋🏿	raised hand: dark skin tone
-👌	OK hand
-👌🏻	OK hand: light skin tone
-👌🏼	OK hand: medium-light skin tone
-👌🏽	OK hand: medium skin tone
-👌🏾	OK hand: medium-dark skin tone
-👌🏿	OK hand: dark skin tone
-👍	thumbs up
-👍🏻	thumbs up: light skin tone
-👍🏼	thumbs up: medium-light skin tone
-👍🏽	thumbs up: medium skin tone
-👍🏾	thumbs up: medium-dark skin tone
-👍🏿	thumbs up: dark skin tone
-👎	thumbs down
-👎🏻	thumbs down: light skin tone
-👎🏼	thumbs down: medium-light skin tone
-👎🏽	thumbs down: medium skin tone
-👎🏾	thumbs down: medium-dark skin tone
-👎🏿	thumbs down: dark skin tone
-✊	raised fist
-✊🏻	raised fist: light skin tone
-✊🏼	raised fist: medium-light skin tone
-✊🏽	raised fist: medium skin tone
-✊🏾	raised fist: medium-dark skin tone
-✊🏿	raised fist: dark skin tone
-👊	oncoming fist
-👊🏻	oncoming fist: light skin tone
-👊🏼	oncoming fist: medium-light skin tone
-👊🏽	oncoming fist: medium skin tone
-👊🏾	oncoming fist: medium-dark skin tone
-👊🏿	oncoming fist: dark skin tone
-🤛	left-facing fist
-🤛🏻	left-facing fist: light skin tone
-🤛🏼	left-facing fist: medium-light skin tone
-🤛🏽	left-facing fist: medium skin tone
-🤛🏾	left-facing fist: medium-dark skin tone
-🤛🏿	left-facing fist: dark skin tone
-🤜	right-facing fist
-🤜🏻	right-facing fist: light skin tone
-🤜🏼	right-facing fist: medium-light skin tone
-🤜🏽	right-facing fist: medium skin tone
-🤜🏾	right-facing fist: medium-dark skin tone
-🤜🏿	right-facing fist: dark skin tone
-🤚	raised back of hand
-🤚🏻	raised back of hand: light skin tone
-🤚🏼	raised back of hand: medium-light skin tone
-🤚🏽	raised back of hand: medium skin tone
-🤚🏾	raised back of hand: medium-dark skin tone
-🤚🏿	raised back of hand: dark skin tone
-👋	waving hand
-👋🏻	waving hand: light skin tone
-👋🏼	waving hand: medium-light skin tone
-👋🏽	waving hand: medium skin tone
-👋🏾	waving hand: medium-dark skin tone
-👋🏿	waving hand: dark skin tone
-🤟	love-you gesture
-🤟🏻	love-you gesture: light skin tone
-🤟🏼	love-you gesture: medium-light skin tone
-🤟🏽	love-you gesture: medium skin tone
-🤟🏾	love-you gesture: medium-dark skin tone
-🤟🏿	love-you gesture: dark skin tone
-✍️	writing hand
-✍	writing hand
-✍🏻	writing hand: light skin tone
-✍🏼	writing hand: medium-light skin tone
-✍🏽	writing hand: medium skin tone
-✍🏾	writing hand: medium-dark skin tone
-✍🏿	writing hand: dark skin tone
-👏	clapping hands
-👏🏻	clapping hands: light skin tone
-👏🏼	clapping hands: medium-light skin tone
-👏🏽	clapping hands: medium skin tone
-👏🏾	clapping hands: medium-dark skin tone
-👏🏿	clapping hands: dark skin tone
-👐	open hands
-👐🏻	open hands: light skin tone
-👐🏼	open hands: medium-light skin tone
-👐🏽	open hands: medium skin tone
-👐🏾	open hands: medium-dark skin tone
-👐🏿	open hands: dark skin tone
-🙌	raising hands
-🙌🏻	raising hands: light skin tone
-🙌🏼	raising hands: medium-light skin tone
-🙌🏽	raising hands: medium skin tone
-🙌🏾	raising hands: medium-dark skin tone
-🙌🏿	raising hands: dark skin tone
-🤲	palms up together
-🤲🏻	palms up together: light skin tone
-🤲🏼	palms up together: medium-light skin tone
-🤲🏽	palms up together: medium skin tone
-🤲🏾	palms up together: medium-dark skin tone
-🤲🏿	palms up together: dark skin tone
-🙏	folded hands
-🙏🏻	folded hands: light skin tone
-🙏🏼	folded hands: medium-light skin tone
-🙏🏽	folded hands: medium skin tone
-🙏🏾	folded hands: medium-dark skin tone
-🙏🏿	folded hands: dark skin tone
-🤝	handshake
-💅	nail polish
-💅🏻	nail polish: light skin tone
-💅🏼	nail polish: medium-light skin tone
-💅🏽	nail polish: medium skin tone
-💅🏾	nail polish: medium-dark skin tone
-💅🏿	nail polish: dark skin tone
-👂	ear
-👂🏻	ear: light skin tone
-👂🏼	ear: medium-light skin tone
-👂🏽	ear: medium skin tone
-👂🏾	ear: medium-dark skin tone
-👂🏿	ear: dark skin tone
-👃	nose
-👃🏻	nose: light skin tone
-👃🏼	nose: medium-light skin tone
-👃🏽	nose: medium skin tone
-👃🏾	nose: medium-dark skin tone
-👃🏿	nose: dark skin tone
-🦰	red-haired
-🦱	curly-haired
-🦲	bald
-🦳	white-haired
-👣	footprints
-👀	eyes
-👁️	eye
-👁	eye
-👁️‍🗨️	eye in speech bubble
-👁‍🗨️	eye in speech bubble
-👁️‍🗨	eye in speech bubble
-👁‍🗨	eye in speech bubble
-🧠	brain
-🦴	bone
-🦷	tooth
-👅	tongue
-👄	mouth
-💋	kiss mark
-💘	heart with arrow
-❤️	red heart
-❤	red heart
-💓	beating heart
-💔	broken heart
-💕	two hearts
-💖	sparkling heart
-💗	growing heart
-💙	blue heart
-💚	green heart
-💛	yellow heart
-🧡	orange heart
-💜	purple heart
-🖤	black heart
-💝	heart with ribbon
-💞	revolving hearts
-💟	heart decoration
-❣️	heavy heart exclamation
-❣	heavy heart exclamation
-💌	love letter
-💤	zzz
-💢	anger symbol
-💣	bomb
-💥	collision
-💦	sweat droplets
-💨	dashing away
-💫	dizzy
-💬	speech balloon
-🗨️	left speech bubble
-🗨	left speech bubble
-🗯️	right anger bubble
-🗯	right anger bubble
-💭	thought balloon
-🕳️	hole
-🕳	hole
-👓	glasses
-🕶️	sunglasses
-🕶	sunglasses
-🥽	goggles
-🥼	lab coat
-👔	necktie
-👕	t-shirt
-👖	jeans
-🧣	scarf
-🧤	gloves
-🧥	coat
-🧦	socks
-👗	dress
-👘	kimono
-👙	bikini
-👚	woman’s clothes
-👛	purse
-👜	handbag
-👝	clutch bag
-🛍️	shopping bags
-🛍	shopping bags
-🎒	school backpack
-👞	man’s shoe
-👟	running shoe
-🥾	hiking boot
-🥿	woman’s flat shoe
-👠	high-heeled shoe
-👡	woman’s sandal
-👢	woman’s boot
-👑	crown
-👒	woman’s hat
-🎩	top hat
-🎓	graduation cap
-🧢	billed cap
-⛑️	rescue worker’s helmet
-⛑	rescue worker’s helmet
-📿	prayer beads
-💄	lipstick
-💍	ring
-💎	gem stone
-🐵	monkey face
-🐒	monkey
-🦍	gorilla
-🐶	dog face
-🐕	dog
-🐩	poodle
-🐺	wolf face
-🦊	fox face
-🦝	raccoon
-🐱	cat face
-🐈	cat
-🦁	lion face
-🐯	tiger face
-🐅	tiger
-🐆	leopard
-🐴	horse face
-🐎	horse
-🦄	unicorn face
-🦓	zebra
-🦌	deer
-🐮	cow face
-🐂	ox
-🐃	water buffalo
-🐄	cow
-🐷	pig face
-🐖	pig
-🐗	boar
-🐽	pig nose
-🐏	ram
-🐑	ewe
-🐐	goat
-🐪	camel
-🐫	two-hump camel
-🦙	llama
-🦒	giraffe
-🐘	elephant
-🦏	rhinoceros
-🦛	hippopotamus
-🐭	mouse face
-🐁	mouse
-🐀	rat
-🐹	hamster face
-🐰	rabbit face
-🐇	rabbit
-🐿️	chipmunk
-🐿	chipmunk
-🦔	hedgehog
-🦇	bat
-🐻	bear face
-🐨	koala
-🐼	panda face
-🦘	kangaroo
-🦡	badger
-🐾	paw prints
-🦃	turkey
-🐔	chicken
-🐓	rooster
-🐣	hatching chick
-🐤	baby chick
-🐥	front-facing baby chick
-🐦	bird
-🐧	penguin
-🕊️	dove
-🕊	dove
-🦅	eagle
-🦆	duck
-🦢	swan
-🦉	owl
-🦚	peacock
-🦜	parrot
-🐸	frog face
-🐊	crocodile
-🐢	turtle
-🦎	lizard
-🐍	snake
-🐲	dragon face
-🐉	dragon
-🦕	sauropod
-🦖	T-Rex
-🐳	spouting whale
-🐋	whale
-🐬	dolphin
-🐟	fish
-🐠	tropical fish
-🐡	blowfish
-🦈	shark
-🐙	octopus
-🐚	spiral shell
-🦀	crab
-🦞	lobster
-🦐	shrimp
-🦑	squid
-🐌	snail
-🦋	butterfly
-🐛	bug
-🐜	ant
-🐝	honeybee
-🐞	lady beetle
-🦗	cricket
-🕷️	spider
-🕷	spider
-🕸️	spider web
-🕸	spider web
-🦂	scorpion
-🦟	mosquito
-🦠	microbe
-💐	bouquet
-🌸	cherry blossom
-💮	white flower
-🏵️	rosette
-🏵	rosette
-🌹	rose
-🥀	wilted flower
-🌺	hibiscus
-🌻	sunflower
-🌼	blossom
-🌷	tulip
-🌱	seedling
-🌲	evergreen tree
-🌳	deciduous tree
-🌴	palm tree
-🌵	cactus
-🌾	sheaf of rice
-🌿	herb
-☘️	shamrock
-☘	shamrock
-🍀	four leaf clover
-🍁	maple leaf
-🍂	fallen leaf
-🍃	leaf fluttering in wind
-🍇	grapes
-🍈	melon
-🍉	watermelon
-🍊	tangerine
-🍋	lemon
-🍌	banana
-🍍	pineapple
-🥭	mango
-🍎	red apple
-🍏	green apple
-🍐	pear
-🍑	peach
-🍒	cherries
-🍓	strawberry
-🥝	kiwi fruit
-🍅	tomato
-🥥	coconut
-🥑	avocado
-🍆	eggplant
-🥔	potato
-🥕	carrot
-🌽	ear of corn
-🌶️	hot pepper
-🌶	hot pepper
-🥒	cucumber
-🥬	leafy green
-🥦	broccoli
-🍄	mushroom
-🥜	peanuts
-🌰	chestnut
-🍞	bread
-🥐	croissant
-🥖	baguette bread
-🥨	pretzel
-🥯	bagel
-🥞	pancakes
-🧀	cheese wedge
-🍖	meat on bone
-🍗	poultry leg
-🥩	cut of meat
-🥓	bacon
-🍔	hamburger
-🍟	french fries
-🍕	pizza
-🌭	hot dog
-🥪	sandwich
-🌮	taco
-🌯	burrito
-🥙	stuffed flatbread
-🥚	egg
-🍳	cooking
-🥘	shallow pan of food
-🍲	pot of food
-🥣	bowl with spoon
-🥗	green salad
-🍿	popcorn
-🧂	salt
-🥫	canned food
-🍱	bento box
-🍘	rice cracker
-🍙	rice ball
-🍚	cooked rice
-🍛	curry rice
-🍜	steaming bowl
-🍝	spaghetti
-🍠	roasted sweet potato
-🍢	oden
-🍣	sushi
-🍤	fried shrimp
-🍥	fish cake with swirl
-🥮	moon cake
-🍡	dango
-🥟	dumpling
-🥠	fortune cookie
-🥡	takeout box
-🍦	soft ice cream
-🍧	shaved ice
-🍨	ice cream
-🍩	doughnut
-🍪	cookie
-🎂	birthday cake
-🍰	shortcake
-🧁	cupcake
-🥧	pie
-🍫	chocolate bar
-🍬	candy
-🍭	lollipop
-🍮	custard
-🍯	honey pot
-🍼	baby bottle
-🥛	glass of milk
-☕	hot beverage
-🍵	teacup without handle
-🍶	sake
-🍾	bottle with popping cork
-🍷	wine glass
-🍸	cocktail glass
-🍹	tropical drink
-🍺	beer mug
-🍻	clinking beer mugs
-🥂	clinking glasses
-🥃	tumbler glass
-🥤	cup with straw
-🥢	chopsticks
-🍽️	fork and knife with plate
-🍽	fork and knife with plate
-🍴	fork and knife
-🥄	spoon
-🔪	kitchen knife
-🏺	amphora
-🌍	globe showing Europe-Africa
-🌎	globe showing Americas
-🌏	globe showing Asia-Australia
-🌐	globe with meridians
-🗺️	world map
-🗺	world map
-🗾	map of Japan
-🧭	compass
-🏔️	snow-capped mountain
-🏔	snow-capped mountain
-⛰️	mountain
-⛰	mountain
-🌋	volcano
-🗻	mount fuji
-🏕️	camping
-🏕	camping
-🏖️	beach with umbrella
-🏖	beach with umbrella
-🏜️	desert
-🏜	desert
-🏝️	desert island
-🏝	desert island
-🏞️	national park
-🏞	national park
-🏟️	stadium
-🏟	stadium
-🏛️	classical building
-🏛	classical building
-🏗️	building construction
-🏗	building construction
-🧱	bricks
-🏘️	houses
-🏘	houses
-🏚️	derelict house
-🏚	derelict house
-🏠	house
-🏡	house with garden
-🏢	office building
-🏣	Japanese post office
-🏤	post office
-🏥	hospital
-🏦	bank
-🏨	hotel
-🏩	love hotel
-🏪	convenience store
-🏫	school
-🏬	department store
-🏭	factory
-🏯	Japanese castle
-🏰	castle
-💒	wedding
-🗼	Tokyo tower
-🗽	Statue of Liberty
-⛪	church
-🕌	mosque
-🕍	synagogue
-⛩️	shinto shrine
-⛩	shinto shrine
-🕋	kaaba
-⛲	fountain
-⛺	tent
-🌁	foggy
-🌃	night with stars
-🏙️	cityscape
-🏙	cityscape
-🌄	sunrise over mountains
-🌅	sunrise
-🌆	cityscape at dusk
-🌇	sunset
-🌉	bridge at night
-♨️	hot springs
-♨	hot springs
-🌌	milky way
-🎠	carousel horse
-🎡	ferris wheel
-🎢	roller coaster
-💈	barber pole
-🎪	circus tent
-🚂	locomotive
-🚃	railway car
-🚄	high-speed train
-🚅	bullet train
-🚆	train
-🚇	metro
-🚈	light rail
-🚉	station
-🚊	tram
-🚝	monorail
-🚞	mountain railway
-🚋	tram car
-🚌	bus
-🚍	oncoming bus
-🚎	trolleybus
-🚐	minibus
-🚑	ambulance
-🚒	fire engine
-🚓	police car
-🚔	oncoming police car
-🚕	taxi
-🚖	oncoming taxi
-🚗	automobile
-🚘	oncoming automobile
-🚙	sport utility vehicle
-🚚	delivery truck
-🚛	articulated lorry
-🚜	tractor
-🚲	bicycle
-🛴	kick scooter
-🛹	skateboard
-🛵	motor scooter
-🚏	bus stop
-🛣️	motorway
-🛣	motorway
-🛤️	railway track
-🛤	railway track
-🛢️	oil drum
-🛢	oil drum
-⛽	fuel pump
-🚨	police car light
-🚥	horizontal traffic light
-🚦	vertical traffic light
-🛑	stop sign
-🚧	construction
-⚓	anchor
-⛵	sailboat
-🛶	canoe
-🚤	speedboat
-🛳️	passenger ship
-🛳	passenger ship
-⛴️	ferry
-⛴	ferry
-🛥️	motor boat
-🛥	motor boat
-🚢	ship
-✈️	airplane
-✈	airplane
-🛩️	small airplane
-🛩	small airplane
-🛫	airplane departure
-🛬	airplane arrival
-💺	seat
-🚁	helicopter
-🚟	suspension railway
-🚠	mountain cableway
-🚡	aerial tramway
-🛰️	satellite
-🛰	satellite
-🚀	rocket
-🛸	flying saucer
-🛎️	bellhop bell
-🛎	bellhop bell
-🧳	luggage
-⌛	hourglass done
-⏳	hourglass not done
-⌚	watch
-⏰	alarm clock
-⏱️	stopwatch
-⏱	stopwatch
-⏲️	timer clock
-⏲	timer clock
-🕰️	mantelpiece clock
-🕰	mantelpiece clock
-🕛	twelve o’clock
-🕧	twelve-thirty
-🕐	one o’clock
-🕜	one-thirty
-🕑	two o’clock
-🕝	two-thirty
-🕒	three o’clock
-🕞	three-thirty
-🕓	four o’clock
-🕟	four-thirty
-🕔	five o’clock
-🕠	five-thirty
-🕕	six o’clock
-🕡	six-thirty
-🕖	seven o’clock
-🕢	seven-thirty
-🕗	eight o’clock
-🕣	eight-thirty
-🕘	nine o’clock
-🕤	nine-thirty
-🕙	ten o’clock
-🕥	ten-thirty
-🕚	eleven o’clock
-🕦	eleven-thirty
-🌑	new moon
-🌒	waxing crescent moon
-🌓	first quarter moon
-🌔	waxing gibbous moon
-🌕	full moon
-🌖	waning gibbous moon
-🌗	last quarter moon
-🌘	waning crescent moon
-🌙	crescent moon
-🌚	new moon face
-🌛	first quarter moon face
-🌜	last quarter moon face
-🌡️	thermometer
-🌡	thermometer
-☀️	sun
-☀	sun
-🌝	full moon face
-🌞	sun with face
-⭐	star
-🌟	glowing star
-🌠	shooting star
-☁️	cloud
-☁	cloud
-⛅	sun behind cloud
-⛈️	cloud with lightning and rain
-⛈	cloud with lightning and rain
-🌤️	sun behind small cloud
-🌤	sun behind small cloud
-🌥️	sun behind large cloud
-🌥	sun behind large cloud
-🌦️	sun behind rain cloud
-🌦	sun behind rain cloud
-🌧️	cloud with rain
-🌧	cloud with rain
-🌨️	cloud with snow
-🌨	cloud with snow
-🌩️	cloud with lightning
-🌩	cloud with lightning
-🌪️	tornado
-🌪	tornado
-🌫️	fog
-🌫	fog
-🌬️	wind face
-🌬	wind face
-🌀	cyclone
-🌈	rainbow
-🌂	closed umbrella
-☂️	umbrella
-☂	umbrella
-☔	umbrella with rain drops
-⛱️	umbrella on ground
-⛱	umbrella on ground
-⚡	high voltage
-❄️	snowflake
-❄	snowflake
-☃️	snowman
-☃	snowman
-⛄	snowman without snow
-☄️	comet
-☄	comet
-🔥	fire
-💧	droplet
-🌊	water wave
-🎃	jack-o-lantern
-🎄	Christmas tree
-🎆	fireworks
-🎇	sparkler
-🧨	firecracker
-✨	sparkles
-🎈	balloon
-🎉	party popper
-🎊	confetti ball
-🎋	tanabata tree
-🎍	pine decoration
-🎎	Japanese dolls
-🎏	carp streamer
-🎐	wind chime
-🎑	moon viewing ceremony
-🧧	red envelope
-🎀	ribbon
-🎁	wrapped gift
-🎗️	reminder ribbon
-🎗	reminder ribbon
-🎟️	admission tickets
-🎟	admission tickets
-🎫	ticket
-🎖️	military medal
-🎖	military medal
-🏆	trophy
-🏅	sports medal
-🥇	1st place medal
-🥈	2nd place medal
-🥉	3rd place medal
-⚽	soccer ball
-⚾	baseball
-🥎	softball
-🏀	basketball
-🏐	volleyball
-🏈	american football
-🏉	rugby football
-🎾	tennis
-🥏	flying disc
-🎳	bowling
-🏏	cricket game
-🏑	field hockey
-🏒	ice hockey
-🥍	lacrosse
-🏓	ping pong
-🏸	badminton
-🥊	boxing glove
-🥋	martial arts uniform
-🥅	goal net
-⛳	flag in hole
-⛸️	ice skate
-⛸	ice skate
-🎣	fishing pole
-🎽	running shirt
-🎿	skis
-🛷	sled
-🥌	curling stone
-🎯	direct hit
-🎱	pool 8 ball
-🔮	crystal ball
-🧿	nazar amulet
-🎮	video game
-🕹️	joystick
-🕹	joystick
-🎰	slot machine
-🎲	game die
-🧩	jigsaw
-🧸	teddy bear
-♠️	spade suit
-♠	spade suit
-♥️	heart suit
-♥	heart suit
-♦️	diamond suit
-♦	diamond suit
-♣️	club suit
-♣	club suit
-♟️	chess pawn
-♟	chess pawn
-🃏	joker
-🀄	mahjong red dragon
-🎴	flower playing cards
-🎭	performing arts
-🖼️	framed picture
-🖼	framed picture
-🎨	artist palette
-🧵	thread
-🧶	yarn
-🔇	muted speaker
-🔈	speaker low volume
-🔉	speaker medium volume
-🔊	speaker high volume
-📢	loudspeaker
-📣	megaphone
-📯	postal horn
-🔔	bell
-🔕	bell with slash
-🎼	musical score
-🎵	musical note
-🎶	musical notes
-🎙️	studio microphone
-🎙	studio microphone
-🎚️	level slider
-🎚	level slider
-🎛️	control knobs
-🎛	control knobs
-🎤	microphone
-🎧	headphone
-📻	radio
-🎷	saxophone
-🎸	guitar
-🎹	musical keyboard
-🎺	trumpet
-🎻	violin
-🥁	drum
-📱	mobile phone
-📲	mobile phone with arrow
-☎️	telephone
-☎	telephone
-📞	telephone receiver
-📟	pager
-📠	fax machine
-🔋	battery
-🔌	electric plug
-💻	laptop computer
-🖥️	desktop computer
-🖥	desktop computer
-🖨️	printer
-🖨	printer
-⌨️	keyboard
-⌨	keyboard
-🖱️	computer mouse
-🖱	computer mouse
-🖲️	trackball
-🖲	trackball
-💽	computer disk
-💾	floppy disk
-💿	optical disk
-📀	dvd
-🧮	abacus
-🎥	movie camera
-🎞️	film frames
-🎞	film frames
-📽️	film projector
-📽	film projector
-🎬	clapper board
-📺	television
-📷	camera
-📸	camera with flash
-📹	video camera
-📼	videocassette
-🔍	magnifying glass tilted left
-🔎	magnifying glass tilted right
-🕯️	candle
-🕯	candle
-💡	light bulb
-🔦	flashlight
-🏮	red paper lantern
-📔	notebook with decorative cover
-📕	closed book
-📖	open book
-📗	green book
-📘	blue book
-📙	orange book
-📚	books
-📓	notebook
-📒	ledger
-📃	page with curl
-📜	scroll
-📄	page facing up
-📰	newspaper
-🗞️	rolled-up newspaper
-🗞	rolled-up newspaper
-📑	bookmark tabs
-🔖	bookmark
-🏷️	label
-🏷	label
-💰	money bag
-💴	yen banknote
-💵	dollar banknote
-💶	euro banknote
-💷	pound banknote
-💸	money with wings
-💳	credit card
-🧾	receipt
-💹	chart increasing with yen
-💱	currency exchange
-💲	heavy dollar sign
-✉️	envelope
-✉	envelope
-📧	e-mail
-📨	incoming envelope
-📩	envelope with arrow
-📤	outbox tray
-📥	inbox tray
-📦	package
-📫	closed mailbox with raised flag
-📪	closed mailbox with lowered flag
-📬	open mailbox with raised flag
-📭	open mailbox with lowered flag
-📮	postbox
-🗳️	ballot box with ballot
-🗳	ballot box with ballot
-✏️	pencil
-✏	pencil
-✒️	black nib
-✒	black nib
-🖋️	fountain pen
-🖋	fountain pen
-🖊️	pen
-🖊	pen
-🖌️	paintbrush
-🖌	paintbrush
-🖍️	crayon
-🖍	crayon
-📝	memo
-💼	briefcase
-📁	file folder
-📂	open file folder
-🗂️	card index dividers
-🗂	card index dividers
-📅	calendar
-📆	tear-off calendar
-🗒️	spiral notepad
-🗒	spiral notepad
-🗓️	spiral calendar
-🗓	spiral calendar
-📇	card index
-📈	chart increasing
-📉	chart decreasing
-📊	bar chart
-📋	clipboard
-📌	pushpin
-📍	round pushpin
-📎	paperclip
-🖇️	linked paperclips
-🖇	linked paperclips
-📏	straight ruler
-📐	triangular ruler
-✂️	scissors
-✂	scissors
-🗃️	card file box
-🗃	card file box
-🗄️	file cabinet
-🗄	file cabinet
-🗑️	wastebasket
-🗑	wastebasket
-🔒	locked
-🔓	unlocked
-🔏	locked with pen
-🔐	locked with key
-🔑	key
-🗝️	old key
-🗝	old key
-🔨	hammer
-⛏️	pick
-⛏	pick
-⚒️	hammer and pick
-⚒	hammer and pick
-🛠️	hammer and wrench
-🛠	hammer and wrench
-🗡️	dagger
-🗡	dagger
-⚔️	crossed swords
-⚔	crossed swords
-🔫	pistol
-🏹	bow and arrow
-🛡️	shield
-🛡	shield
-🔧	wrench
-🔩	nut and bolt
-⚙️	gear
-⚙	gear
-🗜️	clamp
-🗜	clamp
-⚖️	balance scale
-⚖	balance scale
-🔗	link
-⛓️	chains
-⛓	chains
-🧰	toolbox
-🧲	magnet
-⚗️	alembic
-⚗	alembic
-🧪	test tube
-🧫	petri dish
-🧬	dna
-🔬	microscope
-🔭	telescope
-📡	satellite antenna
-💉	syringe
-💊	pill
-🚪	door
-🛏️	bed
-🛏	bed
-🛋️	couch and lamp
-🛋	couch and lamp
-🚽	toilet
-🚿	shower
-🛁	bathtub
-🧴	lotion bottle
-🧷	safety pin
-🧹	broom
-🧺	basket
-🧻	roll of paper
-🧼	soap
-🧽	sponge
-🧯	fire extinguisher
-🛒	shopping cart
-🚬	cigarette
-⚰️	coffin
-⚰	coffin
-⚱️	funeral urn
-⚱	funeral urn
-🗿	moai
-🏧	ATM sign
-🚮	litter in bin sign
-🚰	potable water
-♿	wheelchair symbol
-🚹	men’s room
-🚺	women’s room
-🚻	restroom
-🚼	baby symbol
-🚾	water closet
-🛂	passport control
-🛃	customs
-🛄	baggage claim
-🛅	left luggage
-⚠️	warning
-⚠	warning
-🚸	children crossing
-⛔	no entry
-🚫	prohibited
-🚳	no bicycles
-🚭	no smoking
-🚯	no littering
-🚱	non-potable water
-🚷	no pedestrians
-📵	no mobile phones
-🔞	no one under eighteen
-☢️	radioactive
-☢	radioactive
-☣️	biohazard
-☣	biohazard
-⬆️	up arrow
-⬆	up arrow
-↗️	up-right arrow
-↗	up-right arrow
-➡️	right arrow
-➡	right arrow
-↘️	down-right arrow
-↘	down-right arrow
-⬇️	down arrow
-⬇	down arrow
-↙️	down-left arrow
-↙	down-left arrow
-⬅️	left arrow
-⬅	left arrow
-↖️	up-left arrow
-↖	up-left arrow
-↕️	up-down arrow
-↕	up-down arrow
-↔️	left-right arrow
-↔	left-right arrow
-↩️	right arrow curving left
-↩	right arrow curving left
-↪️	left arrow curving right
-↪	left arrow curving right
-⤴️	right arrow curving up
-⤴	right arrow curving up
-⤵️	right arrow curving down
-⤵	right arrow curving down
-🔃	clockwise vertical arrows
-🔄	counterclockwise arrows button
-🔙	BACK arrow
-🔚	END arrow
-🔛	ON! arrow
-🔜	SOON arrow
-🔝	TOP arrow
-🛐	place of worship
-⚛️	atom symbol
-⚛	atom symbol
-🕉️	om
-🕉	om
-✡️	star of David
-✡	star of David
-☸️	wheel of dharma
-☸	wheel of dharma
-☯️	yin yang
-☯	yin yang
-✝️	latin cross
-✝	latin cross
-☦️	orthodox cross
-☦	orthodox cross
-☪️	star and crescent
-☪	star and crescent
-☮️	peace symbol
-☮	peace symbol
-🕎	menorah
-🔯	dotted six-pointed star
-♈	Aries
-♉	Taurus
-♊	Gemini
-♋	Cancer
-♌	Leo
-♍	Virgo
-♎	Libra
-♏	Scorpio
-♐	Sagittarius
-♑	Capricorn
-♒	Aquarius
-♓	Pisces
-⛎	Ophiuchus
-🔀	shuffle tracks button
-🔁	repeat button
-🔂	repeat single button
-▶️	play button
-▶	play button
-⏩	fast-forward button
-⏭️	next track button
-⏭	next track button
-⏯️	play or pause button
-⏯	play or pause button
-◀️	reverse button
-◀	reverse button
-⏪	fast reverse button
-⏮️	last track button
-⏮	last track button
-🔼	upwards button
-⏫	fast up button
-🔽	downwards button
-⏬	fast down button
-⏸️	pause button
-⏸	pause button
-⏹️	stop button
-⏹	stop button
-⏺️	record button
-⏺	record button
-⏏️	eject button
-⏏	eject button
-🎦	cinema
-🔅	dim button
-🔆	bright button
-📶	antenna bars
-📳	vibration mode
-📴	mobile phone off
-♀️	female sign
-♀	female sign
-♂️	male sign
-♂	male sign
-⚕️	medical symbol
-⚕	medical symbol
-♾️	infinity
-♾	infinity
-♻️	recycling symbol
-♻	recycling symbol
-⚜️	fleur-de-lis
-⚜	fleur-de-lis
-🔱	trident emblem
-📛	name badge
-🔰	Japanese symbol for beginner
-⭕	heavy large circle
-✅	white heavy check mark
-☑️	ballot box with check
-☑	ballot box with check
-✔️	heavy check mark
-✔	heavy check mark
-✖️	heavy multiplication x
-✖	heavy multiplication x
-❌	cross mark
-❎	cross mark button
-➕	heavy plus sign
-➖	heavy minus sign
-➗	heavy division sign
-➰	curly loop
-➿	double curly loop
-〽️	part alternation mark
-〽	part alternation mark
-✳️	eight-spoked asterisk
-✳	eight-spoked asterisk
-✴️	eight-pointed star
-✴	eight-pointed star
-❇️	sparkle
-❇	sparkle
-‼️	double exclamation mark
-‼	double exclamation mark
-⁉️	exclamation question mark
-⁉	exclamation question mark
-❓	question mark
-❔	white question mark
-❕	white exclamation mark
-❗	exclamation mark
-〰️	wavy dash
-〰	wavy dash
-©️	copyright
-©	copyright
-®️	registered
-®	registered
-™️	trade mark
-™	trade mark
-#️⃣	keycap: #
-#⃣	keycap: #
-*️⃣	keycap: *
-*⃣	keycap: *
-0️⃣	keycap: 0
-0⃣	keycap: 0
-1️⃣	keycap: 1
-1⃣	keycap: 1
-2️⃣	keycap: 2
-2⃣	keycap: 2
-3️⃣	keycap: 3
-3⃣	keycap: 3
-4️⃣	keycap: 4
-4⃣	keycap: 4
-5️⃣	keycap: 5
-5⃣	keycap: 5
-6️⃣	keycap: 6
-6⃣	keycap: 6
-7️⃣	keycap: 7
-7⃣	keycap: 7
-8️⃣	keycap: 8
-8⃣	keycap: 8
-9️⃣	keycap: 9
-9⃣	keycap: 9
-🔟	keycap: 10
-💯	hundred points
-🔠	input latin uppercase
-🔡	input latin lowercase
-🔢	input numbers
-🔣	input symbols
-🔤	input latin letters
-🅰️	A button (blood type)
-🅰	A button (blood type)
-🆎	AB button (blood type)
-🅱️	B button (blood type)
-🅱	B button (blood type)
-🆑	CL button
-🆒	COOL button
-🆓	FREE button
-ℹ️	information
-ℹ	information
-🆔	ID button
-Ⓜ️	circled M
-Ⓜ	circled M
-🆕	NEW button
-🆖	NG button
-🅾️	O button (blood type)
-🅾	O button (blood type)
-🆗	OK button
-🅿️	P button
-🅿	P button
-🆘	SOS button
-🆙	UP! button
-🆚	VS button
-🈁	Japanese “here” button
-🈂️	Japanese “service charge” button
-🈂	Japanese “service charge” button
-🈷️	Japanese “monthly amount” button
-🈷	Japanese “monthly amount” button
-🈶	Japanese “not free of charge” button
-🈯	Japanese “reserved” button
-🉐	Japanese “bargain” button
-🈹	Japanese “discount” button
-🈚	Japanese “free of charge” button
-🈲	Japanese “prohibited” button
-🉑	Japanese “acceptable” button
-🈸	Japanese “application” button
-🈴	Japanese “passing grade” button
-🈳	Japanese “vacancy” button
-㊗️	Japanese “congratulations” button
-㊗	Japanese “congratulations” button
-㊙️	Japanese “secret” button
-㊙	Japanese “secret” button
-🈺	Japanese “open for business” button
-🈵	Japanese “no vacancy” button
-▪️	black small square
-▪	black small square
-▫️	white small square
-▫	white small square
-◻️	white medium square
-◻	white medium square
-◼️	black medium square
-◼	black medium square
-◽	white medium-small square
-◾	black medium-small square
-⬛	black large square
-⬜	white large square
-🔶	large orange diamond
-🔷	large blue diamond
-🔸	small orange diamond
-🔹	small blue diamond
-🔺	red triangle pointed up
-🔻	red triangle pointed down
-💠	diamond with a dot
-🔘	radio button
-🔲	black square button
-🔳	white square button
-⚪	white circle
-⚫	black circle
-🔴	red circle
-🔵	blue circle
-🏁	chequered flag
-🚩	triangular flag
-🎌	crossed flags
-🏴	black flag
-🏳️	white flag
-🏳	white flag
-🏳️‍🌈	rainbow flag
-🏳‍🌈	rainbow flag
-🏴‍☠️	pirate flag
-🏴‍☠	pirate flag
-🇦🇨	Ascension Island
-🇦🇩	Andorra
-🇦🇪	United Arab Emirates
-🇦🇫	Afghanistan
-🇦🇬	Antigua & Barbuda
-🇦🇮	Anguilla
-🇦🇱	Albania
-🇦🇲	Armenia
-🇦🇴	Angola
-🇦🇶	Antarctica
-🇦🇷	Argentina
-🇦🇸	American Samoa
-🇦🇹	Austria
-🇦🇺	Australia
-🇦🇼	Aruba
-🇦🇽	Åland Islands
-🇦🇿	Azerbaijan
-🇧🇦	Bosnia & Herzegovina
-🇧🇧	Barbados
-🇧🇩	Bangladesh
-🇧🇪	Belgium
-🇧🇫	Burkina Faso
-🇧🇬	Bulgaria
-🇧🇭	Bahrain
-🇧🇮	Burundi
-🇧🇯	Benin
-🇧🇱	St. Barthélemy
-🇧🇲	Bermuda
-🇧🇳	Brunei
-🇧🇴	Bolivia
-🇧🇶	Caribbean Netherlands
-🇧🇷	Brazil
-🇧🇸	Bahamas
-🇧🇹	Bhutan
-🇧🇻	Bouvet Island
-🇧🇼	Botswana
-🇧🇾	Belarus
-🇧🇿	Belize
-🇨🇦	Canada
-🇨🇨	Cocos (Keeling) Islands
-🇨🇩	Congo - Kinshasa
-🇨🇫	Central African Republic
-🇨🇬	Congo - Brazzaville
-🇨🇭	Switzerland
-🇨🇮	Côte d’Ivoire
-🇨🇰	Cook Islands
-🇨🇱	Chile
-🇨🇲	Cameroon
-🇨🇳	China
-🇨🇴	Colombia
-🇨🇵	Clipperton Island
-🇨🇷	Costa Rica
-🇨🇺	Cuba
-🇨🇻	Cape Verde
-🇨🇼	Curaçao
-🇨🇽	Christmas Island
-🇨🇾	Cyprus
-🇨🇿	Czechia
-🇩🇪	Germany
-🇩🇬	Diego Garcia
-🇩🇯	Djibouti
-🇩🇰	Denmark
-🇩🇲	Dominica
-🇩🇴	Dominican Republic
-🇩🇿	Algeria
-🇪🇦	Ceuta & Melilla
-🇪🇨	Ecuador
-🇪🇪	Estonia
-🇪🇬	Egypt
-🇪🇭	Western Sahara
-🇪🇷	Eritrea
-🇪🇸	Spain
-🇪🇹	Ethiopia
-🇪🇺	European Union
-🇫🇮	Finland
-🇫🇯	Fiji
-🇫🇰	Falkland Islands
-🇫🇲	Micronesia
-🇫🇴	Faroe Islands
-🇫🇷	France
-🇬🇦	Gabon
-🇬🇧	United Kingdom
-🇬🇩	Grenada
-🇬🇪	Georgia
-🇬🇫	French Guiana
-🇬🇬	Guernsey
-🇬🇭	Ghana
-🇬🇮	Gibraltar
-🇬🇱	Greenland
-🇬🇲	Gambia
-🇬🇳	Guinea
-🇬🇵	Guadeloupe
-🇬🇶	Equatorial Guinea
-🇬🇷	Greece
-🇬🇸	South Georgia & South Sandwich Islands
-🇬🇹	Guatemala
-🇬🇺	Guam
-🇬🇼	Guinea-Bissau
-🇬🇾	Guyana
-🇭🇰	Hong Kong SAR China
-🇭🇲	Heard & McDonald Islands
-🇭🇳	Honduras
-🇭🇷	Croatia
-🇭🇹	Haiti
-🇭🇺	Hungary
-🇮🇨	Canary Islands
-🇮🇩	Indonesia
-🇮🇪	Ireland
-🇮🇱	Israel
-🇮🇲	Isle of Man
-🇮🇳	India
-🇮🇴	British Indian Ocean Territory
-🇮🇶	Iraq
-🇮🇷	Iran
-🇮🇸	Iceland
-🇮🇹	Italy
-🇯🇪	Jersey
-🇯🇲	Jamaica
-🇯🇴	Jordan
-🇯🇵	Japan
-🇰🇪	Kenya
-🇰🇬	Kyrgyzstan
-🇰🇭	Cambodia
-🇰🇮	Kiribati
-🇰🇲	Comoros
-🇰🇳	St. Kitts & Nevis
-🇰🇵	North Korea
-🇰🇷	South Korea
-🇰🇼	Kuwait
-🇰🇾	Cayman Islands
-🇰🇿	Kazakhstan
-🇱🇦	Laos
-🇱🇧	Lebanon
-🇱🇨	St. Lucia
-🇱🇮	Liechtenstein
-🇱🇰	Sri Lanka
-🇱🇷	Liberia
-🇱🇸	Lesotho
-🇱🇹	Lithuania
-🇱🇺	Luxembourg
-🇱🇻	Latvia
-🇱🇾	Libya
-🇲🇦	Morocco
-🇲🇨	Monaco
-🇲🇩	Moldova
-🇲🇪	Montenegro
-🇲🇫	St. Martin
-🇲🇬	Madagascar
-🇲🇭	Marshall Islands
-🇲🇰	Macedonia
-🇲🇱	Mali
-🇲🇲	Myanmar (Burma)
-🇲🇳	Mongolia
-🇲🇴	Macau SAR China
-🇲🇵	Northern Mariana Islands
-🇲🇶	Martinique
-🇲🇷	Mauritania
-🇲🇸	Montserrat
-🇲🇹	Malta
-🇲🇺	Mauritius
-🇲🇻	Maldives
-🇲🇼	Malawi
-🇲🇽	Mexico
-🇲🇾	Malaysia
-🇲🇿	Mozambique
-🇳🇦	Namibia
-🇳🇨	New Caledonia
-🇳🇪	Niger
-🇳🇫	Norfolk Island
-🇳🇬	Nigeria
-🇳🇮	Nicaragua
-🇳🇱	Netherlands
-🇳🇴	Norway
-🇳🇵	Nepal
-🇳🇷	Nauru
-🇳🇺	Niue
-🇳🇿	New Zealand
-🇴🇲	Oman
-🇵🇦	Panama
-🇵🇪	Peru
-🇵🇫	French Polynesia
-🇵🇬	Papua New Guinea
-🇵🇭	Philippines
-🇵🇰	Pakistan
-🇵🇱	Poland
-🇵🇲	St. Pierre & Miquelon
-🇵🇳	Pitcairn Islands
-🇵🇷	Puerto Rico
-🇵🇸	Palestinian Territories
-🇵🇹	Portugal
-🇵🇼	Palau
-🇵🇾	Paraguay
-🇶🇦	Qatar
-🇷🇪	Réunion
-🇷🇴	Romania
-🇷🇸	Serbia
-🇷🇺	Russia
-🇷🇼	Rwanda
-🇸🇦	Saudi Arabia
-🇸🇧	Solomon Islands
-🇸🇨	Seychelles
-🇸🇩	Sudan
-🇸🇪	Sweden
-🇸🇬	Singapore
-🇸🇭	St. Helena
-🇸🇮	Slovenia
-🇸🇯	Svalbard & Jan Mayen
-🇸🇰	Slovakia
-🇸🇱	Sierra Leone
-🇸🇲	San Marino
-🇸🇳	Senegal
-🇸🇴	Somalia
-🇸🇷	Suriname
-🇸🇸	South Sudan
-🇸🇹	São Tomé & Príncipe
-🇸🇻	El Salvador
-🇸🇽	Sint Maarten
-🇸🇾	Syria
-🇸🇿	Swaziland
-🇹🇦	Tristan da Cunha
-🇹🇨	Turks & Caicos Islands
-🇹🇩	Chad
-🇹🇫	French Southern Territories
-🇹🇬	Togo
-🇹🇭	Thailand
-🇹🇯	Tajikistan
-🇹🇰	Tokelau
-🇹🇱	Timor-Leste
-🇹🇲	Turkmenistan
-🇹🇳	Tunisia
-🇹🇴	Tonga
-🇹🇷	Turkey
-🇹🇹	Trinidad & Tobago
-🇹🇻	Tuvalu
-🇹🇼	Taiwan
-🇹🇿	Tanzania
-🇺🇦	Ukraine
-🇺🇬	Uganda
-🇺🇲	U.S. Outlying Islands
-🇺🇳	United Nations
-🇺🇸	United States
-🇺🇾	Uruguay
-🇺🇿	Uzbekistan
-🇻🇦	Vatican City
-🇻🇨	St. Vincent & Grenadines
-🇻🇪	Venezuela
-🇻🇬	British Virgin Islands
-🇻🇮	U.S. Virgin Islands
-🇻🇳	Vietnam
-🇻🇺	Vanuatu
-🇼🇫	Wallis & Futuna
-🇼🇸	Samoa
-🇽🇰	Kosovo
-🇾🇪	Yemen
-🇾🇹	Mayotte
-🇿🇦	South Africa
-🇿🇲	Zambia
-🇿🇼	Zimbabwe
-🏴󠁧󠁢󠁥󠁮󠁧󠁿	England
-🏴󠁧󠁢󠁳󠁣󠁴󠁿	Scotland
+😀	grinning face
+😁	beaming face with smiling eyes
+😂	face with tears of joy
+🤣	rolling on the floor laughing
+😃	grinning face with big eyes
+😄	grinning face with smiling eyes
+😅	grinning face with sweat
+😆	grinning squinting face
+😉	winking face
+😊	smiling face with smiling eyes
+😋	face savoring food
+😎	smiling face with sunglasses
+😍	smiling face with heart-eyes
+😘	face blowing a kiss
+🥰	smiling face with 3 hearts
+😗	kissing face
+😙	kissing face with smiling eyes
+😚	kissing face with closed eyes
+☺️	smiling face
+☺	smiling face
+🙂	slightly smiling face
+🤗	hugging face
+🤩	star-struck
+🤔	thinking face
+🤨	face with raised eyebrow
+😐	neutral face
+😑	expressionless face
+😶	face without mouth
+🙄	face with rolling eyes
+😏	smirking face
+😣	persevering face
+😥	sad but relieved face
+😮	face with open mouth
+🤐	zipper-mouth face
+😯	hushed face
+😪	sleepy face
+😫	tired face
+😴	sleeping face
+😌	relieved face
+😛	face with tongue
+😜	winking face with tongue
+😝	squinting face with tongue
+🤤	drooling face
+😒	unamused face
+😓	downcast face with sweat
+😔	pensive face
+😕	confused face
+🙃	upside-down face
+🤑	money-mouth face
+😲	astonished face
+☹️	frowning face
+☹	frowning face
+🙁	slightly frowning face
+😖	confounded face
+😞	disappointed face
+😟	worried face
+😤	face with steam from nose
+😢	crying face
+😭	loudly crying face
+😦	frowning face with open mouth
+😧	anguished face
+😨	fearful face
+😩	weary face
+🤯	exploding head
+😬	grimacing face
+😰	anxious face with sweat
+😱	face screaming in fear
+🥵	hot face
+🥶	cold face
+😳	flushed face
+🤪	zany face
+😵	dizzy face
+😡	pouting face
+😠	angry face
+🤬	face with symbols on mouth
+😷	face with medical mask
+🤒	face with thermometer
+🤕	face with head-bandage
+🤢	nauseated face
+🤮	face vomiting
+🤧	sneezing face
+😇	smiling face with halo
+🤠	cowboy hat face
+🥳	partying face
+🥴	woozy face
+🥺	pleading face
+🤥	lying face
+🤫	shushing face
+🤭	face with hand over mouth
+🧐	face with monocle
+🤓	nerd face
+😈	smiling face with horns
+👿	angry face with horns
+🤡	clown face
+👹	ogre
+👺	goblin
+💀	skull
+☠️	skull and crossbones
+☠	skull and crossbones
+👻	ghost
+👽	alien
+👾	alien monster
+🤖	robot face
+💩	pile of poo
+😺	grinning cat face
+😸	grinning cat face with smiling eyes
+😹	cat face with tears of joy
+😻	smiling cat face with heart-eyes
+😼	cat face with wry smile
+😽	kissing cat face
+🙀	weary cat face
+😿	crying cat face
+😾	pouting cat face
+🙈	see-no-evil monkey
+🙉	hear-no-evil monkey
+🙊	speak-no-evil monkey
+🏻	light skin tone
+🏼	medium-light skin tone
+🏽	medium skin tone
+🏾	medium-dark skin tone
+🏿	dark skin tone
+👶	baby
+👶🏻	baby: light skin tone
+👶🏼	baby: medium-light skin tone
+👶🏽	baby: medium skin tone
+👶🏾	baby: medium-dark skin tone
+👶🏿	baby: dark skin tone
+🧒	child
+🧒🏻	child: light skin tone
+🧒🏼	child: medium-light skin tone
+🧒🏽	child: medium skin tone
+🧒🏾	child: medium-dark skin tone
+🧒🏿	child: dark skin tone
+👦	boy
+👦🏻	boy: light skin tone
+👦🏼	boy: medium-light skin tone
+👦🏽	boy: medium skin tone
+👦🏾	boy: medium-dark skin tone
+👦🏿	boy: dark skin tone
+👧	girl
+👧🏻	girl: light skin tone
+👧🏼	girl: medium-light skin tone
+👧🏽	girl: medium skin tone
+👧🏾	girl: medium-dark skin tone
+👧🏿	girl: dark skin tone
+🧑	adult
+🧑🏻	adult: light skin tone
+🧑🏼	adult: medium-light skin tone
+🧑🏽	adult: medium skin tone
+🧑🏾	adult: medium-dark skin tone
+🧑🏿	adult: dark skin tone
+👨	man
+👨🏻	man: light skin tone
+👨🏼	man: medium-light skin tone
+👨🏽	man: medium skin tone
+👨🏾	man: medium-dark skin tone
+👨🏿	man: dark skin tone
+👩	woman
+👩🏻	woman: light skin tone
+👩🏼	woman: medium-light skin tone
+👩🏽	woman: medium skin tone
+👩🏾	woman: medium-dark skin tone
+👩🏿	woman: dark skin tone
+🧓	older adult
+🧓🏻	older adult: light skin tone
+🧓🏼	older adult: medium-light skin tone
+🧓🏽	older adult: medium skin tone
+🧓🏾	older adult: medium-dark skin tone
+🧓🏿	older adult: dark skin tone
+👴	old man
+👴🏻	old man: light skin tone
+👴🏼	old man: medium-light skin tone
+👴🏽	old man: medium skin tone
+👴🏾	old man: medium-dark skin tone
+👴🏿	old man: dark skin tone
+👵	old woman
+👵🏻	old woman: light skin tone
+👵🏼	old woman: medium-light skin tone
+👵🏽	old woman: medium skin tone
+👵🏾	old woman: medium-dark skin tone
+👵🏿	old woman: dark skin tone
+👨‍⚕️	man health worker
+👨‍⚕	man health worker
+👨🏻‍⚕️	man health worker: light skin tone
+👨🏻‍⚕	man health worker: light skin tone
+👨🏼‍⚕️	man health worker: medium-light skin tone
+👨🏼‍⚕	man health worker: medium-light skin tone
+👨🏽‍⚕️	man health worker: medium skin tone
+👨🏽‍⚕	man health worker: medium skin tone
+👨🏾‍⚕️	man health worker: medium-dark skin tone
+👨🏾‍⚕	man health worker: medium-dark skin tone
+👨🏿‍⚕️	man health worker: dark skin tone
+👨🏿‍⚕	man health worker: dark skin tone
+👩‍⚕️	woman health worker
+👩‍⚕	woman health worker
+👩🏻‍⚕️	woman health worker: light skin tone
+👩🏻‍⚕	woman health worker: light skin tone
+👩🏼‍⚕️	woman health worker: medium-light skin tone
+👩🏼‍⚕	woman health worker: medium-light skin tone
+👩🏽‍⚕️	woman health worker: medium skin tone
+👩🏽‍⚕	woman health worker: medium skin tone
+👩🏾‍⚕️	woman health worker: medium-dark skin tone
+👩🏾‍⚕	woman health worker: medium-dark skin tone
+👩🏿‍⚕️	woman health worker: dark skin tone
+👩🏿‍⚕	woman health worker: dark skin tone
+👨‍🎓	man student
+👨🏻‍🎓	man student: light skin tone
+👨🏼‍🎓	man student: medium-light skin tone
+👨🏽‍🎓	man student: medium skin tone
+👨🏾‍🎓	man student: medium-dark skin tone
+👨🏿‍🎓	man student: dark skin tone
+👩‍🎓	woman student
+👩🏻‍🎓	woman student: light skin tone
+👩🏼‍🎓	woman student: medium-light skin tone
+👩🏽‍🎓	woman student: medium skin tone
+👩🏾‍🎓	woman student: medium-dark skin tone
+👩🏿‍🎓	woman student: dark skin tone
+👨‍🏫	man teacher
+👨🏻‍🏫	man teacher: light skin tone
+👨🏼‍🏫	man teacher: medium-light skin tone
+👨🏽‍🏫	man teacher: medium skin tone
+👨🏾‍🏫	man teacher: medium-dark skin tone
+👨🏿‍🏫	man teacher: dark skin tone
+👩‍🏫	woman teacher
+👩🏻‍🏫	woman teacher: light skin tone
+👩🏼‍🏫	woman teacher: medium-light skin tone
+👩🏽‍🏫	woman teacher: medium skin tone
+👩🏾‍🏫	woman teacher: medium-dark skin tone
+👩🏿‍🏫	woman teacher: dark skin tone
+👨‍⚖️	man judge
+👨‍⚖	man judge
+👨🏻‍⚖️	man judge: light skin tone
+👨🏻‍⚖	man judge: light skin tone
+👨🏼‍⚖️	man judge: medium-light skin tone
+👨🏼‍⚖	man judge: medium-light skin tone
+👨🏽‍⚖️	man judge: medium skin tone
+👨🏽‍⚖	man judge: medium skin tone
+👨🏾‍⚖️	man judge: medium-dark skin tone
+👨🏾‍⚖	man judge: medium-dark skin tone
+👨🏿‍⚖️	man judge: dark skin tone
+👨🏿‍⚖	man judge: dark skin tone
+👩‍⚖️	woman judge
+👩‍⚖	woman judge
+👩🏻‍⚖️	woman judge: light skin tone
+👩🏻‍⚖	woman judge: light skin tone
+👩🏼‍⚖️	woman judge: medium-light skin tone
+👩🏼‍⚖	woman judge: medium-light skin tone
+👩🏽‍⚖️	woman judge: medium skin tone
+👩🏽‍⚖	woman judge: medium skin tone
+👩🏾‍⚖️	woman judge: medium-dark skin tone
+👩🏾‍⚖	woman judge: medium-dark skin tone
+👩🏿‍⚖️	woman judge: dark skin tone
+👩🏿‍⚖	woman judge: dark skin tone
+👨‍🌾	man farmer
+👨🏻‍🌾	man farmer: light skin tone
+👨🏼‍🌾	man farmer: medium-light skin tone
+👨🏽‍🌾	man farmer: medium skin tone
+👨🏾‍🌾	man farmer: medium-dark skin tone
+👨🏿‍🌾	man farmer: dark skin tone
+👩‍🌾	woman farmer
+👩🏻‍🌾	woman farmer: light skin tone
+👩🏼‍🌾	woman farmer: medium-light skin tone
+👩🏽‍🌾	woman farmer: medium skin tone
+👩🏾‍🌾	woman farmer: medium-dark skin tone
+👩🏿‍🌾	woman farmer: dark skin tone
+👨‍🍳	man cook
+👨🏻‍🍳	man cook: light skin tone
+👨🏼‍🍳	man cook: medium-light skin tone
+👨🏽‍🍳	man cook: medium skin tone
+👨🏾‍🍳	man cook: medium-dark skin tone
+👨🏿‍🍳	man cook: dark skin tone
+👩‍🍳	woman cook
+👩🏻‍🍳	woman cook: light skin tone
+👩🏼‍🍳	woman cook: medium-light skin tone
+👩🏽‍🍳	woman cook: medium skin tone
+👩🏾‍🍳	woman cook: medium-dark skin tone
+👩🏿‍🍳	woman cook: dark skin tone
+👨‍🔧	man mechanic
+👨🏻‍🔧	man mechanic: light skin tone
+👨🏼‍🔧	man mechanic: medium-light skin tone
+👨🏽‍🔧	man mechanic: medium skin tone
+👨🏾‍🔧	man mechanic: medium-dark skin tone
+👨🏿‍🔧	man mechanic: dark skin tone
+👩‍🔧	woman mechanic
+👩🏻‍🔧	woman mechanic: light skin tone
+👩🏼‍🔧	woman mechanic: medium-light skin tone
+👩🏽‍🔧	woman mechanic: medium skin tone
+👩🏾‍🔧	woman mechanic: medium-dark skin tone
+👩🏿‍🔧	woman mechanic: dark skin tone
+👨‍🏭	man factory worker
+👨🏻‍🏭	man factory worker: light skin tone
+👨🏼‍🏭	man factory worker: medium-light skin tone
+👨🏽‍🏭	man factory worker: medium skin tone
+👨🏾‍🏭	man factory worker: medium-dark skin tone
+👨🏿‍🏭	man factory worker: dark skin tone
+👩‍🏭	woman factory worker
+👩🏻‍🏭	woman factory worker: light skin tone
+👩🏼‍🏭	woman factory worker: medium-light skin tone
+👩🏽‍🏭	woman factory worker: medium skin tone
+👩🏾‍🏭	woman factory worker: medium-dark skin tone
+👩🏿‍🏭	woman factory worker: dark skin tone
+👨‍💼	man office worker
+👨🏻‍💼	man office worker: light skin tone
+👨🏼‍💼	man office worker: medium-light skin tone
+👨🏽‍💼	man office worker: medium skin tone
+👨🏾‍💼	man office worker: medium-dark skin tone
+👨🏿‍💼	man office worker: dark skin tone
+👩‍💼	woman office worker
+👩🏻‍💼	woman office worker: light skin tone
+👩🏼‍💼	woman office worker: medium-light skin tone
+👩🏽‍💼	woman office worker: medium skin tone
+👩🏾‍💼	woman office worker: medium-dark skin tone
+👩🏿‍💼	woman office worker: dark skin tone
+👨‍🔬	man scientist
+👨🏻‍🔬	man scientist: light skin tone
+👨🏼‍🔬	man scientist: medium-light skin tone
+👨🏽‍🔬	man scientist: medium skin tone
+👨🏾‍🔬	man scientist: medium-dark skin tone
+👨🏿‍🔬	man scientist: dark skin tone
+👩‍🔬	woman scientist
+👩🏻‍🔬	woman scientist: light skin tone
+👩🏼‍🔬	woman scientist: medium-light skin tone
+👩🏽‍🔬	woman scientist: medium skin tone
+👩🏾‍🔬	woman scientist: medium-dark skin tone
+👩🏿‍🔬	woman scientist: dark skin tone
+👨‍💻	man technologist
+👨🏻‍💻	man technologist: light skin tone
+👨🏼‍💻	man technologist: medium-light skin tone
+👨🏽‍💻	man technologist: medium skin tone
+👨🏾‍💻	man technologist: medium-dark skin tone
+👨🏿‍💻	man technologist: dark skin tone
+👩‍💻	woman technologist
+👩🏻‍💻	woman technologist: light skin tone
+👩🏼‍💻	woman technologist: medium-light skin tone
+👩🏽‍💻	woman technologist: medium skin tone
+👩🏾‍💻	woman technologist: medium-dark skin tone
+👩🏿‍💻	woman technologist: dark skin tone
+👨‍🎤	man singer
+👨🏻‍🎤	man singer: light skin tone
+👨🏼‍🎤	man singer: medium-light skin tone
+👨🏽‍🎤	man singer: medium skin tone
+👨🏾‍🎤	man singer: medium-dark skin tone
+👨🏿‍🎤	man singer: dark skin tone
+👩‍🎤	woman singer
+👩🏻‍🎤	woman singer: light skin tone
+👩🏼‍🎤	woman singer: medium-light skin tone
+👩🏽‍🎤	woman singer: medium skin tone
+👩🏾‍🎤	woman singer: medium-dark skin tone
+👩🏿‍🎤	woman singer: dark skin tone
+👨‍🎨	man artist
+👨🏻‍🎨	man artist: light skin tone
+👨🏼‍🎨	man artist: medium-light skin tone
+👨🏽‍🎨	man artist: medium skin tone
+👨🏾‍🎨	man artist: medium-dark skin tone
+👨🏿‍🎨	man artist: dark skin tone
+👩‍🎨	woman artist
+👩🏻‍🎨	woman artist: light skin tone
+👩🏼‍🎨	woman artist: medium-light skin tone
+👩🏽‍🎨	woman artist: medium skin tone
+👩🏾‍🎨	woman artist: medium-dark skin tone
+👩🏿‍🎨	woman artist: dark skin tone
+👨‍✈️	man pilot
+👨‍✈	man pilot
+👨🏻‍✈️	man pilot: light skin tone
+👨🏻‍✈	man pilot: light skin tone
+👨🏼‍✈️	man pilot: medium-light skin tone
+👨🏼‍✈	man pilot: medium-light skin tone
+👨🏽‍✈️	man pilot: medium skin tone
+👨🏽‍✈	man pilot: medium skin tone
+👨🏾‍✈️	man pilot: medium-dark skin tone
+👨🏾‍✈	man pilot: medium-dark skin tone
+👨🏿‍✈️	man pilot: dark skin tone
+👨🏿‍✈	man pilot: dark skin tone
+👩‍✈️	woman pilot
+👩‍✈	woman pilot
+👩🏻‍✈️	woman pilot: light skin tone
+👩🏻‍✈	woman pilot: light skin tone
+👩🏼‍✈️	woman pilot: medium-light skin tone
+👩🏼‍✈	woman pilot: medium-light skin tone
+👩🏽‍✈️	woman pilot: medium skin tone
+👩🏽‍✈	woman pilot: medium skin tone
+👩🏾‍✈️	woman pilot: medium-dark skin tone
+👩🏾‍✈	woman pilot: medium-dark skin tone
+👩🏿‍✈️	woman pilot: dark skin tone
+👩🏿‍✈	woman pilot: dark skin tone
+👨‍🚀	man astronaut
+👨🏻‍🚀	man astronaut: light skin tone
+👨🏼‍🚀	man astronaut: medium-light skin tone
+👨🏽‍🚀	man astronaut: medium skin tone
+👨🏾‍🚀	man astronaut: medium-dark skin tone
+👨🏿‍🚀	man astronaut: dark skin tone
+👩‍🚀	woman astronaut
+👩🏻‍🚀	woman astronaut: light skin tone
+👩🏼‍🚀	woman astronaut: medium-light skin tone
+👩🏽‍🚀	woman astronaut: medium skin tone
+👩🏾‍🚀	woman astronaut: medium-dark skin tone
+👩🏿‍🚀	woman astronaut: dark skin tone
+👨‍🚒	man firefighter
+👨🏻‍🚒	man firefighter: light skin tone
+👨🏼‍🚒	man firefighter: medium-light skin tone
+👨🏽‍🚒	man firefighter: medium skin tone
+👨🏾‍🚒	man firefighter: medium-dark skin tone
+👨🏿‍🚒	man firefighter: dark skin tone
+👩‍🚒	woman firefighter
+👩🏻‍🚒	woman firefighter: light skin tone
+👩🏼‍🚒	woman firefighter: medium-light skin tone
+👩🏽‍🚒	woman firefighter: medium skin tone
+👩🏾‍🚒	woman firefighter: medium-dark skin tone
+👩🏿‍🚒	woman firefighter: dark skin tone
+👮	police officer
+👮🏻	police officer: light skin tone
+👮🏼	police officer: medium-light skin tone
+👮🏽	police officer: medium skin tone
+👮🏾	police officer: medium-dark skin tone
+👮🏿	police officer: dark skin tone
+👮‍♂️	man police officer
+👮‍♂	man police officer
+👮🏻‍♂️	man police officer: light skin tone
+👮🏻‍♂	man police officer: light skin tone
+👮🏼‍♂️	man police officer: medium-light skin tone
+👮🏼‍♂	man police officer: medium-light skin tone
+👮🏽‍♂️	man police officer: medium skin tone
+👮🏽‍♂	man police officer: medium skin tone
+👮🏾‍♂️	man police officer: medium-dark skin tone
+👮🏾‍♂	man police officer: medium-dark skin tone
+👮🏿‍♂️	man police officer: dark skin tone
+👮🏿‍♂	man police officer: dark skin tone
+👮‍♀️	woman police officer
+👮‍♀	woman police officer
+👮🏻‍♀️	woman police officer: light skin tone
+👮🏻‍♀	woman police officer: light skin tone
+👮🏼‍♀️	woman police officer: medium-light skin tone
+👮🏼‍♀	woman police officer: medium-light skin tone
+👮🏽‍♀️	woman police officer: medium skin tone
+👮🏽‍♀	woman police officer: medium skin tone
+👮🏾‍♀️	woman police officer: medium-dark skin tone
+👮🏾‍♀	woman police officer: medium-dark skin tone
+👮🏿‍♀️	woman police officer: dark skin tone
+👮🏿‍♀	woman police officer: dark skin tone
+🕵️	detective
+🕵	detective
+🕵🏻	detective: light skin tone
+🕵🏼	detective: medium-light skin tone
+🕵🏽	detective: medium skin tone
+🕵🏾	detective: medium-dark skin tone
+🕵🏿	detective: dark skin tone
+🕵️‍♂️	man detective
+🕵‍♂️	man detective
+🕵️‍♂	man detective
+🕵‍♂	man detective
+🕵🏻‍♂️	man detective: light skin tone
+🕵🏻‍♂	man detective: light skin tone
+🕵🏼‍♂️	man detective: medium-light skin tone
+🕵🏼‍♂	man detective: medium-light skin tone
+🕵🏽‍♂️	man detective: medium skin tone
+🕵🏽‍♂	man detective: medium skin tone
+🕵🏾‍♂️	man detective: medium-dark skin tone
+🕵🏾‍♂	man detective: medium-dark skin tone
+🕵🏿‍♂️	man detective: dark skin tone
+🕵🏿‍♂	man detective: dark skin tone
+🕵️‍♀️	woman detective
+🕵‍♀️	woman detective
+🕵️‍♀	woman detective
+🕵‍♀	woman detective
+🕵🏻‍♀️	woman detective: light skin tone
+🕵🏻‍♀	woman detective: light skin tone
+🕵🏼‍♀️	woman detective: medium-light skin tone
+🕵🏼‍♀	woman detective: medium-light skin tone
+🕵🏽‍♀️	woman detective: medium skin tone
+🕵🏽‍♀	woman detective: medium skin tone
+🕵🏾‍♀️	woman detective: medium-dark skin tone
+🕵🏾‍♀	woman detective: medium-dark skin tone
+🕵🏿‍♀️	woman detective: dark skin tone
+🕵🏿‍♀	woman detective: dark skin tone
+💂	guard
+💂🏻	guard: light skin tone
+💂🏼	guard: medium-light skin tone
+💂🏽	guard: medium skin tone
+💂🏾	guard: medium-dark skin tone
+💂🏿	guard: dark skin tone
+💂‍♂️	man guard
+💂‍♂	man guard
+💂🏻‍♂️	man guard: light skin tone
+💂🏻‍♂	man guard: light skin tone
+💂🏼‍♂️	man guard: medium-light skin tone
+💂🏼‍♂	man guard: medium-light skin tone
+💂🏽‍♂️	man guard: medium skin tone
+💂🏽‍♂	man guard: medium skin tone
+💂🏾‍♂️	man guard: medium-dark skin tone
+💂🏾‍♂	man guard: medium-dark skin tone
+💂🏿‍♂️	man guard: dark skin tone
+💂🏿‍♂	man guard: dark skin tone
+💂‍♀️	woman guard
+💂‍♀	woman guard
+💂🏻‍♀️	woman guard: light skin tone
+💂🏻‍♀	woman guard: light skin tone
+💂🏼‍♀️	woman guard: medium-light skin tone
+💂🏼‍♀	woman guard: medium-light skin tone
+💂🏽‍♀️	woman guard: medium skin tone
+💂🏽‍♀	woman guard: medium skin tone
+💂🏾‍♀️	woman guard: medium-dark skin tone
+💂🏾‍♀	woman guard: medium-dark skin tone
+💂🏿‍♀️	woman guard: dark skin tone
+💂🏿‍♀	woman guard: dark skin tone
+👷	construction worker
+👷🏻	construction worker: light skin tone
+👷🏼	construction worker: medium-light skin tone
+👷🏽	construction worker: medium skin tone
+👷🏾	construction worker: medium-dark skin tone
+👷🏿	construction worker: dark skin tone
+👷‍♂️	man construction worker
+👷‍♂	man construction worker
+👷🏻‍♂️	man construction worker: light skin tone
+👷🏻‍♂	man construction worker: light skin tone
+👷🏼‍♂️	man construction worker: medium-light skin tone
+👷🏼‍♂	man construction worker: medium-light skin tone
+👷🏽‍♂️	man construction worker: medium skin tone
+👷🏽‍♂	man construction worker: medium skin tone
+👷🏾‍♂️	man construction worker: medium-dark skin tone
+👷🏾‍♂	man construction worker: medium-dark skin tone
+👷🏿‍♂️	man construction worker: dark skin tone
+👷🏿‍♂	man construction worker: dark skin tone
+👷‍♀️	woman construction worker
+👷‍♀	woman construction worker
+👷🏻‍♀️	woman construction worker: light skin tone
+👷🏻‍♀	woman construction worker: light skin tone
+👷🏼‍♀️	woman construction worker: medium-light skin tone
+👷🏼‍♀	woman construction worker: medium-light skin tone
+👷🏽‍♀️	woman construction worker: medium skin tone
+👷🏽‍♀	woman construction worker: medium skin tone
+👷🏾‍♀️	woman construction worker: medium-dark skin tone
+👷🏾‍♀	woman construction worker: medium-dark skin tone
+👷🏿‍♀️	woman construction worker: dark skin tone
+👷🏿‍♀	woman construction worker: dark skin tone
+🤴	prince
+🤴🏻	prince: light skin tone
+🤴🏼	prince: medium-light skin tone
+🤴🏽	prince: medium skin tone
+🤴🏾	prince: medium-dark skin tone
+🤴🏿	prince: dark skin tone
+👸	princess
+👸🏻	princess: light skin tone
+👸🏼	princess: medium-light skin tone
+👸🏽	princess: medium skin tone
+👸🏾	princess: medium-dark skin tone
+👸🏿	princess: dark skin tone
+👳	person wearing turban
+👳🏻	person wearing turban: light skin tone
+👳🏼	person wearing turban: medium-light skin tone
+👳🏽	person wearing turban: medium skin tone
+👳🏾	person wearing turban: medium-dark skin tone
+👳🏿	person wearing turban: dark skin tone
+👳‍♂️	man wearing turban
+👳‍♂	man wearing turban
+👳🏻‍♂️	man wearing turban: light skin tone
+👳🏻‍♂	man wearing turban: light skin tone
+👳🏼‍♂️	man wearing turban: medium-light skin tone
+👳🏼‍♂	man wearing turban: medium-light skin tone
+👳🏽‍♂️	man wearing turban: medium skin tone
+👳🏽‍♂	man wearing turban: medium skin tone
+👳🏾‍♂️	man wearing turban: medium-dark skin tone
+👳🏾‍♂	man wearing turban: medium-dark skin tone
+👳🏿‍♂️	man wearing turban: dark skin tone
+👳🏿‍♂	man wearing turban: dark skin tone
+👳‍♀️	woman wearing turban
+👳‍♀	woman wearing turban
+👳🏻‍♀️	woman wearing turban: light skin tone
+👳🏻‍♀	woman wearing turban: light skin tone
+👳🏼‍♀️	woman wearing turban: medium-light skin tone
+👳🏼‍♀	woman wearing turban: medium-light skin tone
+👳🏽‍♀️	woman wearing turban: medium skin tone
+👳🏽‍♀	woman wearing turban: medium skin tone
+👳🏾‍♀️	woman wearing turban: medium-dark skin tone
+👳🏾‍♀	woman wearing turban: medium-dark skin tone
+👳🏿‍♀️	woman wearing turban: dark skin tone
+👳🏿‍♀	woman wearing turban: dark skin tone
+👲	man with Chinese cap
+👲🏻	man with Chinese cap: light skin tone
+👲🏼	man with Chinese cap: medium-light skin tone
+👲🏽	man with Chinese cap: medium skin tone
+👲🏾	man with Chinese cap: medium-dark skin tone
+👲🏿	man with Chinese cap: dark skin tone
+🧕	woman with headscarf
+🧕🏻	woman with headscarf: light skin tone
+🧕🏼	woman with headscarf: medium-light skin tone
+🧕🏽	woman with headscarf: medium skin tone
+🧕🏾	woman with headscarf: medium-dark skin tone
+🧕🏿	woman with headscarf: dark skin tone
+🧔	bearded person
+🧔🏻	bearded person: light skin tone
+🧔🏼	bearded person: medium-light skin tone
+🧔🏽	bearded person: medium skin tone
+🧔🏾	bearded person: medium-dark skin tone
+🧔🏿	bearded person: dark skin tone
+👱	blond-haired person
+👱🏻	blond-haired person: light skin tone
+👱🏼	blond-haired person: medium-light skin tone
+👱🏽	blond-haired person: medium skin tone
+👱🏾	blond-haired person: medium-dark skin tone
+👱🏿	blond-haired person: dark skin tone
+👱‍♂️	blond-haired man
+👱‍♂	blond-haired man
+👱🏻‍♂️	blond-haired man: light skin tone
+👱🏻‍♂	blond-haired man: light skin tone
+👱🏼‍♂️	blond-haired man: medium-light skin tone
+👱🏼‍♂	blond-haired man: medium-light skin tone
+👱🏽‍♂️	blond-haired man: medium skin tone
+👱🏽‍♂	blond-haired man: medium skin tone
+👱🏾‍♂️	blond-haired man: medium-dark skin tone
+👱🏾‍♂	blond-haired man: medium-dark skin tone
+👱🏿‍♂️	blond-haired man: dark skin tone
+👱🏿‍♂	blond-haired man: dark skin tone
+👱‍♀️	blond-haired woman
+👱‍♀	blond-haired woman
+👱🏻‍♀️	blond-haired woman: light skin tone
+👱🏻‍♀	blond-haired woman: light skin tone
+👱🏼‍♀️	blond-haired woman: medium-light skin tone
+👱🏼‍♀	blond-haired woman: medium-light skin tone
+👱🏽‍♀️	blond-haired woman: medium skin tone
+👱🏽‍♀	blond-haired woman: medium skin tone
+👱🏾‍♀️	blond-haired woman: medium-dark skin tone
+👱🏾‍♀	blond-haired woman: medium-dark skin tone
+👱🏿‍♀️	blond-haired woman: dark skin tone
+👱🏿‍♀	blond-haired woman: dark skin tone
+👨‍🦰	man, red haired
+👨🏻‍🦰	man, red haired: light skin tone
+👨🏼‍🦰	man, red haired: medium-light skin tone
+👨🏽‍🦰	man, red haired: medium skin tone
+👨🏾‍🦰	man, red haired: medium-dark skin tone
+👨🏿‍🦰	man, red haired: dark skin tone
+👩‍🦰	woman, red haired
+👩🏻‍🦰	woman, red haired: light skin tone
+👩🏼‍🦰	woman, red haired: medium-light skin tone
+👩🏽‍🦰	woman, red haired: medium skin tone
+👩🏾‍🦰	woman, red haired: medium-dark skin tone
+👩🏿‍🦰	woman, red haired: dark skin tone
+👨‍🦱	man, curly haired
+👨🏻‍🦱	man, curly haired: light skin tone
+👨🏼‍🦱	man, curly haired: medium-light skin tone
+👨🏽‍🦱	man, curly haired: medium skin tone
+👨🏾‍🦱	man, curly haired: medium-dark skin tone
+👨🏿‍🦱	man, curly haired: dark skin tone
+👩‍🦱	woman, curly haired
+👩🏻‍🦱	woman, curly haired: light skin tone
+👩🏼‍🦱	woman, curly haired: medium-light skin tone
+👩🏽‍🦱	woman, curly haired: medium skin tone
+👩🏾‍🦱	woman, curly haired: medium-dark skin tone
+👩🏿‍🦱	woman, curly haired: dark skin tone
+👨‍🦲	man, bald
+👨🏻‍🦲	man, bald: light skin tone
+👨🏼‍🦲	man, bald: medium-light skin tone
+👨🏽‍🦲	man, bald: medium skin tone
+👨🏾‍🦲	man, bald: medium-dark skin tone
+👨🏿‍🦲	man, bald: dark skin tone
+👩‍🦲	woman, bald
+👩🏻‍🦲	woman, bald: light skin tone
+👩🏼‍🦲	woman, bald: medium-light skin tone
+👩🏽‍🦲	woman, bald: medium skin tone
+👩🏾‍🦲	woman, bald: medium-dark skin tone
+👩🏿‍🦲	woman, bald: dark skin tone
+👨‍🦳	man, white haired
+👨🏻‍🦳	man, white haired: light skin tone
+👨🏼‍🦳	man, white haired: medium-light skin tone
+👨🏽‍🦳	man, white haired: medium skin tone
+👨🏾‍🦳	man, white haired: medium-dark skin tone
+👨🏿‍🦳	man, white haired: dark skin tone
+👩‍🦳	woman, white haired
+👩🏻‍🦳	woman, white haired: light skin tone
+👩🏼‍🦳	woman, white haired: medium-light skin tone
+👩🏽‍🦳	woman, white haired: medium skin tone
+👩🏾‍🦳	woman, white haired: medium-dark skin tone
+👩🏿‍🦳	woman, white haired: dark skin tone
+🤵	man in tuxedo
+🤵🏻	man in tuxedo: light skin tone
+🤵🏼	man in tuxedo: medium-light skin tone
+🤵🏽	man in tuxedo: medium skin tone
+🤵🏾	man in tuxedo: medium-dark skin tone
+🤵🏿	man in tuxedo: dark skin tone
+👰	bride with veil
+👰🏻	bride with veil: light skin tone
+👰🏼	bride with veil: medium-light skin tone
+👰🏽	bride with veil: medium skin tone
+👰🏾	bride with veil: medium-dark skin tone
+👰🏿	bride with veil: dark skin tone
+🤰	pregnant woman
+🤰🏻	pregnant woman: light skin tone
+🤰🏼	pregnant woman: medium-light skin tone
+🤰🏽	pregnant woman: medium skin tone
+🤰🏾	pregnant woman: medium-dark skin tone
+🤰🏿	pregnant woman: dark skin tone
+🤱	breast-feeding
+🤱🏻	breast-feeding: light skin tone
+🤱🏼	breast-feeding: medium-light skin tone
+🤱🏽	breast-feeding: medium skin tone
+🤱🏾	breast-feeding: medium-dark skin tone
+🤱🏿	breast-feeding: dark skin tone
+👼	baby angel
+👼🏻	baby angel: light skin tone
+👼🏼	baby angel: medium-light skin tone
+👼🏽	baby angel: medium skin tone
+👼🏾	baby angel: medium-dark skin tone
+👼🏿	baby angel: dark skin tone
+🎅	Santa Claus
+🎅🏻	Santa Claus: light skin tone
+🎅🏼	Santa Claus: medium-light skin tone
+🎅🏽	Santa Claus: medium skin tone
+🎅🏾	Santa Claus: medium-dark skin tone
+🎅🏿	Santa Claus: dark skin tone
+🤶	Mrs. Claus
+🤶🏻	Mrs. Claus: light skin tone
+🤶🏼	Mrs. Claus: medium-light skin tone
+🤶🏽	Mrs. Claus: medium skin tone
+🤶🏾	Mrs. Claus: medium-dark skin tone
+🤶🏿	Mrs. Claus: dark skin tone
+🦸	superhero
+🦸🏻	superhero: light skin tone
+🦸🏼	superhero: medium-light skin tone
+🦸🏽	superhero: medium skin tone
+🦸🏾	superhero: medium-dark skin tone
+🦸🏿	superhero: dark skin tone
+🦸‍♀️	woman superhero
+🦸‍♀	woman superhero
+🦸🏻‍♀️	woman superhero: light skin tone
+🦸🏻‍♀	woman superhero: light skin tone
+🦸🏼‍♀️	woman superhero: medium-light skin tone
+🦸🏼‍♀	woman superhero: medium-light skin tone
+🦸🏽‍♀️	woman superhero: medium skin tone
+🦸🏽‍♀	woman superhero: medium skin tone
+🦸🏾‍♀️	woman superhero: medium-dark skin tone
+🦸🏾‍♀	woman superhero: medium-dark skin tone
+🦸🏿‍♀️	woman superhero: dark skin tone
+🦸🏿‍♀	woman superhero: dark skin tone
+🦸‍♂️	man superhero
+🦸‍♂	man superhero
+🦸🏻‍♂️	man superhero: light skin tone
+🦸🏻‍♂	man superhero: light skin tone
+🦸🏼‍♂️	man superhero: medium-light skin tone
+🦸🏼‍♂	man superhero: medium-light skin tone
+🦸🏽‍♂️	man superhero: medium skin tone
+🦸🏽‍♂	man superhero: medium skin tone
+🦸🏾‍♂️	man superhero: medium-dark skin tone
+🦸🏾‍♂	man superhero: medium-dark skin tone
+🦸🏿‍♂️	man superhero: dark skin tone
+🦸🏿‍♂	man superhero: dark skin tone
+🦹	supervillain
+🦹🏻	supervillain: light skin tone
+🦹🏼	supervillain: medium-light skin tone
+🦹🏽	supervillain: medium skin tone
+🦹🏾	supervillain: medium-dark skin tone
+🦹🏿	supervillain: dark skin tone
+🦹‍♀️	woman supervillain
+🦹‍♀	woman supervillain
+🦹🏻‍♀️	woman supervillain: light skin tone
+🦹🏻‍♀	woman supervillain: light skin tone
+🦹🏼‍♀️	woman supervillain: medium-light skin tone
+🦹🏼‍♀	woman supervillain: medium-light skin tone
+🦹🏽‍♀️	woman supervillain: medium skin tone
+🦹🏽‍♀	woman supervillain: medium skin tone
+🦹🏾‍♀️	woman supervillain: medium-dark skin tone
+🦹🏾‍♀	woman supervillain: medium-dark skin tone
+🦹🏿‍♀️	woman supervillain: dark skin tone
+🦹🏿‍♀	woman supervillain: dark skin tone
+🦹‍♂️	man supervillain
+🦹‍♂	man supervillain
+🦹🏻‍♂️	man supervillain: light skin tone
+🦹🏻‍♂	man supervillain: light skin tone
+🦹🏼‍♂️	man supervillain: medium-light skin tone
+🦹🏼‍♂	man supervillain: medium-light skin tone
+🦹🏽‍♂️	man supervillain: medium skin tone
+🦹🏽‍♂	man supervillain: medium skin tone
+🦹🏾‍♂️	man supervillain: medium-dark skin tone
+🦹🏾‍♂	man supervillain: medium-dark skin tone
+🦹🏿‍♂️	man supervillain: dark skin tone
+🦹🏿‍♂	man supervillain: dark skin tone
+🧙	mage
+🧙🏻	mage: light skin tone
+🧙🏼	mage: medium-light skin tone
+🧙🏽	mage: medium skin tone
+🧙🏾	mage: medium-dark skin tone
+🧙🏿	mage: dark skin tone
+🧙‍♀️	woman mage
+🧙‍♀	woman mage
+🧙🏻‍♀️	woman mage: light skin tone
+🧙🏻‍♀	woman mage: light skin tone
+🧙🏼‍♀️	woman mage: medium-light skin tone
+🧙🏼‍♀	woman mage: medium-light skin tone
+🧙🏽‍♀️	woman mage: medium skin tone
+🧙🏽‍♀	woman mage: medium skin tone
+🧙🏾‍♀️	woman mage: medium-dark skin tone
+🧙🏾‍♀	woman mage: medium-dark skin tone
+🧙🏿‍♀️	woman mage: dark skin tone
+🧙🏿‍♀	woman mage: dark skin tone
+🧙‍♂️	man mage
+🧙‍♂	man mage
+🧙🏻‍♂️	man mage: light skin tone
+🧙🏻‍♂	man mage: light skin tone
+🧙🏼‍♂️	man mage: medium-light skin tone
+🧙🏼‍♂	man mage: medium-light skin tone
+🧙🏽‍♂️	man mage: medium skin tone
+🧙🏽‍♂	man mage: medium skin tone
+🧙🏾‍♂️	man mage: medium-dark skin tone
+🧙🏾‍♂	man mage: medium-dark skin tone
+🧙🏿‍♂️	man mage: dark skin tone
+🧙🏿‍♂	man mage: dark skin tone
+🧚	fairy
+🧚🏻	fairy: light skin tone
+🧚🏼	fairy: medium-light skin tone
+🧚🏽	fairy: medium skin tone
+🧚🏾	fairy: medium-dark skin tone
+🧚🏿	fairy: dark skin tone
+🧚‍♀️	woman fairy
+🧚‍♀	woman fairy
+🧚🏻‍♀️	woman fairy: light skin tone
+🧚🏻‍♀	woman fairy: light skin tone
+🧚🏼‍♀️	woman fairy: medium-light skin tone
+🧚🏼‍♀	woman fairy: medium-light skin tone
+🧚🏽‍♀️	woman fairy: medium skin tone
+🧚🏽‍♀	woman fairy: medium skin tone
+🧚🏾‍♀️	woman fairy: medium-dark skin tone
+🧚🏾‍♀	woman fairy: medium-dark skin tone
+🧚🏿‍♀️	woman fairy: dark skin tone
+🧚🏿‍♀	woman fairy: dark skin tone
+🧚‍♂️	man fairy
+🧚‍♂	man fairy
+🧚🏻‍♂️	man fairy: light skin tone
+🧚🏻‍♂	man fairy: light skin tone
+🧚🏼‍♂️	man fairy: medium-light skin tone
+🧚🏼‍♂	man fairy: medium-light skin tone
+🧚🏽‍♂️	man fairy: medium skin tone
+🧚🏽‍♂	man fairy: medium skin tone
+🧚🏾‍♂️	man fairy: medium-dark skin tone
+🧚🏾‍♂	man fairy: medium-dark skin tone
+🧚🏿‍♂️	man fairy: dark skin tone
+🧚🏿‍♂	man fairy: dark skin tone
+🧛	vampire
+🧛🏻	vampire: light skin tone
+🧛🏼	vampire: medium-light skin tone
+🧛🏽	vampire: medium skin tone
+🧛🏾	vampire: medium-dark skin tone
+🧛🏿	vampire: dark skin tone
+🧛‍♀️	woman vampire
+🧛‍♀	woman vampire
+🧛🏻‍♀️	woman vampire: light skin tone
+🧛🏻‍♀	woman vampire: light skin tone
+🧛🏼‍♀️	woman vampire: medium-light skin tone
+🧛🏼‍♀	woman vampire: medium-light skin tone
+🧛🏽‍♀️	woman vampire: medium skin tone
+🧛🏽‍♀	woman vampire: medium skin tone
+🧛🏾‍♀️	woman vampire: medium-dark skin tone
+🧛🏾‍♀	woman vampire: medium-dark skin tone
+🧛🏿‍♀️	woman vampire: dark skin tone
+🧛🏿‍♀	woman vampire: dark skin tone
+🧛‍♂️	man vampire
+🧛‍♂	man vampire
+🧛🏻‍♂️	man vampire: light skin tone
+🧛🏻‍♂	man vampire: light skin tone
+🧛🏼‍♂️	man vampire: medium-light skin tone
+🧛🏼‍♂	man vampire: medium-light skin tone
+🧛🏽‍♂️	man vampire: medium skin tone
+🧛🏽‍♂	man vampire: medium skin tone
+🧛🏾‍♂️	man vampire: medium-dark skin tone
+🧛🏾‍♂	man vampire: medium-dark skin tone
+🧛🏿‍♂️	man vampire: dark skin tone
+🧛🏿‍♂	man vampire: dark skin tone
+🧜	merperson
+🧜🏻	merperson: light skin tone
+🧜🏼	merperson: medium-light skin tone
+🧜🏽	merperson: medium skin tone
+🧜🏾	merperson: medium-dark skin tone
+🧜🏿	merperson: dark skin tone
+🧜‍♀️	mermaid
+🧜‍♀	mermaid
+🧜🏻‍♀️	mermaid: light skin tone
+🧜🏻‍♀	mermaid: light skin tone
+🧜🏼‍♀️	mermaid: medium-light skin tone
+🧜🏼‍♀	mermaid: medium-light skin tone
+🧜🏽‍♀️	mermaid: medium skin tone
+🧜🏽‍♀	mermaid: medium skin tone
+🧜🏾‍♀️	mermaid: medium-dark skin tone
+🧜🏾‍♀	mermaid: medium-dark skin tone
+🧜🏿‍♀️	mermaid: dark skin tone
+🧜🏿‍♀	mermaid: dark skin tone
+🧜‍♂️	merman
+🧜‍♂	merman
+🧜🏻‍♂️	merman: light skin tone
+🧜🏻‍♂	merman: light skin tone
+🧜🏼‍♂️	merman: medium-light skin tone
+🧜🏼‍♂	merman: medium-light skin tone
+🧜🏽‍♂️	merman: medium skin tone
+🧜🏽‍♂	merman: medium skin tone
+🧜🏾‍♂️	merman: medium-dark skin tone
+🧜🏾‍♂	merman: medium-dark skin tone
+🧜🏿‍♂️	merman: dark skin tone
+🧜🏿‍♂	merman: dark skin tone
+🧝	elf
+🧝🏻	elf: light skin tone
+🧝🏼	elf: medium-light skin tone
+🧝🏽	elf: medium skin tone
+🧝🏾	elf: medium-dark skin tone
+🧝🏿	elf: dark skin tone
+🧝‍♀️	woman elf
+🧝‍♀	woman elf
+🧝🏻‍♀️	woman elf: light skin tone
+🧝🏻‍♀	woman elf: light skin tone
+🧝🏼‍♀️	woman elf: medium-light skin tone
+🧝🏼‍♀	woman elf: medium-light skin tone
+🧝🏽‍♀️	woman elf: medium skin tone
+🧝🏽‍♀	woman elf: medium skin tone
+🧝🏾‍♀️	woman elf: medium-dark skin tone
+🧝🏾‍♀	woman elf: medium-dark skin tone
+🧝🏿‍♀️	woman elf: dark skin tone
+🧝🏿‍♀	woman elf: dark skin tone
+🧝‍♂️	man elf
+🧝‍♂	man elf
+🧝🏻‍♂️	man elf: light skin tone
+🧝🏻‍♂	man elf: light skin tone
+🧝🏼‍♂️	man elf: medium-light skin tone
+🧝🏼‍♂	man elf: medium-light skin tone
+🧝🏽‍♂️	man elf: medium skin tone
+🧝🏽‍♂	man elf: medium skin tone
+🧝🏾‍♂️	man elf: medium-dark skin tone
+🧝🏾‍♂	man elf: medium-dark skin tone
+🧝🏿‍♂️	man elf: dark skin tone
+🧝🏿‍♂	man elf: dark skin tone
+🧞	genie
+🧞‍♀️	woman genie
+🧞‍♀	woman genie
+🧞‍♂️	man genie
+🧞‍♂	man genie
+🧟	zombie
+🧟‍♀️	woman zombie
+🧟‍♀	woman zombie
+🧟‍♂️	man zombie
+🧟‍♂	man zombie
+🙍	person frowning
+🙍🏻	person frowning: light skin tone
+🙍🏼	person frowning: medium-light skin tone
+🙍🏽	person frowning: medium skin tone
+🙍🏾	person frowning: medium-dark skin tone
+🙍🏿	person frowning: dark skin tone
+🙍‍♂️	man frowning
+🙍‍♂	man frowning
+🙍🏻‍♂️	man frowning: light skin tone
+🙍🏻‍♂	man frowning: light skin tone
+🙍🏼‍♂️	man frowning: medium-light skin tone
+🙍🏼‍♂	man frowning: medium-light skin tone
+🙍🏽‍♂️	man frowning: medium skin tone
+🙍🏽‍♂	man frowning: medium skin tone
+🙍🏾‍♂️	man frowning: medium-dark skin tone
+🙍🏾‍♂	man frowning: medium-dark skin tone
+🙍🏿‍♂️	man frowning: dark skin tone
+🙍🏿‍♂	man frowning: dark skin tone
+🙍‍♀️	woman frowning
+🙍‍♀	woman frowning
+🙍🏻‍♀️	woman frowning: light skin tone
+🙍🏻‍♀	woman frowning: light skin tone
+🙍🏼‍♀️	woman frowning: medium-light skin tone
+🙍🏼‍♀	woman frowning: medium-light skin tone
+🙍🏽‍♀️	woman frowning: medium skin tone
+🙍🏽‍♀	woman frowning: medium skin tone
+🙍🏾‍♀️	woman frowning: medium-dark skin tone
+🙍🏾‍♀	woman frowning: medium-dark skin tone
+🙍🏿‍♀️	woman frowning: dark skin tone
+🙍🏿‍♀	woman frowning: dark skin tone
+🙎	person pouting
+🙎🏻	person pouting: light skin tone
+🙎🏼	person pouting: medium-light skin tone
+🙎🏽	person pouting: medium skin tone
+🙎🏾	person pouting: medium-dark skin tone
+🙎🏿	person pouting: dark skin tone
+🙎‍♂️	man pouting
+🙎‍♂	man pouting
+🙎🏻‍♂️	man pouting: light skin tone
+🙎🏻‍♂	man pouting: light skin tone
+🙎🏼‍♂️	man pouting: medium-light skin tone
+🙎🏼‍♂	man pouting: medium-light skin tone
+🙎🏽‍♂️	man pouting: medium skin tone
+🙎🏽‍♂	man pouting: medium skin tone
+🙎🏾‍♂️	man pouting: medium-dark skin tone
+🙎🏾‍♂	man pouting: medium-dark skin tone
+🙎🏿‍♂️	man pouting: dark skin tone
+🙎🏿‍♂	man pouting: dark skin tone
+🙎‍♀️	woman pouting
+🙎‍♀	woman pouting
+🙎🏻‍♀️	woman pouting: light skin tone
+🙎🏻‍♀	woman pouting: light skin tone
+🙎🏼‍♀️	woman pouting: medium-light skin tone
+🙎🏼‍♀	woman pouting: medium-light skin tone
+🙎🏽‍♀️	woman pouting: medium skin tone
+🙎🏽‍♀	woman pouting: medium skin tone
+🙎🏾‍♀️	woman pouting: medium-dark skin tone
+🙎🏾‍♀	woman pouting: medium-dark skin tone
+🙎🏿‍♀️	woman pouting: dark skin tone
+🙎🏿‍♀	woman pouting: dark skin tone
+🙅	person gesturing NO
+🙅🏻	person gesturing NO: light skin tone
+🙅🏼	person gesturing NO: medium-light skin tone
+🙅🏽	person gesturing NO: medium skin tone
+🙅🏾	person gesturing NO: medium-dark skin tone
+🙅🏿	person gesturing NO: dark skin tone
+🙅‍♂️	man gesturing NO
+🙅‍♂	man gesturing NO
+🙅🏻‍♂️	man gesturing NO: light skin tone
+🙅🏻‍♂	man gesturing NO: light skin tone
+🙅🏼‍♂️	man gesturing NO: medium-light skin tone
+🙅🏼‍♂	man gesturing NO: medium-light skin tone
+🙅🏽‍♂️	man gesturing NO: medium skin tone
+🙅🏽‍♂	man gesturing NO: medium skin tone
+🙅🏾‍♂️	man gesturing NO: medium-dark skin tone
+🙅🏾‍♂	man gesturing NO: medium-dark skin tone
+🙅🏿‍♂️	man gesturing NO: dark skin tone
+🙅🏿‍♂	man gesturing NO: dark skin tone
+🙅‍♀️	woman gesturing NO
+🙅‍♀	woman gesturing NO
+🙅🏻‍♀️	woman gesturing NO: light skin tone
+🙅🏻‍♀	woman gesturing NO: light skin tone
+🙅🏼‍♀️	woman gesturing NO: medium-light skin tone
+🙅🏼‍♀	woman gesturing NO: medium-light skin tone
+🙅🏽‍♀️	woman gesturing NO: medium skin tone
+🙅🏽‍♀	woman gesturing NO: medium skin tone
+🙅🏾‍♀️	woman gesturing NO: medium-dark skin tone
+🙅🏾‍♀	woman gesturing NO: medium-dark skin tone
+🙅🏿‍♀️	woman gesturing NO: dark skin tone
+🙅🏿‍♀	woman gesturing NO: dark skin tone
+🙆	person gesturing OK
+🙆🏻	person gesturing OK: light skin tone
+🙆🏼	person gesturing OK: medium-light skin tone
+🙆🏽	person gesturing OK: medium skin tone
+🙆🏾	person gesturing OK: medium-dark skin tone
+🙆🏿	person gesturing OK: dark skin tone
+🙆‍♂️	man gesturing OK
+🙆‍♂	man gesturing OK
+🙆🏻‍♂️	man gesturing OK: light skin tone
+🙆🏻‍♂	man gesturing OK: light skin tone
+🙆🏼‍♂️	man gesturing OK: medium-light skin tone
+🙆🏼‍♂	man gesturing OK: medium-light skin tone
+🙆🏽‍♂️	man gesturing OK: medium skin tone
+🙆🏽‍♂	man gesturing OK: medium skin tone
+🙆🏾‍♂️	man gesturing OK: medium-dark skin tone
+🙆🏾‍♂	man gesturing OK: medium-dark skin tone
+🙆🏿‍♂️	man gesturing OK: dark skin tone
+🙆🏿‍♂	man gesturing OK: dark skin tone
+🙆‍♀️	woman gesturing OK
+🙆‍♀	woman gesturing OK
+🙆🏻‍♀️	woman gesturing OK: light skin tone
+🙆🏻‍♀	woman gesturing OK: light skin tone
+🙆🏼‍♀️	woman gesturing OK: medium-light skin tone
+🙆🏼‍♀	woman gesturing OK: medium-light skin tone
+🙆🏽‍♀️	woman gesturing OK: medium skin tone
+🙆🏽‍♀	woman gesturing OK: medium skin tone
+🙆🏾‍♀️	woman gesturing OK: medium-dark skin tone
+🙆🏾‍♀	woman gesturing OK: medium-dark skin tone
+🙆🏿‍♀️	woman gesturing OK: dark skin tone
+🙆🏿‍♀	woman gesturing OK: dark skin tone
+💁	person tipping hand
+💁🏻	person tipping hand: light skin tone
+💁🏼	person tipping hand: medium-light skin tone
+💁🏽	person tipping hand: medium skin tone
+💁🏾	person tipping hand: medium-dark skin tone
+💁🏿	person tipping hand: dark skin tone
+💁‍♂️	man tipping hand
+💁‍♂	man tipping hand
+💁🏻‍♂️	man tipping hand: light skin tone
+💁🏻‍♂	man tipping hand: light skin tone
+💁🏼‍♂️	man tipping hand: medium-light skin tone
+💁🏼‍♂	man tipping hand: medium-light skin tone
+💁🏽‍♂️	man tipping hand: medium skin tone
+💁🏽‍♂	man tipping hand: medium skin tone
+💁🏾‍♂️	man tipping hand: medium-dark skin tone
+💁🏾‍♂	man tipping hand: medium-dark skin tone
+💁🏿‍♂️	man tipping hand: dark skin tone
+💁🏿‍♂	man tipping hand: dark skin tone
+💁‍♀️	woman tipping hand
+💁‍♀	woman tipping hand
+💁🏻‍♀️	woman tipping hand: light skin tone
+💁🏻‍♀	woman tipping hand: light skin tone
+💁🏼‍♀️	woman tipping hand: medium-light skin tone
+💁🏼‍♀	woman tipping hand: medium-light skin tone
+💁🏽‍♀️	woman tipping hand: medium skin tone
+💁🏽‍♀	woman tipping hand: medium skin tone
+💁🏾‍♀️	woman tipping hand: medium-dark skin tone
+💁🏾‍♀	woman tipping hand: medium-dark skin tone
+💁🏿‍♀️	woman tipping hand: dark skin tone
+💁🏿‍♀	woman tipping hand: dark skin tone
+🙋	person raising hand
+🙋🏻	person raising hand: light skin tone
+🙋🏼	person raising hand: medium-light skin tone
+🙋🏽	person raising hand: medium skin tone
+🙋🏾	person raising hand: medium-dark skin tone
+🙋🏿	person raising hand: dark skin tone
+🙋‍♂️	man raising hand
+🙋‍♂	man raising hand
+🙋🏻‍♂️	man raising hand: light skin tone
+🙋🏻‍♂	man raising hand: light skin tone
+🙋🏼‍♂️	man raising hand: medium-light skin tone
+🙋🏼‍♂	man raising hand: medium-light skin tone
+🙋🏽‍♂️	man raising hand: medium skin tone
+🙋🏽‍♂	man raising hand: medium skin tone
+🙋🏾‍♂️	man raising hand: medium-dark skin tone
+🙋🏾‍♂	man raising hand: medium-dark skin tone
+🙋🏿‍♂️	man raising hand: dark skin tone
+🙋🏿‍♂	man raising hand: dark skin tone
+🙋‍♀️	woman raising hand
+🙋‍♀	woman raising hand
+🙋🏻‍♀️	woman raising hand: light skin tone
+🙋🏻‍♀	woman raising hand: light skin tone
+🙋🏼‍♀️	woman raising hand: medium-light skin tone
+🙋🏼‍♀	woman raising hand: medium-light skin tone
+🙋🏽‍♀️	woman raising hand: medium skin tone
+🙋🏽‍♀	woman raising hand: medium skin tone
+🙋🏾‍♀️	woman raising hand: medium-dark skin tone
+🙋🏾‍♀	woman raising hand: medium-dark skin tone
+🙋🏿‍♀️	woman raising hand: dark skin tone
+🙋🏿‍♀	woman raising hand: dark skin tone
+🙇	person bowing
+🙇🏻	person bowing: light skin tone
+🙇🏼	person bowing: medium-light skin tone
+🙇🏽	person bowing: medium skin tone
+🙇🏾	person bowing: medium-dark skin tone
+🙇🏿	person bowing: dark skin tone
+🙇‍♂️	man bowing
+🙇‍♂	man bowing
+🙇🏻‍♂️	man bowing: light skin tone
+🙇🏻‍♂	man bowing: light skin tone
+🙇🏼‍♂️	man bowing: medium-light skin tone
+🙇🏼‍♂	man bowing: medium-light skin tone
+🙇🏽‍♂️	man bowing: medium skin tone
+🙇🏽‍♂	man bowing: medium skin tone
+🙇🏾‍♂️	man bowing: medium-dark skin tone
+🙇🏾‍♂	man bowing: medium-dark skin tone
+🙇🏿‍♂️	man bowing: dark skin tone
+🙇🏿‍♂	man bowing: dark skin tone
+🙇‍♀️	woman bowing
+🙇‍♀	woman bowing
+🙇🏻‍♀️	woman bowing: light skin tone
+🙇🏻‍♀	woman bowing: light skin tone
+🙇🏼‍♀️	woman bowing: medium-light skin tone
+🙇🏼‍♀	woman bowing: medium-light skin tone
+🙇🏽‍♀️	woman bowing: medium skin tone
+🙇🏽‍♀	woman bowing: medium skin tone
+🙇🏾‍♀️	woman bowing: medium-dark skin tone
+🙇🏾‍♀	woman bowing: medium-dark skin tone
+🙇🏿‍♀️	woman bowing: dark skin tone
+🙇🏿‍♀	woman bowing: dark skin tone
+🤦	person facepalming
+🤦🏻	person facepalming: light skin tone
+🤦🏼	person facepalming: medium-light skin tone
+🤦🏽	person facepalming: medium skin tone
+🤦🏾	person facepalming: medium-dark skin tone
+🤦🏿	person facepalming: dark skin tone
+🤦‍♂️	man facepalming
+🤦‍♂	man facepalming
+🤦🏻‍♂️	man facepalming: light skin tone
+🤦🏻‍♂	man facepalming: light skin tone
+🤦🏼‍♂️	man facepalming: medium-light skin tone
+🤦🏼‍♂	man facepalming: medium-light skin tone
+🤦🏽‍♂️	man facepalming: medium skin tone
+🤦🏽‍♂	man facepalming: medium skin tone
+🤦🏾‍♂️	man facepalming: medium-dark skin tone
+🤦🏾‍♂	man facepalming: medium-dark skin tone
+🤦🏿‍♂️	man facepalming: dark skin tone
+🤦🏿‍♂	man facepalming: dark skin tone
+🤦‍♀️	woman facepalming
+🤦‍♀	woman facepalming
+🤦🏻‍♀️	woman facepalming: light skin tone
+🤦🏻‍♀	woman facepalming: light skin tone
+🤦🏼‍♀️	woman facepalming: medium-light skin tone
+🤦🏼‍♀	woman facepalming: medium-light skin tone
+🤦🏽‍♀️	woman facepalming: medium skin tone
+🤦🏽‍♀	woman facepalming: medium skin tone
+🤦🏾‍♀️	woman facepalming: medium-dark skin tone
+🤦🏾‍♀	woman facepalming: medium-dark skin tone
+🤦🏿‍♀️	woman facepalming: dark skin tone
+🤦🏿‍♀	woman facepalming: dark skin tone
+🤷	person shrugging
+🤷🏻	person shrugging: light skin tone
+🤷🏼	person shrugging: medium-light skin tone
+🤷🏽	person shrugging: medium skin tone
+🤷🏾	person shrugging: medium-dark skin tone
+🤷🏿	person shrugging: dark skin tone
+🤷‍♂️	man shrugging
+🤷‍♂	man shrugging
+🤷🏻‍♂️	man shrugging: light skin tone
+🤷🏻‍♂	man shrugging: light skin tone
+🤷🏼‍♂️	man shrugging: medium-light skin tone
+🤷🏼‍♂	man shrugging: medium-light skin tone
+🤷🏽‍♂️	man shrugging: medium skin tone
+🤷🏽‍♂	man shrugging: medium skin tone
+🤷🏾‍♂️	man shrugging: medium-dark skin tone
+🤷🏾‍♂	man shrugging: medium-dark skin tone
+🤷🏿‍♂️	man shrugging: dark skin tone
+🤷🏿‍♂	man shrugging: dark skin tone
+🤷‍♀️	woman shrugging
+🤷‍♀	woman shrugging
+🤷🏻‍♀️	woman shrugging: light skin tone
+🤷🏻‍♀	woman shrugging: light skin tone
+🤷🏼‍♀️	woman shrugging: medium-light skin tone
+🤷🏼‍♀	woman shrugging: medium-light skin tone
+🤷🏽‍♀️	woman shrugging: medium skin tone
+🤷🏽‍♀	woman shrugging: medium skin tone
+🤷🏾‍♀️	woman shrugging: medium-dark skin tone
+🤷🏾‍♀	woman shrugging: medium-dark skin tone
+🤷🏿‍♀️	woman shrugging: dark skin tone
+🤷🏿‍♀	woman shrugging: dark skin tone
+💆	person getting massage
+💆🏻	person getting massage: light skin tone
+💆🏼	person getting massage: medium-light skin tone
+💆🏽	person getting massage: medium skin tone
+💆🏾	person getting massage: medium-dark skin tone
+💆🏿	person getting massage: dark skin tone
+💆‍♂️	man getting massage
+💆‍♂	man getting massage
+💆🏻‍♂️	man getting massage: light skin tone
+💆🏻‍♂	man getting massage: light skin tone
+💆🏼‍♂️	man getting massage: medium-light skin tone
+💆🏼‍♂	man getting massage: medium-light skin tone
+💆🏽‍♂️	man getting massage: medium skin tone
+💆🏽‍♂	man getting massage: medium skin tone
+💆🏾‍♂️	man getting massage: medium-dark skin tone
+💆🏾‍♂	man getting massage: medium-dark skin tone
+💆🏿‍♂️	man getting massage: dark skin tone
+💆🏿‍♂	man getting massage: dark skin tone
+💆‍♀️	woman getting massage
+💆‍♀	woman getting massage
+💆🏻‍♀️	woman getting massage: light skin tone
+💆🏻‍♀	woman getting massage: light skin tone
+💆🏼‍♀️	woman getting massage: medium-light skin tone
+💆🏼‍♀	woman getting massage: medium-light skin tone
+💆🏽‍♀️	woman getting massage: medium skin tone
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+💆🏿‍♀	woman getting massage: dark skin tone
+💇	person getting haircut
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+💇‍♀️	woman getting haircut
+💇‍♀	woman getting haircut
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+💇🏻‍♀	woman getting haircut: light skin tone
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+⛷️	skier
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+🏋️‍♂️	man lifting weights
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+🏋️‍♂	man lifting weights
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+🏋🏿‍♂	man lifting weights: dark skin tone
+🏋️‍♀️	woman lifting weights
+🏋‍♀️	woman lifting weights
+🏋️‍♀	woman lifting weights
+🏋‍♀	woman lifting weights
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+🏋🏿‍♀️	woman lifting weights: dark skin tone
+🏋🏿‍♀	woman lifting weights: dark skin tone
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+🚴‍♀️	woman biking
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+🚵🏿‍♀	woman mountain biking: dark skin tone
+🏎️	racing car
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+🤸‍♀️	woman cartwheeling
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+🤼	people wrestling
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+🤾	person playing handball
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+👫	man and woman holding hands
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+💏	kiss
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+👩‍❤‍💋‍👩	kiss: woman, woman
+💑	couple with heart
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+👩‍❤‍👨	couple with heart: woman, man
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+👩‍❤‍👩	couple with heart: woman, woman
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+👩‍👧‍👦	family: woman, girl, boy
+👩‍👧‍👧	family: woman, girl, girl
+🤳	selfie
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+👈	backhand index pointing left
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+☝️	index pointing up
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+✌️	victory hand
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+🤘	sign of the horns
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+🤙	call me hand
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+🖐️	hand with fingers splayed
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+✋	raised hand
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+👌	OK hand
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+👌🏽	OK hand: medium skin tone
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+👌🏿	OK hand: dark skin tone
+👍	thumbs up
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+👎	thumbs down
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+👊	oncoming fist
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+🤛	left-facing fist
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+🤜🏼	right-facing fist: medium-light skin tone
+🤜🏽	right-facing fist: medium skin tone
+🤜🏾	right-facing fist: medium-dark skin tone
+🤜🏿	right-facing fist: dark skin tone
+🤚	raised back of hand
+🤚🏻	raised back of hand: light skin tone
+🤚🏼	raised back of hand: medium-light skin tone
+🤚🏽	raised back of hand: medium skin tone
+🤚🏾	raised back of hand: medium-dark skin tone
+🤚🏿	raised back of hand: dark skin tone
+👋	waving hand
+👋🏻	waving hand: light skin tone
+👋🏼	waving hand: medium-light skin tone
+👋🏽	waving hand: medium skin tone
+👋🏾	waving hand: medium-dark skin tone
+👋🏿	waving hand: dark skin tone
+🤟	love-you gesture
+🤟🏻	love-you gesture: light skin tone
+🤟🏼	love-you gesture: medium-light skin tone
+🤟🏽	love-you gesture: medium skin tone
+🤟🏾	love-you gesture: medium-dark skin tone
+🤟🏿	love-you gesture: dark skin tone
+✍️	writing hand
+✍	writing hand
+✍🏻	writing hand: light skin tone
+✍🏼	writing hand: medium-light skin tone
+✍🏽	writing hand: medium skin tone
+✍🏾	writing hand: medium-dark skin tone
+✍🏿	writing hand: dark skin tone
+👏	clapping hands
+👏🏻	clapping hands: light skin tone
+👏🏼	clapping hands: medium-light skin tone
+👏🏽	clapping hands: medium skin tone
+👏🏾	clapping hands: medium-dark skin tone
+👏🏿	clapping hands: dark skin tone
+👐	open hands
+👐🏻	open hands: light skin tone
+👐🏼	open hands: medium-light skin tone
+👐🏽	open hands: medium skin tone
+👐🏾	open hands: medium-dark skin tone
+👐🏿	open hands: dark skin tone
+🙌	raising hands
+🙌🏻	raising hands: light skin tone
+🙌🏼	raising hands: medium-light skin tone
+🙌🏽	raising hands: medium skin tone
+🙌🏾	raising hands: medium-dark skin tone
+🙌🏿	raising hands: dark skin tone
+🤲	palms up together
+🤲🏻	palms up together: light skin tone
+🤲🏼	palms up together: medium-light skin tone
+🤲🏽	palms up together: medium skin tone
+🤲🏾	palms up together: medium-dark skin tone
+🤲🏿	palms up together: dark skin tone
+🙏	folded hands
+🙏🏻	folded hands: light skin tone
+🙏🏼	folded hands: medium-light skin tone
+🙏🏽	folded hands: medium skin tone
+🙏🏾	folded hands: medium-dark skin tone
+🙏🏿	folded hands: dark skin tone
+🤝	handshake
+💅	nail polish
+💅🏻	nail polish: light skin tone
+💅🏼	nail polish: medium-light skin tone
+💅🏽	nail polish: medium skin tone
+💅🏾	nail polish: medium-dark skin tone
+💅🏿	nail polish: dark skin tone
+👂	ear
+👂🏻	ear: light skin tone
+👂🏼	ear: medium-light skin tone
+👂🏽	ear: medium skin tone
+👂🏾	ear: medium-dark skin tone
+👂🏿	ear: dark skin tone
+👃	nose
+👃🏻	nose: light skin tone
+👃🏼	nose: medium-light skin tone
+👃🏽	nose: medium skin tone
+👃🏾	nose: medium-dark skin tone
+👃🏿	nose: dark skin tone
+🦰	red-haired
+🦱	curly-haired
+🦲	bald
+🦳	white-haired
+👣	footprints
+👀	eyes
+👁️	eye
+👁	eye
+👁️‍🗨️	eye in speech bubble
+👁‍🗨️	eye in speech bubble
+👁️‍🗨	eye in speech bubble
+👁‍🗨	eye in speech bubble
+🧠	brain
+🦴	bone
+🦷	tooth
+👅	tongue
+👄	mouth
+💋	kiss mark
+💘	heart with arrow
+❤️	red heart
+❤	red heart
+💓	beating heart
+💔	broken heart
+💕	two hearts
+💖	sparkling heart
+💗	growing heart
+💙	blue heart
+💚	green heart
+💛	yellow heart
+🧡	orange heart
+💜	purple heart
+🖤	black heart
+💝	heart with ribbon
+💞	revolving hearts
+💟	heart decoration
+❣️	heavy heart exclamation
+❣	heavy heart exclamation
+💌	love letter
+💤	zzz
+💢	anger symbol
+💣	bomb
+💥	collision
+💦	sweat droplets
+💨	dashing away
+💫	dizzy
+💬	speech balloon
+🗨️	left speech bubble
+🗨	left speech bubble
+🗯️	right anger bubble
+🗯	right anger bubble
+💭	thought balloon
+🕳️	hole
+🕳	hole
+👓	glasses
+🕶️	sunglasses
+🕶	sunglasses
+🥽	goggles
+🥼	lab coat
+👔	necktie
+👕	t-shirt
+👖	jeans
+🧣	scarf
+🧤	gloves
+🧥	coat
+🧦	socks
+👗	dress
+👘	kimono
+👙	bikini
+👚	woman’s clothes
+👛	purse
+👜	handbag
+👝	clutch bag
+🛍️	shopping bags
+🛍	shopping bags
+🎒	school backpack
+👞	man’s shoe
+👟	running shoe
+🥾	hiking boot
+🥿	woman’s flat shoe
+👠	high-heeled shoe
+👡	woman’s sandal
+👢	woman’s boot
+👑	crown
+👒	woman’s hat
+🎩	top hat
+🎓	graduation cap
+🧢	billed cap
+⛑️	rescue worker’s helmet
+⛑	rescue worker’s helmet
+📿	prayer beads
+💄	lipstick
+💍	ring
+💎	gem stone
+🐵	monkey face
+🐒	monkey
+🦍	gorilla
+🐶	dog face
+🐕	dog
+🐩	poodle
+🐺	wolf face
+🦊	fox face
+🦝	raccoon
+🐱	cat face
+🐈	cat
+🦁	lion face
+🐯	tiger face
+🐅	tiger
+🐆	leopard
+🐴	horse face
+🐎	horse
+🦄	unicorn face
+🦓	zebra
+🦌	deer
+🐮	cow face
+🐂	ox
+🐃	water buffalo
+🐄	cow
+🐷	pig face
+🐖	pig
+🐗	boar
+🐽	pig nose
+🐏	ram
+🐑	ewe
+🐐	goat
+🐪	camel
+🐫	two-hump camel
+🦙	llama
+🦒	giraffe
+🐘	elephant
+🦏	rhinoceros
+🦛	hippopotamus
+🐭	mouse face
+🐁	mouse
+🐀	rat
+🐹	hamster face
+🐰	rabbit face
+🐇	rabbit
+🐿️	chipmunk
+🐿	chipmunk
+🦔	hedgehog
+🦇	bat
+🐻	bear face
+🐨	koala
+🐼	panda face
+🦘	kangaroo
+🦡	badger
+🐾	paw prints
+🦃	turkey
+🐔	chicken
+🐓	rooster
+🐣	hatching chick
+🐤	baby chick
+🐥	front-facing baby chick
+🐦	bird
+🐧	penguin
+🕊️	dove
+🕊	dove
+🦅	eagle
+🦆	duck
+🦢	swan
+🦉	owl
+🦚	peacock
+🦜	parrot
+🐸	frog face
+🐊	crocodile
+🐢	turtle
+🦎	lizard
+🐍	snake
+🐲	dragon face
+🐉	dragon
+🦕	sauropod
+🦖	T-Rex
+🐳	spouting whale
+🐋	whale
+🐬	dolphin
+🐟	fish
+🐠	tropical fish
+🐡	blowfish
+🦈	shark
+🐙	octopus
+🐚	spiral shell
+🦀	crab
+🦞	lobster
+🦐	shrimp
+🦑	squid
+🐌	snail
+🦋	butterfly
+🐛	bug
+🐜	ant
+🐝	honeybee
+🐞	lady beetle
+🦗	cricket
+🕷️	spider
+🕷	spider
+🕸️	spider web
+🕸	spider web
+🦂	scorpion
+🦟	mosquito
+🦠	microbe
+💐	bouquet
+🌸	cherry blossom
+💮	white flower
+🏵️	rosette
+🏵	rosette
+🌹	rose
+🥀	wilted flower
+🌺	hibiscus
+🌻	sunflower
+🌼	blossom
+🌷	tulip
+🌱	seedling
+🌲	evergreen tree
+🌳	deciduous tree
+🌴	palm tree
+🌵	cactus
+🌾	sheaf of rice
+🌿	herb
+☘️	shamrock
+☘	shamrock
+🍀	four leaf clover
+🍁	maple leaf
+🍂	fallen leaf
+🍃	leaf fluttering in wind
+🍇	grapes
+🍈	melon
+🍉	watermelon
+🍊	tangerine
+🍋	lemon
+🍌	banana
+🍍	pineapple
+🥭	mango
+🍎	red apple
+🍏	green apple
+🍐	pear
+🍑	peach
+🍒	cherries
+🍓	strawberry
+🥝	kiwi fruit
+🍅	tomato
+🥥	coconut
+🥑	avocado
+🍆	eggplant
+🥔	potato
+🥕	carrot
+🌽	ear of corn
+🌶️	hot pepper
+🌶	hot pepper
+🥒	cucumber
+🥬	leafy green
+🥦	broccoli
+🍄	mushroom
+🥜	peanuts
+🌰	chestnut
+🍞	bread
+🥐	croissant
+🥖	baguette bread
+🥨	pretzel
+🥯	bagel
+🥞	pancakes
+🧀	cheese wedge
+🍖	meat on bone
+🍗	poultry leg
+🥩	cut of meat
+🥓	bacon
+🍔	hamburger
+🍟	french fries
+🍕	pizza
+🌭	hot dog
+🥪	sandwich
+🌮	taco
+🌯	burrito
+🥙	stuffed flatbread
+🥚	egg
+🍳	cooking
+🥘	shallow pan of food
+🍲	pot of food
+🥣	bowl with spoon
+🥗	green salad
+🍿	popcorn
+🧂	salt
+🥫	canned food
+🍱	bento box
+🍘	rice cracker
+🍙	rice ball
+🍚	cooked rice
+🍛	curry rice
+🍜	steaming bowl
+🍝	spaghetti
+🍠	roasted sweet potato
+🍢	oden
+🍣	sushi
+🍤	fried shrimp
+🍥	fish cake with swirl
+🥮	moon cake
+🍡	dango
+🥟	dumpling
+🥠	fortune cookie
+🥡	takeout box
+🍦	soft ice cream
+🍧	shaved ice
+🍨	ice cream
+🍩	doughnut
+🍪	cookie
+🎂	birthday cake
+🍰	shortcake
+🧁	cupcake
+🥧	pie
+🍫	chocolate bar
+🍬	candy
+🍭	lollipop
+🍮	custard
+🍯	honey pot
+🍼	baby bottle
+🥛	glass of milk
+☕	hot beverage
+🍵	teacup without handle
+🍶	sake
+🍾	bottle with popping cork
+🍷	wine glass
+🍸	cocktail glass
+🍹	tropical drink
+🍺	beer mug
+🍻	clinking beer mugs
+🥂	clinking glasses
+🥃	tumbler glass
+🥤	cup with straw
+🥢	chopsticks
+🍽️	fork and knife with plate
+🍽	fork and knife with plate
+🍴	fork and knife
+🥄	spoon
+🔪	kitchen knife
+🏺	amphora
+🌍	globe showing Europe-Africa
+🌎	globe showing Americas
+🌏	globe showing Asia-Australia
+🌐	globe with meridians
+🗺️	world map
+🗺	world map
+🗾	map of Japan
+🧭	compass
+🏔️	snow-capped mountain
+🏔	snow-capped mountain
+⛰️	mountain
+⛰	mountain
+🌋	volcano
+🗻	mount fuji
+🏕️	camping
+🏕	camping
+🏖️	beach with umbrella
+🏖	beach with umbrella
+🏜️	desert
+🏜	desert
+🏝️	desert island
+🏝	desert island
+🏞️	national park
+🏞	national park
+🏟️	stadium
+🏟	stadium
+🏛️	classical building
+🏛	classical building
+🏗️	building construction
+🏗	building construction
+🧱	bricks
+🏘️	houses
+🏘	houses
+🏚️	derelict house
+🏚	derelict house
+🏠	house
+🏡	house with garden
+🏢	office building
+🏣	Japanese post office
+🏤	post office
+🏥	hospital
+🏦	bank
+🏨	hotel
+🏩	love hotel
+🏪	convenience store
+🏫	school
+🏬	department store
+🏭	factory
+🏯	Japanese castle
+🏰	castle
+💒	wedding
+🗼	Tokyo tower
+🗽	Statue of Liberty
+⛪	church
+🕌	mosque
+🕍	synagogue
+⛩️	shinto shrine
+⛩	shinto shrine
+🕋	kaaba
+⛲	fountain
+⛺	tent
+🌁	foggy
+🌃	night with stars
+🏙️	cityscape
+🏙	cityscape
+🌄	sunrise over mountains
+🌅	sunrise
+🌆	cityscape at dusk
+🌇	sunset
+🌉	bridge at night
+♨️	hot springs
+♨	hot springs
+🌌	milky way
+🎠	carousel horse
+🎡	ferris wheel
+🎢	roller coaster
+💈	barber pole
+🎪	circus tent
+🚂	locomotive
+🚃	railway car
+🚄	high-speed train
+🚅	bullet train
+🚆	train
+🚇	metro
+🚈	light rail
+🚉	station
+🚊	tram
+🚝	monorail
+🚞	mountain railway
+🚋	tram car
+🚌	bus
+🚍	oncoming bus
+🚎	trolleybus
+🚐	minibus
+🚑	ambulance
+🚒	fire engine
+🚓	police car
+🚔	oncoming police car
+🚕	taxi
+🚖	oncoming taxi
+🚗	automobile
+🚘	oncoming automobile
+🚙	sport utility vehicle
+🚚	delivery truck
+🚛	articulated lorry
+🚜	tractor
+🚲	bicycle
+🛴	kick scooter
+🛹	skateboard
+🛵	motor scooter
+🚏	bus stop
+🛣️	motorway
+🛣	motorway
+🛤️	railway track
+🛤	railway track
+🛢️	oil drum
+🛢	oil drum
+⛽	fuel pump
+🚨	police car light
+🚥	horizontal traffic light
+🚦	vertical traffic light
+🛑	stop sign
+🚧	construction
+⚓	anchor
+⛵	sailboat
+🛶	canoe
+🚤	speedboat
+🛳️	passenger ship
+🛳	passenger ship
+⛴️	ferry
+⛴	ferry
+🛥️	motor boat
+🛥	motor boat
+🚢	ship
+✈️	airplane
+✈	airplane
+🛩️	small airplane
+🛩	small airplane
+🛫	airplane departure
+🛬	airplane arrival
+💺	seat
+🚁	helicopter
+🚟	suspension railway
+🚠	mountain cableway
+🚡	aerial tramway
+🛰️	satellite
+🛰	satellite
+🚀	rocket
+🛸	flying saucer
+🛎️	bellhop bell
+🛎	bellhop bell
+🧳	luggage
+⌛	hourglass done
+⏳	hourglass not done
+⌚	watch
+⏰	alarm clock
+⏱️	stopwatch
+⏱	stopwatch
+⏲️	timer clock
+⏲	timer clock
+🕰️	mantelpiece clock
+🕰	mantelpiece clock
+🕛	twelve o’clock
+🕧	twelve-thirty
+🕐	one o’clock
+🕜	one-thirty
+🕑	two o’clock
+🕝	two-thirty
+🕒	three o’clock
+🕞	three-thirty
+🕓	four o’clock
+🕟	four-thirty
+🕔	five o’clock
+🕠	five-thirty
+🕕	six o’clock
+🕡	six-thirty
+🕖	seven o’clock
+🕢	seven-thirty
+🕗	eight o’clock
+🕣	eight-thirty
+🕘	nine o’clock
+🕤	nine-thirty
+🕙	ten o’clock
+🕥	ten-thirty
+🕚	eleven o’clock
+🕦	eleven-thirty
+🌑	new moon
+🌒	waxing crescent moon
+🌓	first quarter moon
+🌔	waxing gibbous moon
+🌕	full moon
+🌖	waning gibbous moon
+🌗	last quarter moon
+🌘	waning crescent moon
+🌙	crescent moon
+🌚	new moon face
+🌛	first quarter moon face
+🌜	last quarter moon face
+🌡️	thermometer
+🌡	thermometer
+☀️	sun
+☀	sun
+🌝	full moon face
+🌞	sun with face
+⭐	star
+🌟	glowing star
+🌠	shooting star
+☁️	cloud
+☁	cloud
+⛅	sun behind cloud
+⛈️	cloud with lightning and rain
+⛈	cloud with lightning and rain
+🌤️	sun behind small cloud
+🌤	sun behind small cloud
+🌥️	sun behind large cloud
+🌥	sun behind large cloud
+🌦️	sun behind rain cloud
+🌦	sun behind rain cloud
+🌧️	cloud with rain
+🌧	cloud with rain
+🌨️	cloud with snow
+🌨	cloud with snow
+🌩️	cloud with lightning
+🌩	cloud with lightning
+🌪️	tornado
+🌪	tornado
+🌫️	fog
+🌫	fog
+🌬️	wind face
+🌬	wind face
+🌀	cyclone
+🌈	rainbow
+🌂	closed umbrella
+☂️	umbrella
+☂	umbrella
+☔	umbrella with rain drops
+⛱️	umbrella on ground
+⛱	umbrella on ground
+⚡	high voltage
+❄️	snowflake
+❄	snowflake
+☃️	snowman
+☃	snowman
+⛄	snowman without snow
+☄️	comet
+☄	comet
+🔥	fire
+💧	droplet
+🌊	water wave
+🎃	jack-o-lantern
+🎄	Christmas tree
+🎆	fireworks
+🎇	sparkler
+🧨	firecracker
+✨	sparkles
+🎈	balloon
+🎉	party popper
+🎊	confetti ball
+🎋	tanabata tree
+🎍	pine decoration
+🎎	Japanese dolls
+🎏	carp streamer
+🎐	wind chime
+🎑	moon viewing ceremony
+🧧	red envelope
+🎀	ribbon
+🎁	wrapped gift
+🎗️	reminder ribbon
+🎗	reminder ribbon
+🎟️	admission tickets
+🎟	admission tickets
+🎫	ticket
+🎖️	military medal
+🎖	military medal
+🏆	trophy
+🏅	sports medal
+🥇	1st place medal
+🥈	2nd place medal
+🥉	3rd place medal
+⚽	soccer ball
+⚾	baseball
+🥎	softball
+🏀	basketball
+🏐	volleyball
+🏈	american football
+🏉	rugby football
+🎾	tennis
+🥏	flying disc
+🎳	bowling
+🏏	cricket game
+🏑	field hockey
+🏒	ice hockey
+🥍	lacrosse
+🏓	ping pong
+🏸	badminton
+🥊	boxing glove
+🥋	martial arts uniform
+🥅	goal net
+⛳	flag in hole
+⛸️	ice skate
+⛸	ice skate
+🎣	fishing pole
+🎽	running shirt
+🎿	skis
+🛷	sled
+🥌	curling stone
+🎯	direct hit
+🎱	pool 8 ball
+🔮	crystal ball
+🧿	nazar amulet
+🎮	video game
+🕹️	joystick
+🕹	joystick
+🎰	slot machine
+🎲	game die
+🧩	jigsaw
+🧸	teddy bear
+♠️	spade suit
+♠	spade suit
+♥️	heart suit
+♥	heart suit
+♦️	diamond suit
+♦	diamond suit
+♣️	club suit
+♣	club suit
+♟️	chess pawn
+♟	chess pawn
+🃏	joker
+🀄	mahjong red dragon
+🎴	flower playing cards
+🎭	performing arts
+🖼️	framed picture
+🖼	framed picture
+🎨	artist palette
+🧵	thread
+🧶	yarn
+🔇	muted speaker
+🔈	speaker low volume
+🔉	speaker medium volume
+🔊	speaker high volume
+📢	loudspeaker
+📣	megaphone
+📯	postal horn
+🔔	bell
+🔕	bell with slash
+🎼	musical score
+🎵	musical note
+🎶	musical notes
+🎙️	studio microphone
+🎙	studio microphone
+🎚️	level slider
+🎚	level slider
+🎛️	control knobs
+🎛	control knobs
+🎤	microphone
+🎧	headphone
+📻	radio
+🎷	saxophone
+🎸	guitar
+🎹	musical keyboard
+🎺	trumpet
+🎻	violin
+🥁	drum
+📱	mobile phone
+📲	mobile phone with arrow
+☎️	telephone
+☎	telephone
+📞	telephone receiver
+📟	pager
+📠	fax machine
+🔋	battery
+🔌	electric plug
+💻	laptop computer
+🖥️	desktop computer
+🖥	desktop computer
+🖨️	printer
+🖨	printer
+⌨️	keyboard
+⌨	keyboard
+🖱️	computer mouse
+🖱	computer mouse
+🖲️	trackball
+🖲	trackball
+💽	computer disk
+💾	floppy disk
+💿	optical disk
+📀	dvd
+🧮	abacus
+🎥	movie camera
+🎞️	film frames
+🎞	film frames
+📽️	film projector
+📽	film projector
+🎬	clapper board
+📺	television
+📷	camera
+📸	camera with flash
+📹	video camera
+📼	videocassette
+🔍	magnifying glass tilted left
+🔎	magnifying glass tilted right
+🕯️	candle
+🕯	candle
+💡	light bulb
+🔦	flashlight
+🏮	red paper lantern
+📔	notebook with decorative cover
+📕	closed book
+📖	open book
+📗	green book
+📘	blue book
+📙	orange book
+📚	books
+📓	notebook
+📒	ledger
+📃	page with curl
+📜	scroll
+📄	page facing up
+📰	newspaper
+🗞️	rolled-up newspaper
+🗞	rolled-up newspaper
+📑	bookmark tabs
+🔖	bookmark
+🏷️	label
+🏷	label
+💰	money bag
+💴	yen banknote
+💵	dollar banknote
+💶	euro banknote
+💷	pound banknote
+💸	money with wings
+💳	credit card
+🧾	receipt
+💹	chart increasing with yen
+💱	currency exchange
+💲	heavy dollar sign
+✉️	envelope
+✉	envelope
+📧	e-mail
+📨	incoming envelope
+📩	envelope with arrow
+📤	outbox tray
+📥	inbox tray
+📦	package
+📫	closed mailbox with raised flag
+📪	closed mailbox with lowered flag
+📬	open mailbox with raised flag
+📭	open mailbox with lowered flag
+📮	postbox
+🗳️	ballot box with ballot
+🗳	ballot box with ballot
+✏️	pencil
+✏	pencil
+✒️	black nib
+✒	black nib
+🖋️	fountain pen
+🖋	fountain pen
+🖊️	pen
+🖊	pen
+🖌️	paintbrush
+🖌	paintbrush
+🖍️	crayon
+🖍	crayon
+📝	memo
+💼	briefcase
+📁	file folder
+📂	open file folder
+🗂️	card index dividers
+🗂	card index dividers
+📅	calendar
+📆	tear-off calendar
+🗒️	spiral notepad
+🗒	spiral notepad
+🗓️	spiral calendar
+🗓	spiral calendar
+📇	card index
+📈	chart increasing
+📉	chart decreasing
+📊	bar chart
+📋	clipboard
+📌	pushpin
+📍	round pushpin
+📎	paperclip
+🖇️	linked paperclips
+🖇	linked paperclips
+📏	straight ruler
+📐	triangular ruler
+✂️	scissors
+✂	scissors
+🗃️	card file box
+🗃	card file box
+🗄️	file cabinet
+🗄	file cabinet
+🗑️	wastebasket
+🗑	wastebasket
+🔒	locked
+🔓	unlocked
+🔏	locked with pen
+🔐	locked with key
+🔑	key
+🗝️	old key
+🗝	old key
+🔨	hammer
+⛏️	pick
+⛏	pick
+⚒️	hammer and pick
+⚒	hammer and pick
+🛠️	hammer and wrench
+🛠	hammer and wrench
+🗡️	dagger
+🗡	dagger
+⚔️	crossed swords
+⚔	crossed swords
+🔫	pistol
+🏹	bow and arrow
+🛡️	shield
+🛡	shield
+🔧	wrench
+🔩	nut and bolt
+⚙️	gear
+⚙	gear
+🗜️	clamp
+🗜	clamp
+⚖️	balance scale
+⚖	balance scale
+🔗	link
+⛓️	chains
+⛓	chains
+🧰	toolbox
+🧲	magnet
+⚗️	alembic
+⚗	alembic
+🧪	test tube
+🧫	petri dish
+🧬	dna
+🔬	microscope
+🔭	telescope
+📡	satellite antenna
+💉	syringe
+💊	pill
+🚪	door
+🛏️	bed
+🛏	bed
+🛋️	couch and lamp
+🛋	couch and lamp
+🚽	toilet
+🚿	shower
+🛁	bathtub
+🧴	lotion bottle
+🧷	safety pin
+🧹	broom
+🧺	basket
+🧻	roll of paper
+🧼	soap
+🧽	sponge
+🧯	fire extinguisher
+🛒	shopping cart
+🚬	cigarette
+⚰️	coffin
+⚰	coffin
+⚱️	funeral urn
+⚱	funeral urn
+🗿	moai
+🏧	ATM sign
+🚮	litter in bin sign
+🚰	potable water
+♿	wheelchair symbol
+🚹	men’s room
+🚺	women’s room
+🚻	restroom
+🚼	baby symbol
+🚾	water closet
+🛂	passport control
+🛃	customs
+🛄	baggage claim
+🛅	left luggage
+⚠️	warning
+⚠	warning
+🚸	children crossing
+⛔	no entry
+🚫	prohibited
+🚳	no bicycles
+🚭	no smoking
+🚯	no littering
+🚱	non-potable water
+🚷	no pedestrians
+📵	no mobile phones
+🔞	no one under eighteen
+☢️	radioactive
+☢	radioactive
+☣️	biohazard
+☣	biohazard
+⬆️	up arrow
+⬆	up arrow
+↗️	up-right arrow
+↗	up-right arrow
+➡️	right arrow
+➡	right arrow
+↘️	down-right arrow
+↘	down-right arrow
+⬇️	down arrow
+⬇	down arrow
+↙️	down-left arrow
+↙	down-left arrow
+⬅️	left arrow
+⬅	left arrow
+↖️	up-left arrow
+↖	up-left arrow
+↕️	up-down arrow
+↕	up-down arrow
+↔️	left-right arrow
+↔	left-right arrow
+↩️	right arrow curving left
+↩	right arrow curving left
+↪️	left arrow curving right
+↪	left arrow curving right
+⤴️	right arrow curving up
+⤴	right arrow curving up
+⤵️	right arrow curving down
+⤵	right arrow curving down
+🔃	clockwise vertical arrows
+🔄	counterclockwise arrows button
+🔙	BACK arrow
+🔚	END arrow
+🔛	ON! arrow
+🔜	SOON arrow
+🔝	TOP arrow
+🛐	place of worship
+⚛️	atom symbol
+⚛	atom symbol
+🕉️	om
+🕉	om
+✡️	star of David
+✡	star of David
+☸️	wheel of dharma
+☸	wheel of dharma
+☯️	yin yang
+☯	yin yang
+✝️	latin cross
+✝	latin cross
+☦️	orthodox cross
+☦	orthodox cross
+☪️	star and crescent
+☪	star and crescent
+☮️	peace symbol
+☮	peace symbol
+🕎	menorah
+🔯	dotted six-pointed star
+♈	Aries
+♉	Taurus
+♊	Gemini
+♋	Cancer
+♌	Leo
+♍	Virgo
+♎	Libra
+♏	Scorpio
+♐	Sagittarius
+♑	Capricorn
+♒	Aquarius
+♓	Pisces
+⛎	Ophiuchus
+🔀	shuffle tracks button
+🔁	repeat button
+🔂	repeat single button
+▶️	play button
+▶	play button
+⏩	fast-forward button
+⏭️	next track button
+⏭	next track button
+⏯️	play or pause button
+⏯	play or pause button
+◀️	reverse button
+◀	reverse button
+⏪	fast reverse button
+⏮️	last track button
+⏮	last track button
+🔼	upwards button
+⏫	fast up button
+🔽	downwards button
+⏬	fast down button
+⏸️	pause button
+⏸	pause button
+⏹️	stop button
+⏹	stop button
+⏺️	record button
+⏺	record button
+⏏️	eject button
+⏏	eject button
+🎦	cinema
+🔅	dim button
+🔆	bright button
+📶	antenna bars
+📳	vibration mode
+📴	mobile phone off
+♀️	female sign
+♀	female sign
+♂️	male sign
+♂	male sign
+⚕️	medical symbol
+⚕	medical symbol
+♾️	infinity
+♾	infinity
+♻️	recycling symbol
+♻	recycling symbol
+⚜️	fleur-de-lis
+⚜	fleur-de-lis
+🔱	trident emblem
+📛	name badge
+🔰	Japanese symbol for beginner
+⭕	heavy large circle
+✅	white heavy check mark
+☑️	ballot box with check
+☑	ballot box with check
+✔️	heavy check mark
+✔	heavy check mark
+✖️	heavy multiplication x
+✖	heavy multiplication x
+❌	cross mark
+❎	cross mark button
+➕	heavy plus sign
+➖	heavy minus sign
+➗	heavy division sign
+➰	curly loop
+➿	double curly loop
+〽️	part alternation mark
+〽	part alternation mark
+✳️	eight-spoked asterisk
+✳	eight-spoked asterisk
+✴️	eight-pointed star
+✴	eight-pointed star
+❇️	sparkle
+❇	sparkle
+‼️	double exclamation mark
+‼	double exclamation mark
+⁉️	exclamation question mark
+⁉	exclamation question mark
+❓	question mark
+❔	white question mark
+❕	white exclamation mark
+❗	exclamation mark
+〰️	wavy dash
+〰	wavy dash
+©️	copyright
+©	copyright
+®️	registered
+®	registered
+™️	trade mark
+™	trade mark
+#️⃣	keycap: #
+#⃣	keycap: #
+*️⃣	keycap: *
+*⃣	keycap: *
+0️⃣	keycap: 0
+0⃣	keycap: 0
+1️⃣	keycap: 1
+1⃣	keycap: 1
+2️⃣	keycap: 2
+2⃣	keycap: 2
+3️⃣	keycap: 3
+3⃣	keycap: 3
+4️⃣	keycap: 4
+4⃣	keycap: 4
+5️⃣	keycap: 5
+5⃣	keycap: 5
+6️⃣	keycap: 6
+6⃣	keycap: 6
+7️⃣	keycap: 7
+7⃣	keycap: 7
+8️⃣	keycap: 8
+8⃣	keycap: 8
+9️⃣	keycap: 9
+9⃣	keycap: 9
+🔟	keycap: 10
+💯	hundred points
+🔠	input latin uppercase
+🔡	input latin lowercase
+🔢	input numbers
+🔣	input symbols
+🔤	input latin letters
+🅰️	A button (blood type)
+🅰	A button (blood type)
+🆎	AB button (blood type)
+🅱️	B button (blood type)
+🅱	B button (blood type)
+🆑	CL button
+🆒	COOL button
+🆓	FREE button
+ℹ️	information
+ℹ	information
+🆔	ID button
+Ⓜ️	circled M
+Ⓜ	circled M
+🆕	NEW button
+🆖	NG button
+🅾️	O button (blood type)
+🅾	O button (blood type)
+🆗	OK button
+🅿️	P button
+🅿	P button
+🆘	SOS button
+🆙	UP! button
+🆚	VS button
+🈁	Japanese “here” button
+🈂️	Japanese “service charge” button
+🈂	Japanese “service charge” button
+🈷️	Japanese “monthly amount” button
+🈷	Japanese “monthly amount” button
+🈶	Japanese “not free of charge” button
+🈯	Japanese “reserved” button
+🉐	Japanese “bargain” button
+🈹	Japanese “discount” button
+🈚	Japanese “free of charge” button
+🈲	Japanese “prohibited” button
+🉑	Japanese “acceptable” button
+🈸	Japanese “application” button
+🈴	Japanese “passing grade” button
+🈳	Japanese “vacancy” button
+㊗️	Japanese “congratulations” button
+㊗	Japanese “congratulations” button
+㊙️	Japanese “secret” button
+㊙	Japanese “secret” button
+🈺	Japanese “open for business” button
+🈵	Japanese “no vacancy” button
+▪️	black small square
+▪	black small square
+▫️	white small square
+▫	white small square
+◻️	white medium square
+◻	white medium square
+◼️	black medium square
+◼	black medium square
+◽	white medium-small square
+◾	black medium-small square
+⬛	black large square
+⬜	white large square
+🔶	large orange diamond
+🔷	large blue diamond
+🔸	small orange diamond
+🔹	small blue diamond
+🔺	red triangle pointed up
+🔻	red triangle pointed down
+💠	diamond with a dot
+🔘	radio button
+🔲	black square button
+🔳	white square button
+⚪	white circle
+⚫	black circle
+🔴	red circle
+🔵	blue circle
+🏁	chequered flag
+🚩	triangular flag
+🎌	crossed flags
+🏴	black flag
+🏳️	white flag
+🏳	white flag
+🏳️‍🌈	rainbow flag
+🏳‍🌈	rainbow flag
+🏴‍☠️	pirate flag
+🏴‍☠	pirate flag
+🇦🇨	Ascension Island
+🇦🇩	Andorra
+🇦🇪	United Arab Emirates
+🇦🇫	Afghanistan
+🇦🇬	Antigua & Barbuda
+🇦🇮	Anguilla
+🇦🇱	Albania
+🇦🇲	Armenia
+🇦🇴	Angola
+🇦🇶	Antarctica
+🇦🇷	Argentina
+🇦🇸	American Samoa
+🇦🇹	Austria
+🇦🇺	Australia
+🇦🇼	Aruba
+🇦🇽	Åland Islands
+🇦🇿	Azerbaijan
+🇧🇦	Bosnia & Herzegovina
+🇧🇧	Barbados
+🇧🇩	Bangladesh
+🇧🇪	Belgium
+🇧🇫	Burkina Faso
+🇧🇬	Bulgaria
+🇧🇭	Bahrain
+🇧🇮	Burundi
+🇧🇯	Benin
+🇧🇱	St. Barthélemy
+🇧🇲	Bermuda
+🇧🇳	Brunei
+🇧🇴	Bolivia
+🇧🇶	Caribbean Netherlands
+🇧🇷	Brazil
+🇧🇸	Bahamas
+🇧🇹	Bhutan
+🇧🇻	Bouvet Island
+🇧🇼	Botswana
+🇧🇾	Belarus
+🇧🇿	Belize
+🇨🇦	Canada
+🇨🇨	Cocos (Keeling) Islands
+🇨🇩	Congo - Kinshasa
+🇨🇫	Central African Republic
+🇨🇬	Congo - Brazzaville
+🇨🇭	Switzerland
+🇨🇮	Côte d’Ivoire
+🇨🇰	Cook Islands
+🇨🇱	Chile
+🇨🇲	Cameroon
+🇨🇳	China
+🇨🇴	Colombia
+🇨🇵	Clipperton Island
+🇨🇷	Costa Rica
+🇨🇺	Cuba
+🇨🇻	Cape Verde
+🇨🇼	Curaçao
+🇨🇽	Christmas Island
+🇨🇾	Cyprus
+🇨🇿	Czechia
+🇩🇪	Germany
+🇩🇬	Diego Garcia
+🇩🇯	Djibouti
+🇩🇰	Denmark
+🇩🇲	Dominica
+🇩🇴	Dominican Republic
+🇩🇿	Algeria
+🇪🇦	Ceuta & Melilla
+🇪🇨	Ecuador
+🇪🇪	Estonia
+🇪🇬	Egypt
+🇪🇭	Western Sahara
+🇪🇷	Eritrea
+🇪🇸	Spain
+🇪🇹	Ethiopia
+🇪🇺	European Union
+🇫🇮	Finland
+🇫🇯	Fiji
+🇫🇰	Falkland Islands
+🇫🇲	Micronesia
+🇫🇴	Faroe Islands
+🇫🇷	France
+🇬🇦	Gabon
+🇬🇧	United Kingdom
+🇬🇩	Grenada
+🇬🇪	Georgia
+🇬🇫	French Guiana
+🇬🇬	Guernsey
+🇬🇭	Ghana
+🇬🇮	Gibraltar
+🇬🇱	Greenland
+🇬🇲	Gambia
+🇬🇳	Guinea
+🇬🇵	Guadeloupe
+🇬🇶	Equatorial Guinea
+🇬🇷	Greece
+🇬🇸	South Georgia & South Sandwich Islands
+🇬🇹	Guatemala
+🇬🇺	Guam
+🇬🇼	Guinea-Bissau
+🇬🇾	Guyana
+🇭🇰	Hong Kong SAR China
+🇭🇲	Heard & McDonald Islands
+🇭🇳	Honduras
+🇭🇷	Croatia
+🇭🇹	Haiti
+🇭🇺	Hungary
+🇮🇨	Canary Islands
+🇮🇩	Indonesia
+🇮🇪	Ireland
+🇮🇱	Israel
+🇮🇲	Isle of Man
+🇮🇳	India
+🇮🇴	British Indian Ocean Territory
+🇮🇶	Iraq
+🇮🇷	Iran
+🇮🇸	Iceland
+🇮🇹	Italy
+🇯🇪	Jersey
+🇯🇲	Jamaica
+🇯🇴	Jordan
+🇯🇵	Japan
+🇰🇪	Kenya
+🇰🇬	Kyrgyzstan
+🇰🇭	Cambodia
+🇰🇮	Kiribati
+🇰🇲	Comoros
+🇰🇳	St. Kitts & Nevis
+🇰🇵	North Korea
+🇰🇷	South Korea
+🇰🇼	Kuwait
+🇰🇾	Cayman Islands
+🇰🇿	Kazakhstan
+🇱🇦	Laos
+🇱🇧	Lebanon
+🇱🇨	St. Lucia
+🇱🇮	Liechtenstein
+🇱🇰	Sri Lanka
+🇱🇷	Liberia
+🇱🇸	Lesotho
+🇱🇹	Lithuania
+🇱🇺	Luxembourg
+🇱🇻	Latvia
+🇱🇾	Libya
+🇲🇦	Morocco
+🇲🇨	Monaco
+🇲🇩	Moldova
+🇲🇪	Montenegro
+🇲🇫	St. Martin
+🇲🇬	Madagascar
+🇲🇭	Marshall Islands
+🇲🇰	Macedonia
+🇲🇱	Mali
+🇲🇲	Myanmar (Burma)
+🇲🇳	Mongolia
+🇲🇴	Macau SAR China
+🇲🇵	Northern Mariana Islands
+🇲🇶	Martinique
+🇲🇷	Mauritania
+🇲🇸	Montserrat
+🇲🇹	Malta
+🇲🇺	Mauritius
+🇲🇻	Maldives
+🇲🇼	Malawi
+🇲🇽	Mexico
+🇲🇾	Malaysia
+🇲🇿	Mozambique
+🇳🇦	Namibia
+🇳🇨	New Caledonia
+🇳🇪	Niger
+🇳🇫	Norfolk Island
+🇳🇬	Nigeria
+🇳🇮	Nicaragua
+🇳🇱	Netherlands
+🇳🇴	Norway
+🇳🇵	Nepal
+🇳🇷	Nauru
+🇳🇺	Niue
+🇳🇿	New Zealand
+🇴🇲	Oman
+🇵🇦	Panama
+🇵🇪	Peru
+🇵🇫	French Polynesia
+🇵🇬	Papua New Guinea
+🇵🇭	Philippines
+🇵🇰	Pakistan
+🇵🇱	Poland
+🇵🇲	St. Pierre & Miquelon
+🇵🇳	Pitcairn Islands
+🇵🇷	Puerto Rico
+🇵🇸	Palestinian Territories
+🇵🇹	Portugal
+🇵🇼	Palau
+🇵🇾	Paraguay
+🇶🇦	Qatar
+🇷🇪	Réunion
+🇷🇴	Romania
+🇷🇸	Serbia
+🇷🇺	Russia
+🇷🇼	Rwanda
+🇸🇦	Saudi Arabia
+🇸🇧	Solomon Islands
+🇸🇨	Seychelles
+🇸🇩	Sudan
+🇸🇪	Sweden
+🇸🇬	Singapore
+🇸🇭	St. Helena
+🇸🇮	Slovenia
+🇸🇯	Svalbard & Jan Mayen
+🇸🇰	Slovakia
+🇸🇱	Sierra Leone
+🇸🇲	San Marino
+🇸🇳	Senegal
+🇸🇴	Somalia
+🇸🇷	Suriname
+🇸🇸	South Sudan
+🇸🇹	São Tomé & Príncipe
+🇸🇻	El Salvador
+🇸🇽	Sint Maarten
+🇸🇾	Syria
+🇸🇿	Swaziland
+🇹🇦	Tristan da Cunha
+🇹🇨	Turks & Caicos Islands
+🇹🇩	Chad
+🇹🇫	French Southern Territories
+🇹🇬	Togo
+🇹🇭	Thailand
+🇹🇯	Tajikistan
+🇹🇰	Tokelau
+🇹🇱	Timor-Leste
+🇹🇲	Turkmenistan
+🇹🇳	Tunisia
+🇹🇴	Tonga
+🇹🇷	Turkey
+🇹🇹	Trinidad & Tobago
+🇹🇻	Tuvalu
+🇹🇼	Taiwan
+🇹🇿	Tanzania
+🇺🇦	Ukraine
+🇺🇬	Uganda
+🇺🇲	U.S. Outlying Islands
+🇺🇳	United Nations
+🇺🇸	United States
+🇺🇾	Uruguay
+🇺🇿	Uzbekistan
+🇻🇦	Vatican City
+🇻🇨	St. Vincent & Grenadines
+🇻🇪	Venezuela
+🇻🇬	British Virgin Islands
+🇻🇮	U.S. Virgin Islands
+🇻🇳	Vietnam
+🇻🇺	Vanuatu
+🇼🇫	Wallis & Futuna
+🇼🇸	Samoa
+🇽🇰	Kosovo
+🇾🇪	Yemen
+🇾🇹	Mayotte
+🇿🇦	South Africa
+🇿🇲	Zambia
+🇿🇼	Zimbabwe
+🏴󠁧󠁢󠁥󠁮󠁧󠁿	England
+🏴󠁧󠁢󠁳󠁣󠁴󠁿	Scotland
 🏴󠁧󠁢󠁷󠁬󠁳󠁿	Wales
\ No newline at end of file
diff --git a/vaderSentiment/vaderSentiment.py b/vaderSentiment/vaderSentiment.py
index 49cba44..e8587de 100644
--- a/vaderSentiment/vaderSentiment.py
+++ b/vaderSentiment/vaderSentiment.py
@@ -1,682 +1,684 @@
-# coding: utf-8
-# Author: C.J. Hutto
-# Thanks to George Berry for reducing the time complexity from something like O(N^4) to O(N).
-# Thanks to Ewan Klein and Pierpaolo Pantone for bringing VADER into NLTK. Those modifications were awesome.
-# For license information, see LICENSE.TXT
-
-"""
-If you use the VADER sentiment analysis tools, please cite:
-Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for
-Sentiment Analysis of Social Media Text. Eighth International Conference on
-Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.
-"""
-import os
-import re
-import math
-import string
-import requests
-import json
-from itertools import product
-from inspect import getsourcefile
-from io import open
-
-# ##Constants##
-
-# (empirically derived mean sentiment intensity rating increase for booster words)
-B_INCR = 0.293
-B_DECR = -0.293
-
-# (empirically derived mean sentiment intensity rating increase for using ALLCAPs to emphasize a word)
-C_INCR = 0.733
-N_SCALAR = -0.74
-
-# for removing punctuation
-REGEX_REMOVE_PUNCTUATION = re.compile('[%s]' % re.escape(string.punctuation))
-
-PUNC_LIST = [".", "!", "?", ",", ";", ":", "-", "'", "\"",
-             "!!", "!!!", "??", "???", "?!?", "!?!", "?!?!", "!?!?"]
-NEGATE = \
-    ["aint", "arent", "cannot", "cant", "couldnt", "darent", "didnt", "doesnt",
-     "ain't", "aren't", "can't", "couldn't", "daren't", "didn't", "doesn't",
-     "dont", "hadnt", "hasnt", "havent", "isnt", "mightnt", "mustnt", "neither",
-     "don't", "hadn't", "hasn't", "haven't", "isn't", "mightn't", "mustn't",
-     "neednt", "needn't", "never", "none", "nope", "nor", "not", "nothing", "nowhere",
-     "oughtnt", "shant", "shouldnt", "uhuh", "wasnt", "werent",
-     "oughtn't", "shan't", "shouldn't", "uh-uh", "wasn't", "weren't",
-     "without", "wont", "wouldnt", "won't", "wouldn't", "rarely", "seldom", "despite"]
-
-# booster/dampener 'intensifiers' or 'degree adverbs'
-# http://en.wiktionary.org/wiki/Category:English_degree_adverbs
-
-BOOSTER_DICT = \
-    {"absolutely": B_INCR, "amazingly": B_INCR, "awfully": B_INCR, "completely": B_INCR, "considerably": B_INCR,
-     "decidedly": B_INCR, "deeply": B_INCR, "effing": B_INCR, "enormously": B_INCR,
-     "entirely": B_INCR, "especially": B_INCR, "exceptionally": B_INCR, "extremely": B_INCR,
-     "fabulously": B_INCR, "flipping": B_INCR, "flippin": B_INCR,
-     "fricking": B_INCR, "frickin": B_INCR, "frigging": B_INCR, "friggin": B_INCR, "fully": B_INCR, "fucking": B_INCR,
-     "greatly": B_INCR, "hella": B_INCR, "highly": B_INCR, "hugely": B_INCR, "incredibly": B_INCR,
-     "intensely": B_INCR, "majorly": B_INCR, "more": B_INCR, "most": B_INCR, "particularly": B_INCR,
-     "purely": B_INCR, "quite": B_INCR, "really": B_INCR, "remarkably": B_INCR,
-     "so": B_INCR, "substantially": B_INCR,
-     "thoroughly": B_INCR, "totally": B_INCR, "tremendously": B_INCR,
-     "uber": B_INCR, "unbelievably": B_INCR, "unusually": B_INCR, "utterly": B_INCR,
-     "very": B_INCR,
-     "almost": B_DECR, "barely": B_DECR, "hardly": B_DECR, "just enough": B_DECR,
-     "kind of": B_DECR, "kinda": B_DECR, "kindof": B_DECR, "kind-of": B_DECR,
-     "less": B_DECR, "little": B_DECR, "marginally": B_DECR, "occasionally": B_DECR, "partly": B_DECR,
-     "scarcely": B_DECR, "slightly": B_DECR, "somewhat": B_DECR,
-     "sort of": B_DECR, "sorta": B_DECR, "sortof": B_DECR, "sort-of": B_DECR}
-
-# check for sentiment laden idioms that do not contain lexicon words (future work, not yet implemented)
-SENTIMENT_LADEN_IDIOMS = {"cut the mustard": 2, "hand to mouth": -2,
-                          "back handed": -2, "blow smoke": -2, "blowing smoke": -2,
-                          "upper hand": 1, "break a leg": 2,
-                          "cooking with gas": 2, "in the black": 2, "in the red": -2,
-                          "on the ball": 2, "under the weather": -2}
-
-# check for special case idioms containing lexicon words
-SPECIAL_CASE_IDIOMS = {"the shit": 3, "the bomb": 3, "bad ass": 1.5, "yeah right": -2,
-                       "kiss of death": -1.5}
-
-
-# #Static methods# #
-
-def negated(input_words, include_nt=True):
-    """
-    Determine if input contains negation words
-    """
-    input_words = [str(w).lower() for w in input_words]
-    neg_words = []
-    neg_words.extend(NEGATE)
-    for word in neg_words:
-        if word in input_words:
-            return True
-    if include_nt:
-        for word in input_words:
-            if "n't" in word:
-                return True
-    if "least" in input_words:
-        i = input_words.index("least")
-        if i > 0 and input_words[i - 1] != "at":
-            return True
-    return False
-
-
-def normalize(score, alpha=15):
-    """
-    Normalize the score to be between -1 and 1 using an alpha that
-    approximates the max expected value
-    """
-    norm_score = score / math.sqrt((score * score) + alpha)
-    if norm_score < -1.0:
-        return -1.0
-    elif norm_score > 1.0:
-        return 1.0
-    else:
-        return norm_score
-
-
-def allcap_differential(words):
-    """
-    Check whether just some words in the input are ALL CAPS
-    :param list words: The words to inspect
-    :returns: `True` if some but not all items in `words` are ALL CAPS
-    """
-    is_different = False
-    allcap_words = 0
-    for word in words:
-        if word.isupper():
-            allcap_words += 1
-    cap_differential = len(words) - allcap_words
-    if 0 < cap_differential < len(words):
-        is_different = True
-    return is_different
-
-
-def scalar_inc_dec(word, valence, is_cap_diff):
-    """
-    Check if the preceding words increase, decrease, or negate/nullify the
-    valence
-    """
-    scalar = 0.0
-    word_lower = word.lower()
-    if word_lower in BOOSTER_DICT:
-        scalar = BOOSTER_DICT[word_lower]
-        if valence < 0:
-            scalar *= -1
-        # check if booster/dampener word is in ALLCAPS (while others aren't)
-        if word.isupper() and is_cap_diff:
-            if valence > 0:
-                scalar += C_INCR
-            else:
-                scalar -= C_INCR
-    return scalar
-
-
-class SentiText(object):
-    """
-    Identify sentiment-relevant string-level properties of input text.
-    """
-
-    def __init__(self, text):
-        if not isinstance(text, str):
-            text = str(text).encode('utf-8')
-        self.text = text
-        self.words_and_emoticons = self._words_and_emoticons()
-        # doesn't separate words from\
-        # adjacent punctuation (keeps emoticons & contractions)
-        self.is_cap_diff = allcap_differential(self.words_and_emoticons)
-
-    def _words_plus_punc(self):
-        """
-        Returns mapping of form:
-        {
-            'cat,': 'cat',
-            ',cat': 'cat',
-        }
-        """
-        no_punc_text = REGEX_REMOVE_PUNCTUATION.sub('', self.text)
-        # removes punctuation (but loses emoticons & contractions)
-        words_only = no_punc_text.split()
-        # remove singletons
-        words_only = set(w for w in words_only if len(w) > 1)
-        # the product gives ('cat', ',') and (',', 'cat')
-        punc_before = {''.join(p): p[1] for p in product(PUNC_LIST, words_only)}
-        punc_after = {''.join(p): p[0] for p in product(words_only, PUNC_LIST)}
-        words_punc_dict = punc_before
-        words_punc_dict.update(punc_after)
-        return words_punc_dict
-
-    def _words_and_emoticons(self):
-        """
-        Removes leading and trailing puncutation
-        Leaves contractions and most emoticons
-            Does not preserve punc-plus-letter emoticons (e.g. :D)
-        """
-        wes = self.text.split()
-        words_punc_dict = self._words_plus_punc()
-        wes = [we for we in wes if len(we) > 1]
-        for i, we in enumerate(wes):
-            if we in words_punc_dict:
-                wes[i] = words_punc_dict[we]
-        return wes
-
-
-class SentimentIntensityAnalyzer(object):
-    """
-    Give a sentiment intensity score to sentences.
-    """
-
-    def __init__(self, lexicon_file="vader_lexicon.txt", emoji_lexicon="emoji_utf8_lexicon.txt"):
-        _this_module_file_path_ = os.path.abspath(getsourcefile(lambda: 0))
-        lexicon_full_filepath = os.path.join(os.path.dirname(_this_module_file_path_), lexicon_file)
-        with open(lexicon_full_filepath, encoding='utf-8') as f:
-            self.lexicon_full_filepath = f.read()
-        self.lexicon = self.make_lex_dict()
-
-        emoji_full_filepath = os.path.join(os.path.dirname(_this_module_file_path_), emoji_lexicon)
-        with open(emoji_full_filepath, encoding='utf-8') as f:
-            self.emoji_full_filepath = f.read()
-        self.emojis = self.make_emoji_dict()
-
-    def make_lex_dict(self):
-        """
-        Convert lexicon file to a dictionary
-        """
-        lex_dict = {}
-        for line in self.lexicon_full_filepath.split('\n'):
-            (word, measure) = line.strip().split('\t')[0:2]
-            lex_dict[word] = float(measure)
-        return lex_dict
-
-    def make_emoji_dict(self):
-        """
-        Convert emoji lexicon file to a dictionary
-        """
-        emoji_dict = {}
-        for line in self.emoji_full_filepath.split('\n'):
-            (emoji, description) = line.strip().split('\t')[0:2]
-            emoji_dict[emoji] = description
-        return emoji_dict
-
-    def polarity_scores(self, text):
-        """
-        Return a float for sentiment strength based on the input text.
-        Positive values are positive valence, negative value are negative
-        valence.
-        """
-        # convert emojis to their textual descriptions
-        text_token_list = text.split()
-        text_no_emoji_lst = []
-        for token in text_token_list:
-            if token in self.emojis:
-                # get the textual description
-                description = self.emojis[token]
-                text_no_emoji_lst.append(description)
-            else:
-                text_no_emoji_lst.append(token)
-        text = " ".join(x for x in text_no_emoji_lst)
-
-        sentitext = SentiText(text)
-
-        sentiments = []
-        words_and_emoticons = sentitext.words_and_emoticons
-        for item in words_and_emoticons:
-            valence = 0
-            i = words_and_emoticons.index(item)
-            # check for vader_lexicon words that may be used as modifiers or negations
-            if item.lower() in BOOSTER_DICT:
-                sentiments.append(valence)
-                continue
-            if (i < len(words_and_emoticons) - 1 and item.lower() == "kind" and
-                    words_and_emoticons[i + 1].lower() == "of"):
-                sentiments.append(valence)
-                continue
-
-            sentiments = self.sentiment_valence(valence, sentitext, item, i, sentiments)
-
-        sentiments = self._but_check(words_and_emoticons, sentiments)
-
-        valence_dict = self.score_valence(sentiments, text)
-
-        return valence_dict
-
-    def sentiment_valence(self, valence, sentitext, item, i, sentiments):
-        is_cap_diff = sentitext.is_cap_diff
-        words_and_emoticons = sentitext.words_and_emoticons
-        item_lowercase = item.lower()
-        if item_lowercase in self.lexicon:
-            # get the sentiment valence
-            valence = self.lexicon[item_lowercase]
-            # check if sentiment laden word is in ALL CAPS (while others aren't)
-            if item.isupper() and is_cap_diff:
-                if valence > 0:
-                    valence += C_INCR
-                else:
-                    valence -= C_INCR
-
-            for start_i in range(0, 3):
-                # dampen the scalar modifier of preceding words and emoticons
-                # (excluding the ones that immediately preceed the item) based
-                # on their distance from the current item.
-                if i > start_i and words_and_emoticons[i - (start_i + 1)].lower() not in self.lexicon:
-                    s = scalar_inc_dec(words_and_emoticons[i - (start_i + 1)], valence, is_cap_diff)
-                    if start_i == 1 and s != 0:
-                        s = s * 0.95
-                    if start_i == 2 and s != 0:
-                        s = s * 0.9
-                    valence = valence + s
-                    valence = self._negation_check(valence, words_and_emoticons, start_i, i)
-                    if start_i == 2:
-                        valence = self._special_idioms_check(valence, words_and_emoticons, i)
-
-            valence = self._least_check(valence, words_and_emoticons, i)
-        sentiments.append(valence)
-        return sentiments
-
-    def _least_check(self, valence, words_and_emoticons, i):
-        # check for negation case using "least"
-        if i > 1 and words_and_emoticons[i - 1].lower() not in self.lexicon \
-                and words_and_emoticons[i - 1].lower() == "least":
-            if words_and_emoticons[i - 2].lower() != "at" and words_and_emoticons[i - 2].lower() != "very":
-                valence = valence * N_SCALAR
-        elif i > 0 and words_and_emoticons[i - 1].lower() not in self.lexicon \
-                and words_and_emoticons[i - 1].lower() == "least":
-            valence = valence * N_SCALAR
-        return valence
-
-    @staticmethod
-    def _but_check(words_and_emoticons, sentiments):
-        # check for modification in sentiment due to contrastive conjunction 'but'
-        words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons]
-        if 'but' in words_and_emoticons_lower:
-            bi = words_and_emoticons_lower.index('but')
-            for sentiment in sentiments:
-                si = sentiments.index(sentiment)
-                if si < bi:
-                    sentiments.pop(si)
-                    sentiments.insert(si, sentiment * 0.5)
-                elif si > bi:
-                    sentiments.pop(si)
-                    sentiments.insert(si, sentiment * 1.5)
-        return sentiments
-
-    @staticmethod
-    def _special_idioms_check(valence, words_and_emoticons, i):
-        words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons]
-        onezero = "{0} {1}".format(words_and_emoticons_lower[i - 1], words_and_emoticons_lower[i])
-
-        twoonezero = "{0} {1} {2}".format(words_and_emoticons_lower[i - 2],
-                                          words_and_emoticons_lower[i - 1], words_and_emoticons_lower[i])
-
-        twoone = "{0} {1}".format(words_and_emoticons_lower[i - 2], words_and_emoticons_lower[i - 1])
-
-        threetwoone = "{0} {1} {2}".format(words_and_emoticons_lower[i - 3],
-                                           words_and_emoticons_lower[i - 2], words_and_emoticons_lower[i - 1])
-
-        threetwo = "{0} {1}".format(words_and_emoticons_lower[i - 3], words_and_emoticons_lower[i - 2])
-
-        sequences = [onezero, twoonezero, twoone, threetwoone, threetwo]
-
-        for seq in sequences:
-            if seq in SPECIAL_CASE_IDIOMS:
-                valence = SPECIAL_CASE_IDIOMS[seq]
-                break
-
-        if len(words_and_emoticons_lower) - 1 > i:
-            zeroone = "{0} {1}".format(words_and_emoticons_lower[i], words_and_emoticons_lower[i + 1])
-            if zeroone in SPECIAL_CASE_IDIOMS:
-                valence = SPECIAL_CASE_IDIOMS[zeroone]
-        if len(words_and_emoticons_lower) - 1 > i + 1:
-            zeroonetwo = "{0} {1} {2}".format(words_and_emoticons_lower[i], words_and_emoticons_lower[i + 1],
-                                              words_and_emoticons_lower[i + 2])
-            if zeroonetwo in SPECIAL_CASE_IDIOMS:
-                valence = SPECIAL_CASE_IDIOMS[zeroonetwo]
-
-        # check for booster/dampener bi-grams such as 'sort of' or 'kind of'
-        n_grams = [threetwoone, threetwo, twoone]
-        for n_gram in n_grams:
-            if n_gram in BOOSTER_DICT:
-                valence = valence + BOOSTER_DICT[n_gram]
-        return valence
-
-    @staticmethod
-    def _sentiment_laden_idioms_check(valence, senti_text_lower):
-        # Future Work
-        # check for sentiment laden idioms that don't contain a lexicon word
-        idioms_valences = []
-        for idiom in SENTIMENT_LADEN_IDIOMS:
-            if idiom in senti_text_lower:
-                print(idiom, senti_text_lower)
-                valence = SENTIMENT_LADEN_IDIOMS[idiom]
-                idioms_valences.append(valence)
-        if len(idioms_valences) > 0:
-            valence = sum(idioms_valences) / float(len(idioms_valences))
-        return valence
-
-    @staticmethod
-    def _negation_check(valence, words_and_emoticons, start_i, i):
-        words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons]
-        if start_i == 0:
-            if negated([words_and_emoticons_lower[i - (start_i + 1)]]):  # 1 word preceding lexicon word (w/o stopwords)
-                valence = valence * N_SCALAR
-        if start_i == 1:
-            if words_and_emoticons_lower[i - 2] == "never" and \
-                    (words_and_emoticons_lower[i - 1] == "so" or
-                     words_and_emoticons_lower[i - 1] == "this"):
-                valence = valence * 1.25
-            elif words_and_emoticons_lower[i - 2] == "without" and \
-                    words_and_emoticons_lower[i - 1] == "doubt":
-                valence = valence
-            elif negated([words_and_emoticons_lower[i - (start_i + 1)]]):  # 2 words preceding the lexicon word position
-                valence = valence * N_SCALAR
-        if start_i == 2:
-            if words_and_emoticons_lower[i - 3] == "never" and \
-                    (words_and_emoticons_lower[i - 2] == "so" or words_and_emoticons_lower[i - 2] == "this") or \
-                    (words_and_emoticons_lower[i - 1] == "so" or words_and_emoticons_lower[i - 1] == "this"):
-                valence = valence * 1.25
-            elif words_and_emoticons_lower[i - 3] == "without" and \
-                    (words_and_emoticons_lower[i - 2] == "doubt" or words_and_emoticons_lower[i - 1] == "doubt"):
-                valence = valence
-            elif negated([words_and_emoticons_lower[i - (start_i + 1)]]):  # 3 words preceding the lexicon word position
-                valence = valence * N_SCALAR
-        return valence
-
-    def _punctuation_emphasis(self, text):
-        # add emphasis from exclamation points and question marks
-        ep_amplifier = self._amplify_ep(text)
-        qm_amplifier = self._amplify_qm(text)
-        punct_emph_amplifier = ep_amplifier + qm_amplifier
-        return punct_emph_amplifier
-
-    @staticmethod
-    def _amplify_ep(text):
-        # check for added emphasis resulting from exclamation points (up to 4 of them)
-        ep_count = text.count("!")
-        if ep_count > 4:
-            ep_count = 4
-        # (empirically derived mean sentiment intensity rating increase for
-        # exclamation points)
-        ep_amplifier = ep_count * 0.292
-        return ep_amplifier
-
-    @staticmethod
-    def _amplify_qm(text):
-        # check for added emphasis resulting from question marks (2 or 3+)
-        qm_count = text.count("?")
-        qm_amplifier = 0
-        if qm_count > 1:
-            if qm_count <= 3:
-                # (empirically derived mean sentiment intensity rating increase for
-                # question marks)
-                qm_amplifier = qm_count * 0.18
-            else:
-                qm_amplifier = 0.96
-        return qm_amplifier
-
-    @staticmethod
-    def _sift_sentiment_scores(sentiments):
-        # want separate positive versus negative sentiment scores
-        pos_sum = 0.0
-        neg_sum = 0.0
-        neu_count = 0
-        for sentiment_score in sentiments:
-            if sentiment_score > 0:
-                pos_sum += (float(sentiment_score) + 1)  # compensates for neutral words that are counted as 1
-            if sentiment_score < 0:
-                neg_sum += (float(sentiment_score) - 1)  # when used with math.fabs(), compensates for neutrals
-            if sentiment_score == 0:
-                neu_count += 1
-        return pos_sum, neg_sum, neu_count
-
-    def score_valence(self, sentiments, text):
-        if sentiments:
-            sum_s = float(sum(sentiments))
-            # compute and add emphasis from punctuation in text
-            punct_emph_amplifier = self._punctuation_emphasis(text)
-            if sum_s > 0:
-                sum_s += punct_emph_amplifier
-            elif sum_s < 0:
-                sum_s -= punct_emph_amplifier
-
-            compound = normalize(sum_s)
-            # discriminate between positive, negative and neutral sentiment scores
-            pos_sum, neg_sum, neu_count = self._sift_sentiment_scores(sentiments)
-
-            if pos_sum > math.fabs(neg_sum):
-                pos_sum += punct_emph_amplifier
-            elif pos_sum < math.fabs(neg_sum):
-                neg_sum -= punct_emph_amplifier
-
-            total = pos_sum + math.fabs(neg_sum) + neu_count
-            pos = math.fabs(pos_sum / total)
-            neg = math.fabs(neg_sum / total)
-            neu = math.fabs(neu_count / total)
-
-        else:
-            compound = 0.0
-            pos = 0.0
-            neg = 0.0
-            neu = 0.0
-
-        sentiment_dict = \
-            {"neg": round(neg, 3),
-             "neu": round(neu, 3),
-             "pos": round(pos, 3),
-             "compound": round(compound, 4)}
-
-        return sentiment_dict
-
-
-if __name__ == '__main__':
-    # --- examples -------
-    sentences = ["VADER is smart, handsome, and funny.",  # positive sentence example
-                 "VADER is smart, handsome, and funny!",
-                 # punctuation emphasis handled correctly (sentiment intensity adjusted)
-                 "VADER is very smart, handsome, and funny.",
-                 # booster words handled correctly (sentiment intensity adjusted)
-                 "VADER is VERY SMART, handsome, and FUNNY.",  # emphasis for ALLCAPS handled
-                 "VADER is VERY SMART, handsome, and FUNNY!!!",
-                 # combination of signals - VADER appropriately adjusts intensity
-                 "VADER is VERY SMART, uber handsome, and FRIGGIN FUNNY!!!",
-                 # booster words & punctuation make this close to ceiling for score
-                 "VADER is not smart, handsome, nor funny.",  # negation sentence example
-                 "The book was good.",  # positive sentence
-                 "At least it isn't a horrible book.",  # negated negative sentence with contraction
-                 "The book was only kind of good.",
-                 # qualified positive sentence is handled correctly (intensity adjusted)
-                 "The plot was good, but the characters are uncompelling and the dialog is not great.",
-                 # mixed negation sentence
-                 "Today SUX!",  # negative slang with capitalization emphasis
-                 "Today only kinda sux! But I'll get by, lol",
-                 # mixed sentiment example with slang and constrastive conjunction "but"
-                 "Make sure you :) or :D today!",  # emoticons handled
-                 "Catch utf-8 emoji such as 💘 and 💋 and 😁",  # emojis handled
-                 "Not bad at all"  # Capitalized negation
-                 ]
-
-    analyzer = SentimentIntensityAnalyzer()
-
-    print("----------------------------------------------------")
-    print(" - Analyze typical example cases, including handling of:")
-    print("  -- negations")
-    print("  -- punctuation emphasis & punctuation flooding")
-    print("  -- word-shape as emphasis (capitalization difference)")
-    print("  -- degree modifiers (intensifiers such as 'very' and dampeners such as 'kind of')")
-    print("  -- slang words as modifiers such as 'uber' or 'friggin' or 'kinda'")
-    print("  -- contrastive conjunction 'but' indicating a shift in sentiment; sentiment of later text is dominant")
-    print("  -- use of contractions as negations")
-    print("  -- sentiment laden emoticons such as :) and :D")
-    print("  -- utf-8 encoded emojis such as 💘 and 💋 and 😁")
-    print("  -- sentiment laden slang words (e.g., 'sux')")
-    print("  -- sentiment laden initialisms and acronyms (for example: 'lol') \n")
-    for sentence in sentences:
-        vs = analyzer.polarity_scores(sentence)
-        print("{:-<65} {}".format(sentence, str(vs)))
-    print("----------------------------------------------------")
-    print(" - About the scoring: ")
-    print("""  -- The 'compound' score is computed by summing the valence scores of each word in the lexicon, adjusted 
-     according to the rules, and then normalized to be between -1 (most extreme negative) and +1 (most extreme positive). 
-     This is the most useful metric if you want a single unidimensional measure of sentiment for a given sentence.  
-     Calling it a 'normalized, weighted composite score' is accurate.""")
-    print("""  -- The 'pos', 'neu', and 'neg' scores are ratios for proportions of text that fall in each category (so these   
-     should all add up to be 1... or close to it with float operation).  These are the most useful metrics if 
-     you want multidimensional measures of sentiment for a given sentence.""")
-    print("----------------------------------------------------")
-
-    # input("\nPress Enter to continue the demo...\n")  # for DEMO purposes...
-
-    tricky_sentences = ["Sentiment analysis has never been good.",
-                        "Sentiment analysis has never been this good!",
-                        "Most automated sentiment analysis tools are shit.",
-                        "With VADER, sentiment analysis is the shit!",
-                        "Other sentiment analysis tools can be quite bad.",
-                        "On the other hand, VADER is quite bad ass",
-                        "VADER is such a badass!",  # slang with punctuation emphasis
-                        "Without a doubt, excellent idea.",
-                        "Roger Dodger is one of the most compelling variations on this theme.",
-                        "Roger Dodger is at least compelling as a variation on the theme.",
-                        "Roger Dodger is one of the least compelling variations on this theme.",
-                        "Not such a badass after all.",  # Capitalized negation with slang
-                        "Without a doubt, an excellent idea."  # "without {any} doubt" as negation
-                        ]
-    print("----------------------------------------------------")
-    print(" - Analyze examples of tricky sentences that cause trouble to other sentiment analysis tools.")
-    print("  -- special case idioms - e.g., 'never good' vs 'never this good', or 'bad' vs 'bad ass'.")
-    print("  -- special uses of 'least' as negation versus comparison \n")
-    for sentence in tricky_sentences:
-        vs = analyzer.polarity_scores(sentence)
-        print("{:-<69} {}".format(sentence, str(vs)))
-    print("----------------------------------------------------")
-
-    # input("\nPress Enter to continue the demo...\n")  # for DEMO purposes...
-
-    print("----------------------------------------------------")
-    print(
-        " - VADER works best when analysis is done at the sentence level (but it can work on single words or entire novels).")
-    paragraph = "It was one of the worst movies I've seen, despite good reviews. Unbelievably bad acting!! Poor direction. VERY poor production. The movie was bad. Very bad movie. VERY BAD movie!"
-    print("  -- For example, given the following paragraph text from a hypothetical movie review:\n\t'{}'".format(
-        paragraph))
-    print(
-        "  -- You could use NLTK to break the paragraph into sentence tokens for VADER, then average the results for the paragraph like this: \n")
-    # simple example to tokenize paragraph into sentences for VADER
-    from nltk import tokenize
-
-    sentence_list = tokenize.sent_tokenize(paragraph)
-    paragraphSentiments = 0.0
-    for sentence in sentence_list:
-        vs = analyzer.polarity_scores(sentence)
-        print("{:-<69} {}".format(sentence, str(vs["compound"])))
-        paragraphSentiments += vs["compound"]
-    print("AVERAGE SENTIMENT FOR PARAGRAPH: \t" + str(round(paragraphSentiments / len(sentence_list), 4)))
-    print("----------------------------------------------------")
-
-    # input("\nPress Enter to continue the demo...\n")  # for DEMO purposes...
-
-    print("----------------------------------------------------")
-    print(" - Analyze sentiment of IMAGES/VIDEO data based on annotation 'tags' or image labels. \n")
-    conceptList = ["balloons", "cake", "candles", "happy birthday", "friends", "laughing", "smiling", "party"]
-    conceptSentiments = 0.0
-    for concept in conceptList:
-        vs = analyzer.polarity_scores(concept)
-        print("{:-<15} {}".format(concept, str(vs['compound'])))
-        conceptSentiments += vs["compound"]
-    print("AVERAGE SENTIMENT OF TAGS/LABELS: \t" + str(round(conceptSentiments / len(conceptList), 4)))
-    print("\t")
-    conceptList = ["riot", "fire", "fight", "blood", "mob", "war", "police", "tear gas"]
-    conceptSentiments = 0.0
-    for concept in conceptList:
-        vs = analyzer.polarity_scores(concept)
-        print("{:-<15} {}".format(concept, str(vs['compound'])))
-        conceptSentiments += vs["compound"]
-    print("AVERAGE SENTIMENT OF TAGS/LABELS: \t" + str(round(conceptSentiments / len(conceptList), 4)))
-    print("----------------------------------------------------")
-
-    # input("\nPress Enter to continue the demo...")  # for DEMO purposes...
-
-    do_translate = input(
-        "\nWould you like to run VADER demo examples with NON-ENGLISH text? (Note: requires Internet access) \n Type 'y' or 'n', then press Enter: ")
-    if do_translate.lower().lstrip().__contains__("y"):
-        print("\n----------------------------------------------------")
-        print(" - Analyze sentiment of NON ENGLISH text...for example:")
-        print("  -- French, German, Spanish, Italian, Russian, Japanese, Arabic, Chinese")
-        print("  -- many other languages supported. \n")
-        languages = ["English", "French", "German", "Spanish", "Italian", "Russian", "Japanese", "Arabic", "Chinese"]
-        language_codes = ["en", "fr", "de", "es", "it", "ru", "ja", "ar", "zh"]
-        nonEnglish_sentences = ["I'm surprised to see just how amazingly helpful VADER is!",
-                                "Je suis surpris de voir juste comment incroyablement utile VADER est!",
-                                "Ich bin überrascht zu sehen, nur wie erstaunlich nützlich VADER!",
-                                "Me sorprende ver sólo cómo increíblemente útil VADER!",
-                                "Sono sorpreso di vedere solo come incredibilmente utile VADER è!",
-                                "Я удивлен увидеть, как раз как удивительно полезно ВЕЙДЕРА!",
-                                "私はちょうどどのように驚くほど役に立つベイダーを見て驚いています!",
-                                "أنا مندهش لرؤية فقط كيف مثير للدهشة فيدر فائدة!",
-                                "惊讶地看到有用维德是的只是如何令人惊讶了 ！"
-                                ]
-        for sentence in nonEnglish_sentences:
-            to_lang = "en"
-            from_lang = language_codes[nonEnglish_sentences.index(sentence)]
-            if (from_lang == "en") or (from_lang == "en-US"):
-                translation = sentence
-                translator_name = "No translation needed"
-            else:  # please note usage limits for My Memory Translation Service:   http://mymemory.translated.net/doc/usagelimits.php
-                # using   MY MEMORY NET   http://mymemory.translated.net
-                api_url = "http://mymemory.translated.net/api/get?q={}&langpair={}|{}".format(sentence, from_lang,
-                                                                                              to_lang)
-                hdrs = {
-                    'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
-                    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
-                    'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
-                    'Accept-Encoding': 'none',
-                    'Accept-Language': 'en-US,en;q=0.8',
-                    'Connection': 'keep-alive'}
-                response = requests.get(api_url, headers=hdrs)
-                response_json = json.loads(response.text)
-                translation = response_json["responseData"]["translatedText"]
-                translator_name = "MemoryNet Translation Service"
-            vs = analyzer.polarity_scores(translation)
-            print("- {: <8}: {: <69}\t {} ({})".format(languages[nonEnglish_sentences.index(sentence)], sentence,
-                                                       str(vs['compound']), translator_name))
-        print("----------------------------------------------------")
-
-    print("\n\n Demo Done!")
+# coding: utf-8
+# Author: C.J. Hutto
+# Thanks to George Berry for reducing the time complexity from something like O(N^4) to O(N).
+# Thanks to Ewan Klein and Pierpaolo Pantone for bringing VADER into NLTK. Those modifications were awesome.
+# For license information, see LICENSE.TXT
+
+"""
+If you use the VADER sentiment analysis tools, please cite:
+Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for
+Sentiment Analysis of Social Media Text. Eighth International Conference on
+Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.
+"""
+import os
+import re
+import math
+import string
+import requests
+import json
+from itertools import product
+from inspect import getsourcefile
+
+# ##Constants##
+
+# (empirically derived mean sentiment intensity rating increase for booster words)
+B_INCR = 0.293
+B_DECR = -0.293
+
+# (empirically derived mean sentiment intensity rating increase for using ALLCAPs to emphasize a word)
+C_INCR = 0.733
+N_SCALAR = -0.74
+
+# for removing punctuation
+REGEX_REMOVE_PUNCTUATION = re.compile('[%s]' % re.escape(string.punctuation))
+
+PUNC_LIST = [".", "!", "?", ",", ";", ":", "-", "'", "\"",
+             "!!", "!!!", "??", "???", "?!?", "!?!", "?!?!", "!?!?"]
+NEGATE = \
+    ["aint", "arent", "cannot", "cant", "couldnt", "darent", "didnt", "doesnt",
+     "ain't", "aren't", "can't", "couldn't", "daren't", "didn't", "doesn't",
+     "dont", "hadnt", "hasnt", "havent", "isnt", "mightnt", "mustnt", "neither",
+     "don't", "hadn't", "hasn't", "haven't", "isn't", "mightn't", "mustn't",
+     "neednt", "needn't", "never", "none", "nope", "nor", "not", "nothing", "nowhere",
+     "oughtnt", "shant", "shouldnt", "uhuh", "wasnt", "werent",
+     "oughtn't", "shan't", "shouldn't", "uh-uh", "wasn't", "weren't",
+     "without", "wont", "wouldnt", "won't", "wouldn't", "rarely", "seldom", "despite"]
+
+# booster/dampener 'intensifiers' or 'degree adverbs'
+# http://en.wiktionary.org/wiki/Category:English_degree_adverbs
+
+BOOSTER_DICT = \
+    {"absolutely": B_INCR, "amazingly": B_INCR, "awfully": B_INCR, "completely": B_INCR, "considerably": B_INCR,
+     "decidedly": B_INCR, "deeply": B_INCR, "effing": B_INCR, "enormously": B_INCR,
+     "entirely": B_INCR, "especially": B_INCR, "exceptionally": B_INCR, "extremely": B_INCR,
+     "fabulously": B_INCR, "flipping": B_INCR, "flippin": B_INCR,
+     "fricking": B_INCR, "frickin": B_INCR, "frigging": B_INCR, "friggin": B_INCR, "fully": B_INCR, "fucking": B_INCR,
+     "greatly": B_INCR, "hella": B_INCR, "highly": B_INCR, "hugely": B_INCR, "incredibly": B_INCR,
+     "intensely": B_INCR, "majorly": B_INCR, "more": B_INCR, "most": B_INCR, "particularly": B_INCR,
+     "purely": B_INCR, "quite": B_INCR, "really": B_INCR, "remarkably": B_INCR,
+     "so": B_INCR, "substantially": B_INCR,
+     "thoroughly": B_INCR, "totally": B_INCR, "tremendously": B_INCR,
+     "uber": B_INCR, "unbelievably": B_INCR, "unusually": B_INCR, "utterly": B_INCR,
+     "very": B_INCR,
+     "almost": B_DECR, "barely": B_DECR, "hardly": B_DECR, "just enough": B_DECR,
+     "kind of": B_DECR, "kinda": B_DECR, "kindof": B_DECR, "kind-of": B_DECR,
+     "less": B_DECR, "little": B_DECR, "marginally": B_DECR, "occasionally": B_DECR, "partly": B_DECR,
+     "scarcely": B_DECR, "slightly": B_DECR, "somewhat": B_DECR,
+     "sort of": B_DECR, "sorta": B_DECR, "sortof": B_DECR, "sort-of": B_DECR}
+
+# check for sentiment laden idioms that do not contain lexicon words (future work, not yet implemented)
+SENTIMENT_LADEN_IDIOMS = {"cut the mustard": 2, "hand to mouth": -2,
+                          "back handed": -2, "blow smoke": -2, "blowing smoke": -2,
+                          "upper hand": 1, "break a leg": 2,
+                          "cooking with gas": 2, "in the black": 2, "in the red": -2,
+                          "on the ball": 2, "under the weather": -2, "Bull Market": 2.3,
+                          "All time high": 2.3, "Trading analysis": 1, "Short squeeze": 0.6,
+                          "Closing a long": 1.6, "Closing a short": -0.1, "Opening a long": 1.3,
+                          "Opening a short": 0.9, "flip a coin": 0.6}
+
+# check for special case idioms containing lexicon words
+SPECIAL_CASE_IDIOMS = {"the shit": 3, "the bomb": 3, "bad ass": 1.5, "yeah right": -2,
+                       "kiss of death": -1.5}
+
+
+# #Static methods# #
+
+def negated(input_words, include_nt=True):
+    """
+    Determine if input contains negation words
+    """
+    input_words = [str(w).lower() for w in input_words]
+    neg_words = []
+    neg_words.extend(NEGATE)
+    for word in neg_words:
+        if word in input_words:
+            return True
+    if include_nt:
+        for word in input_words:
+            if "n't" in word:
+                return True
+    if "least" in input_words:
+        i = input_words.index("least")
+        if i > 0 and input_words[i - 1] != "at":
+            return True
+    return False
+
+
+def normalize(score, alpha=15):
+    """
+    Normalize the score to be between -1 and 1 using an alpha that
+    approximates the max expected value
+    """
+    norm_score = score / math.sqrt((score * score) + alpha)
+    if norm_score < -1.0:
+        return -1.0
+    elif norm_score > 1.0:
+        return 1.0
+    else:
+        return norm_score
+
+
+def allcap_differential(words):
+    """
+    Check whether just some words in the input are ALL CAPS
+    :param list words: The words to inspect
+    :returns: `True` if some but not all items in `words` are ALL CAPS
+    """
+    is_different = False
+    allcap_words = 0
+    for word in words:
+        if word.isupper():
+            allcap_words += 1
+    cap_differential = len(words) - allcap_words
+    if 0 < cap_differential < len(words):
+        is_different = True
+    return is_different
+
+
+def scalar_inc_dec(word, valence, is_cap_diff):
+    """
+    Check if the preceding words increase, decrease, or negate/nullify the
+    valence
+    """
+    scalar = 0.0
+    word_lower = word.lower()
+    if word_lower in BOOSTER_DICT:
+        scalar = BOOSTER_DICT[word_lower]
+        if valence < 0:
+            scalar *= -1
+        # check if booster/dampener word is in ALLCAPS (while others aren't)
+        if word.isupper() and is_cap_diff:
+            if valence > 0:
+                scalar += C_INCR
+            else:
+                scalar -= C_INCR
+    return scalar
+
+
+class SentiText(object):
+    """
+    Identify sentiment-relevant string-level properties of input text.
+    """
+
+    def __init__(self, text):
+        if not isinstance(text, str):
+            text = str(text).encode('utf-8')
+        self.text = text
+        self.words_and_emoticons = self._words_and_emoticons()
+        # doesn't separate words from\
+        # adjacent punctuation (keeps emoticons & contractions)
+        self.is_cap_diff = allcap_differential(self.words_and_emoticons)
+
+    def _words_plus_punc(self):
+        """
+        Returns mapping of form:
+        {
+            'cat,': 'cat',
+            ',cat': 'cat',
+        }
+        """
+        no_punc_text = REGEX_REMOVE_PUNCTUATION.sub('', self.text)
+        # removes punctuation (but loses emoticons & contractions)
+        words_only = no_punc_text.split()
+        # remove singletons
+        words_only = set(w for w in words_only if len(w) > 1)
+        # the product gives ('cat', ',') and (',', 'cat')
+        punc_before = {''.join(p): p[1] for p in product(PUNC_LIST, words_only)}
+        punc_after = {''.join(p): p[0] for p in product(words_only, PUNC_LIST)}
+        words_punc_dict = punc_before
+        words_punc_dict.update(punc_after)
+        return words_punc_dict
+
+    def _words_and_emoticons(self):
+        """
+        Removes leading and trailing puncutation
+        Leaves contractions and most emoticons
+            Does not preserve punc-plus-letter emoticons (e.g. :D)
+        """
+        wes = self.text.split()
+        words_punc_dict = self._words_plus_punc()
+        wes = [we for we in wes if len(we) > 1]
+        for i, we in enumerate(wes):
+            if we in words_punc_dict:
+                wes[i] = words_punc_dict[we]
+        return wes
+
+
+class SentimentIntensityAnalyzer(object):
+    """
+    Give a sentiment intensity score to sentences.
+    """
+
+    def __init__(self, lexicon_file="vader_lexicon.txt", emoji_lexicon="emoji_utf8_lexicon.txt"):
+        _this_module_file_path_ = os.path.abspath(getsourcefile(lambda: 0))
+        lexicon_full_filepath = os.path.join(os.path.dirname(_this_module_file_path_), lexicon_file)
+        with open(lexicon_full_filepath, encoding='utf-8') as f:
+            self.lexicon_full_filepath = f.read()
+        self.lexicon = self.make_lex_dict()
+
+        emoji_full_filepath = os.path.join(os.path.dirname(_this_module_file_path_), emoji_lexicon)
+        with open(emoji_full_filepath, encoding='utf-8') as f:
+            self.emoji_full_filepath = f.read()
+        self.emojis = self.make_emoji_dict()
+
+    def make_lex_dict(self):
+        """
+        Convert lexicon file to a dictionary
+        """
+        lex_dict = {}
+        for line in self.lexicon_full_filepath.split('\n'):
+            (word, measure) = line.strip().split('\t')[0:2]
+            lex_dict[word] = float(measure)
+        return lex_dict
+
+    def make_emoji_dict(self):
+        """
+        Convert emoji lexicon file to a dictionary
+        """
+        emoji_dict = {}
+        for line in self.emoji_full_filepath.split('\n'):
+            (emoji, description) = line.strip().split('\t')[0:2]
+            emoji_dict[emoji] = description
+        return emoji_dict
+
+    def polarity_scores(self, text):
+        """
+        Return a float for sentiment strength based on the input text.
+        Positive values are positive valence, negative value are negative
+        valence.
+        """
+        # convert emojis to their textual descriptions
+        text_token_list = text.split()
+        text_no_emoji_lst = []
+        for token in text_token_list:
+            if token in self.emojis:
+                # get the textual description
+                description = self.emojis[token]
+                text_no_emoji_lst.append(description)
+            else:
+                text_no_emoji_lst.append(token)
+        text = " ".join(x for x in text_no_emoji_lst)
+
+        sentitext = SentiText(text)
+
+        sentiments = []
+        words_and_emoticons = sentitext.words_and_emoticons
+        for item in words_and_emoticons:
+            valence = 0
+            i = words_and_emoticons.index(item)
+            # check for vader_lexicon words that may be used as modifiers or negations
+            if item.lower() in BOOSTER_DICT:
+                sentiments.append(valence)
+                continue
+            if (i < len(words_and_emoticons) - 1 and item.lower() == "kind" and
+                    words_and_emoticons[i + 1].lower() == "of"):
+                sentiments.append(valence)
+                continue
+
+            sentiments = self.sentiment_valence(valence, sentitext, item, i, sentiments)
+
+        sentiments = self._but_check(words_and_emoticons, sentiments)
+
+        valence_dict = self.score_valence(sentiments, text)
+
+        return valence_dict
+
+    def sentiment_valence(self, valence, sentitext, item, i, sentiments):
+        is_cap_diff = sentitext.is_cap_diff
+        words_and_emoticons = sentitext.words_and_emoticons
+        item_lowercase = item.lower()
+        if item_lowercase in self.lexicon:
+            # get the sentiment valence
+            valence = self.lexicon[item_lowercase]
+            # check if sentiment laden word is in ALL CAPS (while others aren't)
+            if item.isupper() and is_cap_diff:
+                if valence > 0:
+                    valence += C_INCR
+                else:
+                    valence -= C_INCR
+
+            for start_i in range(0, 3):
+                # dampen the scalar modifier of preceding words and emoticons
+                # (excluding the ones that immediately preceed the item) based
+                # on their distance from the current item.
+                if i > start_i and words_and_emoticons[i - (start_i + 1)].lower() not in self.lexicon:
+                    s = scalar_inc_dec(words_and_emoticons[i - (start_i + 1)], valence, is_cap_diff)
+                    if start_i == 1 and s != 0:
+                        s = s * 0.95
+                    if start_i == 2 and s != 0:
+                        s = s * 0.9
+                    valence = valence + s
+                    valence = self._negation_check(valence, words_and_emoticons, start_i, i)
+                    if start_i == 2:
+                        valence = self._special_idioms_check(valence, words_and_emoticons, i)
+
+            valence = self._least_check(valence, words_and_emoticons, i)
+        sentiments.append(valence)
+        return sentiments
+
+    def _least_check(self, valence, words_and_emoticons, i):
+        # check for negation case using "least"
+        if i > 1 and words_and_emoticons[i - 1].lower() not in self.lexicon \
+                and words_and_emoticons[i - 1].lower() == "least":
+            if words_and_emoticons[i - 2].lower() != "at" and words_and_emoticons[i - 2].lower() != "very":
+                valence = valence * N_SCALAR
+        elif i > 0 and words_and_emoticons[i - 1].lower() not in self.lexicon \
+                and words_and_emoticons[i - 1].lower() == "least":
+            valence = valence * N_SCALAR
+        return valence
+
+    @staticmethod
+    def _but_check(words_and_emoticons, sentiments):
+        # check for modification in sentiment due to contrastive conjunction 'but'
+        words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons]
+        if 'but' in words_and_emoticons_lower:
+            bi = words_and_emoticons_lower.index('but')
+            for sentiment in sentiments:
+                si = sentiments.index(sentiment)
+                if si < bi:
+                    sentiments.pop(si)
+                    sentiments.insert(si, sentiment * 0.5)
+                elif si > bi:
+                    sentiments.pop(si)
+                    sentiments.insert(si, sentiment * 1.5)
+        return sentiments
+
+    @staticmethod
+    def _special_idioms_check(valence, words_and_emoticons, i):
+        words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons]
+        onezero = "{0} {1}".format(words_and_emoticons_lower[i - 1], words_and_emoticons_lower[i])
+
+        twoonezero = "{0} {1} {2}".format(words_and_emoticons_lower[i - 2],
+                                          words_and_emoticons_lower[i - 1], words_and_emoticons_lower[i])
+
+        twoone = "{0} {1}".format(words_and_emoticons_lower[i - 2], words_and_emoticons_lower[i - 1])
+
+        threetwoone = "{0} {1} {2}".format(words_and_emoticons_lower[i - 3],
+                                           words_and_emoticons_lower[i - 2], words_and_emoticons_lower[i - 1])
+
+        threetwo = "{0} {1}".format(words_and_emoticons_lower[i - 3], words_and_emoticons_lower[i - 2])
+
+        sequences = [onezero, twoonezero, twoone, threetwoone, threetwo]
+
+        for seq in sequences:
+            if seq in SPECIAL_CASE_IDIOMS:
+                valence = SPECIAL_CASE_IDIOMS[seq]
+                break
+
+        if len(words_and_emoticons_lower) - 1 > i:
+            zeroone = "{0} {1}".format(words_and_emoticons_lower[i], words_and_emoticons_lower[i + 1])
+            if zeroone in SPECIAL_CASE_IDIOMS:
+                valence = SPECIAL_CASE_IDIOMS[zeroone]
+        if len(words_and_emoticons_lower) - 1 > i + 1:
+            zeroonetwo = "{0} {1} {2}".format(words_and_emoticons_lower[i], words_and_emoticons_lower[i + 1],
+                                              words_and_emoticons_lower[i + 2])
+            if zeroonetwo in SPECIAL_CASE_IDIOMS:
+                valence = SPECIAL_CASE_IDIOMS[zeroonetwo]
+
+        # check for booster/dampener bi-grams such as 'sort of' or 'kind of'
+        n_grams = [threetwoone, threetwo, twoone]
+        for n_gram in n_grams:
+            if n_gram in BOOSTER_DICT:
+                valence = valence + BOOSTER_DICT[n_gram]
+        return valence
+
+    @staticmethod
+    def _sentiment_laden_idioms_check(valence, senti_text_lower):
+        # Future Work
+        # check for sentiment laden idioms that don't contain a lexicon word
+        idioms_valences = []
+        for idiom in SENTIMENT_LADEN_IDIOMS:
+            if idiom in senti_text_lower:
+                print(idiom, senti_text_lower)
+                valence = SENTIMENT_LADEN_IDIOMS[idiom]
+                idioms_valences.append(valence)
+        if len(idioms_valences) > 0:
+            valence = sum(idioms_valences) / float(len(idioms_valences))
+        return valence
+
+    @staticmethod
+    def _negation_check(valence, words_and_emoticons, start_i, i):
+        words_and_emoticons_lower = [str(w).lower() for w in words_and_emoticons]
+        if start_i == 0:
+            if negated([words_and_emoticons_lower[i - (start_i + 1)]]):  # 1 word preceding lexicon word (w/o stopwords)
+                valence = valence * N_SCALAR
+        if start_i == 1:
+            if words_and_emoticons_lower[i - 2] == "never" and \
+                    (words_and_emoticons_lower[i - 1] == "so" or
+                     words_and_emoticons_lower[i - 1] == "this"):
+                valence = valence * 1.25
+            elif words_and_emoticons_lower[i - 2] == "without" and \
+                    words_and_emoticons_lower[i - 1] == "doubt":
+                valence = valence
+            elif negated([words_and_emoticons_lower[i - (start_i + 1)]]):  # 2 words preceding the lexicon word position
+                valence = valence * N_SCALAR
+        if start_i == 2:
+            if words_and_emoticons_lower[i - 3] == "never" and \
+                    (words_and_emoticons_lower[i - 2] == "so" or words_and_emoticons_lower[i - 2] == "this") or \
+                    (words_and_emoticons_lower[i - 1] == "so" or words_and_emoticons_lower[i - 1] == "this"):
+                valence = valence * 1.25
+            elif words_and_emoticons_lower[i - 3] == "without" and \
+                    (words_and_emoticons_lower[i - 2] == "doubt" or words_and_emoticons_lower[i - 1] == "doubt"):
+                valence = valence
+            elif negated([words_and_emoticons_lower[i - (start_i + 1)]]):  # 3 words preceding the lexicon word position
+                valence = valence * N_SCALAR
+        return valence
+
+    def _punctuation_emphasis(self, text):
+        # add emphasis from exclamation points and question marks
+        ep_amplifier = self._amplify_ep(text)
+        qm_amplifier = self._amplify_qm(text)
+        punct_emph_amplifier = ep_amplifier + qm_amplifier
+        return punct_emph_amplifier
+
+    @staticmethod
+    def _amplify_ep(text):
+        # check for added emphasis resulting from exclamation points (up to 4 of them)
+        ep_count = text.count("!")
+        if ep_count > 4:
+            ep_count = 4
+        # (empirically derived mean sentiment intensity rating increase for
+        # exclamation points)
+        ep_amplifier = ep_count * 0.292
+        return ep_amplifier
+
+    @staticmethod
+    def _amplify_qm(text):
+        # check for added emphasis resulting from question marks (2 or 3+)
+        qm_count = text.count("?")
+        qm_amplifier = 0
+        if qm_count > 1:
+            if qm_count <= 3:
+                # (empirically derived mean sentiment intensity rating increase for
+                # question marks)
+                qm_amplifier = qm_count * 0.18
+            else:
+                qm_amplifier = 0.96
+        return qm_amplifier
+
+    @staticmethod
+    def _sift_sentiment_scores(sentiments):
+        # want separate positive versus negative sentiment scores
+        pos_sum = 0.0
+        neg_sum = 0.0
+        neu_count = 0
+        for sentiment_score in sentiments:
+            if sentiment_score > 0:
+                pos_sum += (float(sentiment_score) + 1)  # compensates for neutral words that are counted as 1
+            if sentiment_score < 0:
+                neg_sum += (float(sentiment_score) - 1)  # when used with math.fabs(), compensates for neutrals
+            if sentiment_score == 0:
+                neu_count += 1
+        return pos_sum, neg_sum, neu_count
+
+    def score_valence(self, sentiments, text):
+        if sentiments:
+            sum_s = float(sum(sentiments))
+            # compute and add emphasis from punctuation in text
+            punct_emph_amplifier = self._punctuation_emphasis(text)
+            if sum_s > 0:
+                sum_s += punct_emph_amplifier
+            elif sum_s < 0:
+                sum_s -= punct_emph_amplifier
+
+            compound = normalize(sum_s)
+            # discriminate between positive, negative and neutral sentiment scores
+            pos_sum, neg_sum, neu_count = self._sift_sentiment_scores(sentiments)
+
+            if pos_sum > math.fabs(neg_sum):
+                pos_sum += punct_emph_amplifier
+            elif pos_sum < math.fabs(neg_sum):
+                neg_sum -= punct_emph_amplifier
+
+            total = pos_sum + math.fabs(neg_sum) + neu_count
+            pos = math.fabs(pos_sum / total)
+            neg = math.fabs(neg_sum / total)
+            neu = math.fabs(neu_count / total)
+
+        else:
+            compound = 0.0
+            pos = 0.0
+            neg = 0.0
+            neu = 0.0
+
+        sentiment_dict = \
+            {"neg": round(neg, 3),
+             "neu": round(neu, 3),
+             "pos": round(pos, 3),
+             "compound": round(compound, 4)}
+
+        return sentiment_dict
+
+
+if __name__ == '__main__':
+    # --- examples -------
+    sentences = ["VADER is smart, handsome, and funny.",  # positive sentence example
+                 "VADER is smart, handsome, and funny!",
+                 # punctuation emphasis handled correctly (sentiment intensity adjusted)
+                 "VADER is very smart, handsome, and funny.",
+                 # booster words handled correctly (sentiment intensity adjusted)
+                 "VADER is VERY SMART, handsome, and FUNNY.",  # emphasis for ALLCAPS handled
+                 "VADER is VERY SMART, handsome, and FUNNY!!!",
+                 # combination of signals - VADER appropriately adjusts intensity
+                 "VADER is VERY SMART, uber handsome, and FRIGGIN FUNNY!!!",
+                 # booster words & punctuation make this close to ceiling for score
+                 "VADER is not smart, handsome, nor funny.",  # negation sentence example
+                 "The book was good.",  # positive sentence
+                 "At least it isn't a horrible book.",  # negated negative sentence with contraction
+                 "The book was only kind of good.",
+                 # qualified positive sentence is handled correctly (intensity adjusted)
+                 "The plot was good, but the characters are uncompelling and the dialog is not great.",
+                 # mixed negation sentence
+                 "Today SUX!",  # negative slang with capitalization emphasis
+                 "Today only kinda sux! But I'll get by, lol",
+                 # mixed sentiment example with slang and constrastive conjunction "but"
+                 "Make sure you :) or :D today!",  # emoticons handled
+                 "Catch utf-8 emoji such as 💘 and 💋 and 😁",  # emojis handled
+                 "Not bad at all"  # Capitalized negation
+                 ]
+
+    analyzer = SentimentIntensityAnalyzer()
+
+    print("----------------------------------------------------")
+    print(" - Analyze typical example cases, including handling of:")
+    print("  -- negations")
+    print("  -- punctuation emphasis & punctuation flooding")
+    print("  -- word-shape as emphasis (capitalization difference)")
+    print("  -- degree modifiers (intensifiers such as 'very' and dampeners such as 'kind of')")
+    print("  -- slang words as modifiers such as 'uber' or 'friggin' or 'kinda'")
+    print("  -- contrastive conjunction 'but' indicating a shift in sentiment; sentiment of later text is dominant")
+    print("  -- use of contractions as negations")
+    print("  -- sentiment laden emoticons such as :) and :D")
+    print("  -- utf-8 encoded emojis such as 💘 and 💋 and 😁")
+    print("  -- sentiment laden slang words (e.g., 'sux')")
+    print("  -- sentiment laden initialisms and acronyms (for example: 'lol') \n")
+    for sentence in sentences:
+        vs = analyzer.polarity_scores(sentence)
+        print("{:-<65} {}".format(sentence, str(vs)))
+    print("----------------------------------------------------")
+    print(" - About the scoring: ")
+    print("""  -- The 'compound' score is computed by summing the valence scores of each word in the lexicon, adjusted 
+     according to the rules, and then normalized to be between -1 (most extreme negative) and +1 (most extreme positive). 
+     This is the most useful metric if you want a single unidimensional measure of sentiment for a given sentence.  
+     Calling it a 'normalized, weighted composite score' is accurate.""")
+    print("""  -- The 'pos', 'neu', and 'neg' scores are ratios for proportions of text that fall in each category (so these   
+     should all add up to be 1... or close to it with float operation).  These are the most useful metrics if 
+     you want multidimensional measures of sentiment for a given sentence.""")
+    print("----------------------------------------------------")
+
+    # input("\nPress Enter to continue the demo...\n")  # for DEMO purposes...
+
+    tricky_sentences = ["Sentiment analysis has never been good.",
+                        "Sentiment analysis has never been this good!",
+                        "Most automated sentiment analysis tools are shit.",
+                        "With VADER, sentiment analysis is the shit!",
+                        "Other sentiment analysis tools can be quite bad.",
+                        "On the other hand, VADER is quite bad ass",
+                        "VADER is such a badass!",  # slang with punctuation emphasis
+                        "Without a doubt, excellent idea.",
+                        "Roger Dodger is one of the most compelling variations on this theme.",
+                        "Roger Dodger is at least compelling as a variation on the theme.",
+                        "Roger Dodger is one of the least compelling variations on this theme.",
+                        "Not such a badass after all.",  # Capitalized negation with slang
+                        "Without a doubt, an excellent idea."  # "without {any} doubt" as negation
+                        ]
+    print("----------------------------------------------------")
+    print(" - Analyze examples of tricky sentences that cause trouble to other sentiment analysis tools.")
+    print("  -- special case idioms - e.g., 'never good' vs 'never this good', or 'bad' vs 'bad ass'.")
+    print("  -- special uses of 'least' as negation versus comparison \n")
+    for sentence in tricky_sentences:
+        vs = analyzer.polarity_scores(sentence)
+        print("{:-<69} {}".format(sentence, str(vs)))
+    print("----------------------------------------------------")
+
+    # input("\nPress Enter to continue the demo...\n")  # for DEMO purposes...
+
+    print("----------------------------------------------------")
+    print(
+        " - VADER works best when analysis is done at the sentence level (but it can work on single words or entire novels).")
+    paragraph = "It was one of the worst movies I've seen, despite good reviews. Unbelievably bad acting!! Poor direction. VERY poor production. The movie was bad. Very bad movie. VERY BAD movie!"
+    print("  -- For example, given the following paragraph text from a hypothetical movie review:\n\t'{}'".format(
+        paragraph))
+    print(
+        "  -- You could use NLTK to break the paragraph into sentence tokens for VADER, then average the results for the paragraph like this: \n")
+    # simple example to tokenize paragraph into sentences for VADER
+    from nltk import tokenize
+
+    sentence_list = tokenize.sent_tokenize(paragraph)
+    paragraphSentiments = 0.0
+    for sentence in sentence_list:
+        vs = analyzer.polarity_scores(sentence)
+        print("{:-<69} {}".format(sentence, str(vs["compound"])))
+        paragraphSentiments += vs["compound"]
+    print("AVERAGE SENTIMENT FOR PARAGRAPH: \t" + str(round(paragraphSentiments / len(sentence_list), 4)))
+    print("----------------------------------------------------")
+
+    # input("\nPress Enter to continue the demo...\n")  # for DEMO purposes...
+
+    print("----------------------------------------------------")
+    print(" - Analyze sentiment of IMAGES/VIDEO data based on annotation 'tags' or image labels. \n")
+    conceptList = ["balloons", "cake", "candles", "happy birthday", "friends", "laughing", "smiling", "party"]
+    conceptSentiments = 0.0
+    for concept in conceptList:
+        vs = analyzer.polarity_scores(concept)
+        print("{:-<15} {}".format(concept, str(vs['compound'])))
+        conceptSentiments += vs["compound"]
+    print("AVERAGE SENTIMENT OF TAGS/LABELS: \t" + str(round(conceptSentiments / len(conceptList), 4)))
+    print("\t")
+    conceptList = ["riot", "fire", "fight", "blood", "mob", "war", "police", "tear gas"]
+    conceptSentiments = 0.0
+    for concept in conceptList:
+        vs = analyzer.polarity_scores(concept)
+        print("{:-<15} {}".format(concept, str(vs['compound'])))
+        conceptSentiments += vs["compound"]
+    print("AVERAGE SENTIMENT OF TAGS/LABELS: \t" + str(round(conceptSentiments / len(conceptList), 4)))
+    print("----------------------------------------------------")
+
+    # input("\nPress Enter to continue the demo...")  # for DEMO purposes...
+
+    do_translate = input(
+        "\nWould you like to run VADER demo examples with NON-ENGLISH text? (Note: requires Internet access) \n Type 'y' or 'n', then press Enter: ")
+    if do_translate.lower().lstrip().__contains__("y"):
+        print("\n----------------------------------------------------")
+        print(" - Analyze sentiment of NON ENGLISH text...for example:")
+        print("  -- French, German, Spanish, Italian, Russian, Japanese, Arabic, Chinese")
+        print("  -- many other languages supported. \n")
+        languages = ["English", "French", "German", "Spanish", "Italian", "Russian", "Japanese", "Arabic", "Chinese"]
+        language_codes = ["en", "fr", "de", "es", "it", "ru", "ja", "ar", "zh"]
+        nonEnglish_sentences = ["I'm surprised to see just how amazingly helpful VADER is!",
+                                "Je suis surpris de voir juste comment incroyablement utile VADER est!",
+                                "Ich bin überrascht zu sehen, nur wie erstaunlich nützlich VADER!",
+                                "Me sorprende ver sólo cómo increíblemente útil VADER!",
+                                "Sono sorpreso di vedere solo come incredibilmente utile VADER è!",
+                                "Я удивлен увидеть, как раз как удивительно полезно ВЕЙДЕРА!",
+                                "私はちょうどどのように驚くほど役に立つベイダーを見て驚いています!",
+                                "أنا مندهش لرؤية فقط كيف مثير للدهشة فيدر فائدة!",
+                                "惊讶地看到有用维德是的只是如何令人惊讶了 ！"
+                                ]
+        for sentence in nonEnglish_sentences:
+            to_lang = "en"
+            from_lang = language_codes[nonEnglish_sentences.index(sentence)]
+            if (from_lang == "en") or (from_lang == "en-US"):
+                translation = sentence
+                translator_name = "No translation needed"
+            else:  # please note usage limits for My Memory Translation Service:   http://mymemory.translated.net/doc/usagelimits.php
+                # using   MY MEMORY NET   http://mymemory.translated.net
+                api_url = "http://mymemory.translated.net/api/get?q={}&langpair={}|{}".format(sentence, from_lang,
+                                                                                              to_lang)
+                hdrs = {
+                    'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
+                    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
+                    'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
+                    'Accept-Encoding': 'none',
+                    'Accept-Language': 'en-US,en;q=0.8',
+                    'Connection': 'keep-alive'}
+                response = requests.get(api_url, headers=hdrs)
+                response_json = json.loads(response.text)
+                translation = response_json["responseData"]["translatedText"]
+                translator_name = "MemoryNet Translation Service"
+            vs = analyzer.polarity_scores(translation)
+            print("- {: <8}: {: <69}\t {} ({})".format(languages[nonEnglish_sentences.index(sentence)], sentence,
+                                                       str(vs['compound']), translator_name))
+        print("----------------------------------------------------")
+
+    print("\n\n Demo Done!")
diff --git a/vaderSentiment/vader_lexicon.txt b/vaderSentiment/vader_lexicon.txt
index 3412a74..25bb4bf 100644
--- a/vaderSentiment/vader_lexicon.txt
+++ b/vaderSentiment/vader_lexicon.txt
@@ -1,7517 +1,7539 @@
-$:	-1.5	0.80623	[-1, -1, -1, -1, -3, -1, -3, -1, -2, -1]
-%)	-0.4	1.0198	[-1, 0, -1, 0, 0, -2, -1, 2, -1, 0]
-%-)	-1.5	1.43178	[-2, 0, -2, -2, -1, 2, -2, -3, -2, -3]
-&-:	-0.4	1.42829	[-3, -1, 0, 0, -1, -1, -1, 2, -1, 2]
-&:	-0.7	0.64031	[0, -1, -1, -1, 1, -1, -1, -1, -1, -1]
-( '}{' )	1.6	0.66332	[1, 2, 2, 1, 1, 2, 2, 1, 3, 1]
-(%	-0.9	0.9434	[0, 0, 1, -1, -1, -1, -2, -2, -1, -2]
-('-:	2.2	1.16619	[4, 1, 4, 3, 1, 2, 3, 1, 2, 1]
-(':	2.3	0.9	[1, 3, 3, 2, 2, 4, 2, 3, 1, 2]
-((-:	2.1	0.53852	[2, 2, 2, 1, 2, 3, 2, 2, 3, 2]
-(*	1.1	1.13578	[2, 1, 1, -1, 1, 2, 2, -1, 2, 2]
-(-%	-0.7	1.26886	[-1, 2, 0, -1, -1, -2, 0, 0, -3, -1]
-(-*	1.3	1.26886	[4, 1, 2, 0, 2, -1, 1, 2, 1, 1]
-(-:	1.6	0.8	[2, 2, 1, 3, 1, 1, 1, 3, 1, 1]
-(-:0	2.8	0.87178	[3, 2, 3, 4, 3, 2, 3, 1, 4, 3]
-(-:<	-0.4	2.15407	[-3, 3, -1, -1, 2, -1, -2, 3, -3, -1]
-(-:o	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
-(-:O	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
-(-:{	-0.1	1.57797	[-2, -3, 1, -2, 1, 1, 0, 0, 2, 1]
-(-:|>*	1.9	0.83066	[3, 2, 2, 1, 0, 2, 3, 2, 2, 2]
-(-;	1.3	1.18743	[3, 2, 3, 0, 1, -1, 1, 2, 1, 1]
-(-;|	2.1	1.13578	[3, 2, 2, 4, 1, 1, 1, 4, 2, 1]
-(8	2.6	1.0198	[4, 2, 1, 3, 3, 3, 3, 1, 2, 4]
-(:	2.2	1.16619	[3, 1, 1, 2, 1, 2, 4, 3, 4, 1]
-(:0	2.4	1.11355	[0, 2, 3, 4, 3, 2, 3, 3, 1, 3]
-(:<	-0.2	2.03961	[-2, -3, 1, 1, 2, -1, 2, 1, -4, 1]
-(:o	2.5	0.92195	[3, 3, 1, 3, 3, 1, 2, 2, 4, 3]
-(:O	2.5	0.92195	[3, 3, 1, 3, 3, 1, 2, 2, 4, 3]
-(;	1.1	1.22066	[3, 1, 1, -1, 1, 2, 2, -1, 1, 2]
-(;<	0.3	1.00499	[1, 2, -1, -1, 0, 0, 1, -1, 1, 1]
-(=	2.2	1.16619	[3, 1, 2, 2, 1, 1, 4, 3, 4, 1]
-(?:	2.1	0.83066	[2, 2, 1, 3, 2, 2, 4, 1, 2, 2]
-(^:	1.5	0.67082	[1, 2, 2, 1, 3, 2, 1, 1, 1, 1]
-(^;	1.5	0.5	[1, 2, 2, 1, 2, 1, 2, 1, 1, 2]
-(^;0	2.0	0.7746	[2, 2, 1, 2, 1, 4, 2, 2, 2, 2]
-(^;o	1.9	0.83066	[2, 2, 1, 2, 1, 4, 2, 1, 2, 2]
-(o:	1.6	0.8	[2, 1, 3, 1, 1, 1, 2, 3, 1, 1]
-)':	-2.0	0.44721	[-2, -2, -2, -2, -1, -3, -2, -2, -2, -2]
-)-':	-2.1	0.53852	[-2, -2, -3, -2, -1, -2, -3, -2, -2, -2]
-)-:	-2.1	0.9434	[-3, -2, -4, -1, -3, -2, -2, -2, -1, -1]
-)-:<	-2.2	0.4	[-2, -2, -2, -2, -2, -2, -3, -3, -2, -2]
-)-:{	-2.1	0.9434	[-1, -3, -2, -1, -2, -2, -3, -4, -1, -2]
-):	-1.8	0.87178	[-1, -3, -1, -2, -1, -3, -1, -3, -1, -2]
-):<	-1.9	0.53852	[-1, -3, -2, -2, -2, -1, -2, -2, -2, -2]
-):{	-2.3	0.78102	[-1, -2, -3, -3, -2, -2, -4, -2, -2, -2]
-);<	-2.6	0.8	[-2, -2, -2, -3, -2, -3, -2, -2, -4, -4]
-*)	0.6	1.42829	[1, -1, 1, -3, 1, 1, 2, 1, 1, 2]
-*-)	0.3	1.61555	[1, -3, -2, 2, 1, 1, -1, 2, 1, 1]
-*-:	2.1	1.51327	[2, 2, 4, 4, 2, 1, -1, 4, 1, 2]
-*-;	2.4	1.62481	[2, 3, 4, 4, 2, 1, -1, 4, 1, 4]
-*:	1.9	1.04403	[2, 1, 1, 3, 1, 2, 4, 3, 1, 1]
-*<|:-)	1.6	1.28062	[0, 1, 3, 1, 1, 2, 3, 0, 4, 1]
-*\0/*	2.3	1.00499	[2, 0, 3, 1, 3, 3, 2, 3, 3, 3]
-*^:	1.6	1.42829	[2, 2, 1, 3, 2, 2, 3, 3, -1, -1]
-,-:	1.2	0.4	[1, 1, 2, 1, 1, 1, 1, 1, 2, 1]
----'-;-{@	2.3	1.18743	[0, 1, 3, 4, 2, 3, 2, 2, 2, 4]
---<--<@	2.2	1.249	[0, 1, 2, 4, 2, 1, 3, 2, 3, 4]
-.-:	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -2, -1]
-..###-:	-1.7	0.78102	[-2, -3, -3, -2, -1, -1, -1, -1, -1, -2]
-..###:	-1.9	1.04403	[-4, -1, -3, -1, -2, -2, -1, -3, -1, -1]
-/-:	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -1, -2, -3, -1]
-/:	-1.3	0.45826	[-2, -1, -1, -1, -2, -1, -1, -2, -1, -1]
-/:<	-1.4	0.4899	[-1, -2, -2, -1, -1, -1, -1, -1, -2, -2]
-/=	-0.9	0.53852	[-1, -1, -1, 0, -1, -2, -1, -1, -1, 0]
-/^:	-1.0	0.7746	[-2, -1, -2, 1, -1, -1, -1, -1, -1, -1]
-/o:	-1.4	0.66332	[0, -2, -1, -1, -2, -2, -1, -2, -1, -2]
-0-8	0.1	1.44568	[2, -1, -2, 0, 2, 0, 2, 0, -2, 0]
-0-|	-1.2	0.4	[-2, -1, -1, -1, -1, -1, -1, -1, -2, -1]
-0:)	1.9	1.04403	[2, 2, 2, 1, 0, 2, 4, 1, 3, 2]
-0:-)	1.4	0.91652	[2, 1, 0, 1, 2, 3, 2, 1, 2, 0]
-0:-3	1.5	0.92195	[2, 1, 0, 2, 2, 3, 2, 1, 2, 0]
-0:03	1.9	1.22066	[2, 3, 2, 0, 0, 1, 4, 2, 3, 2]
-0;^)	1.6	0.91652	[0, 1, 3, 1, 2, 1, 2, 1, 2, 3]
-0_o	-0.3	0.78102	[0, -2, 0, 1, 0, 0, -1, 0, -1, 0]
-10q	2.1	1.22066	[1, 3, 1, 2, 1, 4, 3, 4, 1, 1]
-1337	2.1	1.13578	[3, 1, 4, 0, 2, 3, 1, 2, 2, 3]
-143	3.2	0.74833	[4, 4, 2, 3, 2, 3, 4, 3, 4, 3]
-1432	2.6	0.8	[4, 3, 3, 2, 2, 4, 2, 2, 2, 2]
-14aa41	2.4	0.91652	[3, 2, 2, 4, 2, 2, 1, 2, 4, 2]
-182	-2.9	1.3	[-4, 0, -3, -3, -1, -3, -4, -4, -4, -3]
-187	-3.1	1.22066	[-4, 0, -4, -3, -2, -4, -3, -3, -4, -4]
-2g2b4g	2.8	0.6	[4, 2, 3, 2, 3, 3, 3, 3, 2, 3]
-2g2bt	-0.1	1.57797	[-1, 2, -1, 1, 0, 2, 0, -3, -2, 1]
-2qt	2.1	0.83066	[3, 3, 3, 3, 2, 1, 2, 1, 2, 1]
-3:(	-2.2	0.87178	[-4, -3, -2, -3, -2, -1, -1, -2, -2, -2]
-3:)	0.5	1.28452	[-2, 1, -2, 1, 1, 1, 1, 2, 1, 1]
-3:-(	-2.3	0.78102	[-2, -3, -2, -2, -2, -2, -4, -1, -3, -2]
-3:-)	-1.4	1.35647	[-1, -2, 1, 1, -2, -2, -3, -1, -3, -2]
-4col	-2.2	1.16619	[-2, -3, -1, -3, -4, -1, -2, -1, -4, -1]
-4q	-3.1	1.51327	[-3, -3, -4, -2, -4, -4, -4, 1, -4, -4]
-5fs	1.5	1.11803	[1, 2, 1, 1, 2, 3, 2, 3, -1, 1]
-8)	1.9	0.7	[2, 2, 2, 1, 1, 2, 2, 3, 3, 1]
-8-d	1.7	0.64031	[1, 2, 0, 2, 2, 2, 2, 2, 2, 2]
-8-o	-0.3	0.78102	[1, -1, 0, 0, 0, -1, 0, -2, 0, 0]
-86	-1.6	1.0198	[-1, -1, -1, -1, -1, -4, -1, -2, -1, -3]
-8d	2.9	0.53852	[3, 3, 4, 2, 3, 3, 3, 3, 2, 3]
-:###..	-2.4	0.91652	[-3, -2, -4, -3, -1, -2, -2, -3, -1, -3]
-:$	-0.2	1.83303	[-2, -1, 0, 0, -1, 1, 4, -3, 1, -1]
-:&	-0.6	1.0198	[-2, -1, 0, 0, -1, -1, 1, -2, 1, -1]
-:'(	-2.2	0.74833	[-2, -1, -2, -2, -2, -2, -4, -3, -2, -2]
-:')	2.3	0.78102	[3, 1, 3, 2, 2, 2, 2, 4, 2, 2]
-:'-(	-2.4	0.66332	[-2, -1, -2, -3, -2, -3, -3, -3, -2, -3]
-:'-)	2.7	0.64031	[2, 1, 3, 3, 3, 3, 3, 3, 3, 3]
-:(	-1.9	1.13578	[-2, -3, -2, 0, -1, -1, -2, -3, -1, -4]
-:)	2.0	1.18322	[2, 2, 1, 1, 1, 1, 4, 3, 4, 1]
-:*	2.5	1.0247	[3, 2, 1, 1, 2, 3, 4, 3, 4, 2]
-:-###..	-2.5	0.92195	[-3, -2, -3, -2, -4, -3, -1, -3, -1, -3]
-:-&	-0.5	0.92195	[-1, -1, 0, -1, -1, -1, -1, 0, 2, -1]
-:-(	-1.5	0.5	[-2, -1, -1, -1, -2, -2, -2, -1, -2, -1]
-:-)	1.3	0.45826	[1, 1, 1, 1, 2, 1, 2, 1, 2, 1]
-:-))	2.8	1.07703	[3, 4, 4, 1, 2, 2, 4, 2, 4, 2]
-:-*	1.7	0.64031	[1, 2, 1, 1, 1, 3, 2, 2, 2, 2]
-:-,	1.1	0.53852	[1, 1, 1, 0, 1, 1, 1, 1, 2, 2]
-:-.	-0.9	0.53852	[-1, -1, 0, -1, 0, -1, -1, -1, -2, -1]
-:-/	-1.2	0.6	[0, -1, -1, -1, -1, -2, -2, -1, -1, -2]
-:-<	-1.5	0.5	[-2, -1, -1, -2, -1, -2, -2, -1, -2, -1]
-:-d	2.3	0.45826	[2, 2, 3, 3, 2, 3, 2, 2, 2, 2]
-:-D	2.3	0.45826	[2, 2, 3, 3, 2, 3, 2, 2, 2, 2]
-:-o	0.1	1.3	[2, -1, -2, 0, 1, 1, 2, 0, -1, -1]
-:-p	1.2	0.4	[1, 2, 1, 1, 1, 1, 2, 1, 1, 1]
-:-[	-1.6	0.4899	[-1, -2, -1, -2, -2, -1, -2, -1, -2, -2]
-:-\	-0.9	0.3	[-1, -1, -1, -1, -1, -1, -1, 0, -1, -1]
-:-c	-1.3	0.45826	[-1, -1, -1, -2, -2, -1, -2, -1, -1, -1]
-:-p	1.5	0.5	[1, 1, 1, 1, 1, 2, 2, 2, 2, 2]
-:-|	-0.7	0.64031	[-1, -1, 0, 0, 0, -1, -1, -2, 0, -1]
-:-||	-2.5	0.67082	[-2, -2, -2, -3, -2, -3, -3, -2, -2, -4]
-:-Þ	0.9	1.04403	[1, -1, 1, 2, 1, -1, 1, 2, 2, 1]
-:/	-1.4	0.66332	[-1, -1, -1, -1, -1, -1, -3, -2, -2, -1]
-:3	2.3	1.26886	[4, 1, 1, 1, 2, 2, 4, 3, 4, 1]
-:<	-2.1	0.7	[-3, -1, -2, -2, -2, -2, -3, -3, -2, -1]
-:>	2.1	1.22066	[3, 1, 1, 1, 1, 2, 4, 3, 4, 1]
-:?)	1.3	0.64031	[3, 1, 1, 1, 1, 2, 1, 1, 1, 1]
-:?c	-1.6	0.4899	[-1, -2, -1, -1, -2, -2, -1, -2, -2, -2]
-:@	-2.5	0.80623	[-1, -3, -3, -2, -1, -3, -3, -3, -3, -3]
-:d	2.3	1.1	[4, 2, 2, 1, 2, 1, 4, 3, 3, 1]
-:D	2.3	1.1	[4, 2, 2, 1, 2, 1, 4, 3, 3, 1]
-:l	-1.7	0.9	[-1, -3, -1, -1, -1, -3, -2, -3, -1, -1]
-:o	-0.4	1.35647	[2, -1, -2, 0, 1, 0, -3, 0, -1, 0]
-:p	1.0	0.7746	[-1, 1, 1, 1, 1, 1, 2, 1, 2, 1]
-:s	-1.2	0.9798	[-2, -2, -1, -1, -1, 1, -3, -1, -1, -1]
-:[	-2.0	0.63246	[-2, -2, -1, -2, -2, -3, -3, -2, -1, -2]
-:\	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -1, -1, -2]
-:]	2.2	1.16619	[3, 1, 1, 1, 3, 1, 4, 2, 2, 4]
-:^)	2.1	1.13578	[3, 2, 4, 1, 1, 1, 1, 2, 4, 2]
-:^*	2.6	0.91652	[2, 1, 2, 3, 4, 4, 3, 2, 3, 2]
-:^/	-1.2	0.6	[-2, -1, -2, 0, -1, -1, -1, -1, -2, -1]
-:^\	-1.0	0.44721	[-1, -1, -1, -1, -1, -2, 0, -1, -1, -1]
-:^|	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
-:c	-2.1	0.83066	[-3, -2, -1, -2, -2, -1, -3, -3, -3, -1]
-:c)	2.0	1.18322	[2, 1, 1, 1, 1, 2, 3, 4, 4, 1]
-:o)	2.1	0.9434	[1, 3, 3, 1, 1, 3, 2, 3, 1, 3]
-:o/	-1.4	0.4899	[-1, -1, -1, -2, -1, -1, -2, -2, -1, -2]
-:o\	-1.1	0.3	[-1, -1, -1, -2, -1, -1, -1, -1, -1, -1]
-:o|	-0.6	1.0198	[0, 0, 0, 0, -1, 0, 0, -3, 0, -2]
-:P	1.4	0.8	[3, 1, 0, 2, 1, 1, 2, 2, 1, 1]
-:{	-1.9	0.83066	[-2, -1, -1, -2, -2, -1, -3, -3, -3, -1]
-:|	-0.4	1.11355	[-1, -1, 0, -1, -1, -1, 1, -2, 2, 0]
-:}	2.1	1.22066	[3, 1, 1, 1, 2, 1, 4, 3, 4, 1]
-:Þ	1.1	0.53852	[1, 1, 1, 1, 0, 1, 1, 2, 2, 1]
-;)	0.9	1.04403	[2, -1, 1, 1, 1, 1, -1, 2, 2, 1]
-;-)	1.0	1.73205	[1, -2, 1, -2, 1, 4, 2, 1, 2, 2]
-;-*	2.2	0.74833	[2, 2, 1, 3, 4, 2, 2, 2, 2, 2]
-;-]	0.7	1.67631	[1, -2, 1, -3, 1, 2, 2, 1, 2, 2]
-;d	0.8	1.249	[2, -1, 2, 1, 1, 1, -2, 2, 1, 1]
-;D	0.8	1.249	[2, -1, 2, 1, 1, 1, -2, 2, 1, 1]
-;]	0.6	1.11355	[1, -1, 1, 1, 1, 1, -2, 2, 1, 1]
-;^)	1.4	0.91652	[2, 2, 1, 2, 1, 2, -1, 1, 2, 2]
-</3	-3.0	1.0	[-3, -3, -4, -3, -4, -1, -2, -2, -4, -4]
-<3	1.9	1.13578	[3, 2, 1, 3, 1, 4, 2, 0, 1, 2]
-<:	2.1	1.13578	[3, 2, 4, 1, 1, 1, 1, 2, 4, 2]
-<:-|	-1.4	0.66332	[-1, -1, -1, -2, -2, -1, -3, -1, -1, -1]
-=)	2.2	1.16619	[4, 2, 3, 3, 2, 1, 1, 4, 1, 1]
-=-3	2.0	0.63246	[2, 2, 2, 3, 1, 3, 1, 2, 2, 2]
-=-d	2.4	0.91652	[2, 2, 1, 3, 2, 4, 2, 4, 2, 2]
-=-D	2.4	0.91652	[2, 2, 1, 3, 2, 4, 2, 4, 2, 2]
-=/	-1.4	0.91652	[-1, -1, -1, -1, -1, -2, -1, -1, -4, -1]
-=3	2.1	0.7	[3, 1, 2, 1, 2, 3, 2, 2, 3, 2]
-=d	2.3	0.45826	[3, 2, 2, 2, 2, 3, 2, 2, 2, 3]
-=D	2.3	0.45826	[3, 2, 2, 2, 2, 3, 2, 2, 2, 3]
-=l	-1.2	0.6	[-2, -1, -1, 0, -2, -1, -2, -1, -1, -1]
-=\	-1.2	0.6	[-2, -1, -1, 0, -2, -1, -2, -1, -1, -1]
-=]	1.6	0.8	[2, 1, 3, 1, 1, 1, 2, 3, 1, 1]
-=p	1.3	0.9	[2, 1, 2, 1, 2, -1, 1, 2, 2, 1]
-=|	-0.8	0.87178	[-2, -1, -2, 1, 0, -1, 0, -1, -1, -1]
->-:	-2.0	0.89443	[-2, -3, -2, -4, -1, -1, -1, -2, -2, -2]
->.<	-1.3	0.45826	[-1, -2, -1, -2, -2, -1, -1, -1, -1, -1]
->:	-2.1	1.13578	[-4, -1, -1, -4, -2, -3, -1, -1, -2, -2]
->:(	-2.7	0.64031	[-2, -3, -2, -3, -3, -2, -4, -2, -3, -3]
->:)	0.4	1.42829	[1, 1, 2, 1, -1, -2, 1, 2, -2, 1]
->:-(	-2.7	0.78102	[-3, -2, -3, -2, -4, -2, -3, -2, -2, -4]
->:-)	-0.4	1.68523	[1, 2, 1, -2, -2, -1, -1, -3, -1, 2]
->:/	-1.6	0.8	[-1, -2, -1, -3, -1, -1, -1, -1, -2, -3]
->:o	-1.2	1.16619	[-3, -1, -2, 0, -2, -2, 0, -1, 1, -2]
->:p	1.0	0.7746	[-1, 1, 1, 2, 1, 2, 1, 1, 1, 1]
->:[	-2.1	0.53852	[-2, -2, -2, -2, -3, -3, -2, -1, -2, -2]
->:\	-1.7	0.64031	[-1, -2, -1, -2, -2, -3, -1, -1, -2, -2]
->;(	-2.9	0.7	[-3, -4, -3, -2, -2, -3, -3, -3, -2, -4]
->;)	0.1	1.04403	[-1, 1, 0, -1, 2, 0, -1, 1, 1, -1]
->_>^	2.1	0.9434	[2, 2, 1, 4, 3, 2, 1, 3, 1, 2]
-@:	-2.1	0.9434	[-3, -2, -3, -1, -2, -4, -1, -2, -1, -2]
-@>-->--	2.1	1.22066	[1, 1, 0, 2, 4, 2, 4, 2, 3, 2]
-@}-;-'---	2.2	1.32665	[0, 1, 3, 2, 1, 4, 4, 1, 3, 3]
-aas	2.5	0.80623	[2, 3, 3, 4, 1, 2, 3, 2, 2, 3]
-aayf	2.7	0.78102	[2, 3, 2, 4, 3, 2, 2, 3, 4, 2]
-afu	-2.9	0.83066	[-3, -3, -3, -3, -3, -1, -4, -4, -2, -3]
-alol	2.8	0.74833	[2, 2, 2, 3, 3, 2, 3, 4, 4, 3]
-ambw	2.9	0.7	[2, 3, 4, 2, 3, 2, 3, 3, 4, 3]
-aml	3.4	0.66332	[4, 3, 2, 4, 3, 3, 4, 4, 3, 4]
-atab	-1.9	1.22066	[-2, 0, -1, -2, -1, -1, -2, -4, -4, -2]
-awol	-1.3	0.78102	[0, -1, -1, -1, -1, -1, -2, -2, -3, -1]
-ayc	0.2	0.9798	[0, 1, -1, 1, 0, 1, 0, -1, 2, -1]
-ayor	-1.2	0.6	[-1, -1, -2, -2, -1, -1, -1, 0, -2, -1]
-aug-00	0.3	1.18743	[2, 0, -2, 0, 0, 1, -1, 2, 1, 0]
-bfd	-2.7	0.78102	[-3, -2, -4, -2, -3, -2, -3, -2, -4, -2]
-bfe	-2.6	1.35647	[-3, -3, -4, -2, -3, -2, 1, -3, -4, -3]
-bff	2.9	0.83066	[3, 3, 4, 2, 4, 2, 2, 3, 4, 2]
-bffn	1.0	0.89443	[2, 1, -1, 1, 0, 1, 2, 1, 2, 1]
-bl	2.3	1.1	[2, 1, 4, 1, 2, 2, 4, 3, 1, 3]
-bsod	-2.2	1.07703	[-1, -4, -3, -3, 0, -2, -3, -2, -2, -2]
-btd	-2.1	0.83066	[-1, -2, -3, -3, -3, -1, -3, -2, -1, -2]
-btdt	-0.1	1.22066	[0, -1, 0, -1, 0, 3, 1, -1, -1, -1]
-bz	0.4	1.35647	[-1, 0, 0, 0, 4, 1, -1, 1, 0, 0]
-b^d	2.6	0.8	[3, 2, 2, 4, 3, 1, 3, 3, 3, 2]
-cwot	-2.3	0.45826	[-3, -2, -2, -2, -2, -3, -2, -3, -2, -2]
-d-':	-2.5	0.67082	[-3, -3, -2, -2, -2, -4, -2, -3, -2, -2]
-d8	-3.2	0.6	[-3, -3, -3, -3, -4, -4, -2, -3, -3, -4]
-d:	-2.9	0.83066	[-3, -3, -3, -3, -2, -4, -1, -3, -3, -4]
-d:<	-3.2	0.9798	[-4, -4, -4, -1, -3, -3, -4, -2, -3, -4]
-d;	-2.9	0.83066	[-1, -3, -3, -3, -3, -4, -2, -3, -3, -4]
-d=	-3.0	0.89443	[-4, -3, -3, -3, -2, -4, -1, -3, -3, -4]
-doa	-2.3	1.00499	[-2, -3, -3, -2, -2, -2, -4, 0, -2, -3]
-dx	-3.0	0.63246	[-3, -2, -3, -3, -4, -3, -4, -2, -3, -3]
-ez	1.5	0.67082	[3, 2, 2, 1, 1, 1, 2, 1, 1, 1]
-fav	2.4	0.91652	[3, 1, 3, 2, 2, 3, 1, 2, 3, 4]
-fcol	-1.8	0.74833	[-2, -2, -1, -2, -1, -2, -1, -3, -3, -1]
-ff	1.8	1.249	[4, 2, 1, 2, 1, 3, 3, 0, 2, 0]
-ffs	-2.8	0.9798	[-2, -2, -3, -3, -2, -4, -4, -4, -1, -3]
-fkm	-2.4	1.35647	[-4, -1, -4, -2, -2, -3, -1, 0, -3, -4]
-foaf	1.8	1.249	[2, 1, 2, 0, 4, 1, 1, 1, 2, 4]
-ftw	2.0	0.7746	[2, 1, 1, 2, 2, 2, 3, 3, 1, 3]
-fu	-3.7	0.45826	[-3, -4, -4, -3, -3, -4, -4, -4, -4, -4]
-fubar	-3.0	1.09545	[-4, -3, -3, -4, -3, -3, -3, -4, 0, -3]
-fwb	2.5	1.43178	[2, 3, 4, 0, 1, 2, 4, 1, 4, 4]
-fyi	0.8	1.66132	[0, 1, 0, -1, 0, 0, 4, 4, 0, 0]
-fysa	0.4	0.91652	[0, 0, 0, 1, 0, 3, 0, 0, 0, 0]
-g1	1.4	0.4899	[2, 1, 1, 1, 2, 1, 2, 1, 1, 2]
-gg	1.2	0.74833	[0, 2, 2, 1, 0, 1, 2, 2, 1, 1]
-gga	1.7	0.45826	[2, 2, 1, 2, 2, 1, 2, 2, 1, 2]
-gigo	-0.6	1.11355	[-2, -1, 1, 0, 0, 0, -1, -2, -2, 1]
-gj	2.0	1.0	[2, 1, 2, 1, 1, 3, 4, 2, 3, 1]
-gl	1.3	0.64031	[1, 1, 1, 1, 3, 1, 1, 2, 1, 1]
-gla	2.5	0.92195	[1, 2, 2, 4, 2, 4, 2, 3, 3, 2]
-gn	1.2	0.74833	[1, 1, 1, 1, 3, 1, 1, 2, 1, 0]
-gr8	2.7	0.78102	[1, 3, 3, 4, 3, 2, 3, 2, 3, 3]
-grrr	-0.4	1.42829	[-2, -1, 0, 1, -2, -1, -1, 3, 0, -1]
-gt	1.1	0.53852	[1, 1, 1, 1, 1, 1, 2, 1, 0, 2]
-h&k	2.3	0.78102	[2, 2, 2, 3, 4, 2, 3, 2, 1, 2]
-hagd	2.2	0.87178	[2, 2, 3, 2, 1, 3, 4, 1, 2, 2]
-hagn	2.2	0.87178	[2, 2, 3, 2, 1, 3, 4, 1, 2, 2]
-hago	1.2	0.4	[1, 2, 1, 1, 1, 2, 1, 1, 1, 1]
-hak	1.9	0.7	[3, 1, 2, 2, 1, 2, 3, 2, 1, 2]
-hand	2.2	0.87178	[2, 2, 1, 3, 2, 3, 4, 1, 2, 2]
-hho1/2k	1.4	1.11355	[1, -1, 2, 3, 1, 1, 1, 2, 3, 1]
-hhoj	2.0	1.09545	[4, 2, 1, 1, 2, 1, 1, 4, 2, 2]
-hhok	0.9	0.9434	[1, 2, 1, 0, -1, 0, 2, 1, 1, 2]
-hugz	2.0	0.7746	[2, 3, 1, 3, 1, 3, 1, 2, 2, 2]
-hi5	1.9	0.53852	[2, 2, 2, 1, 3, 2, 1, 2, 2, 2]
-idk	-0.4	0.66332	[0, 0, 0, 0, -1, -2, 0, 0, 0, -1]
-ijs	0.7	1.84662	[0, -1, 0, -1, 0, 4, 0, 4, -1, 2]
-ilu	3.4	0.66332	[3, 4, 3, 4, 2, 3, 4, 3, 4, 4]
-iluaaf	2.7	1.1	[3, 3, 3, 2, 3, 0, 4, 3, 2, 4]
-ily	3.4	0.66332	[3, 4, 3, 4, 2, 3, 4, 3, 4, 4]
-ily2	2.6	0.66332	[3, 2, 3, 2, 3, 2, 3, 4, 2, 2]
-iou	0.7	1.34536	[0, 0, -1, 2, 0, 0, 0, 4, 1, 1]
-iyq	2.3	1.18743	[3, 3, 1, 1, 2, 1, 4, 4, 3, 1]
-j/j	2.0	1.34164	[4, 1, 1, 1, 1, 4, 4, 1, 2, 1]
-j/k	1.6	1.2	[1, 2, 1, 3, 0, 0, 2, 2, 1, 4]
-j/p	1.4	0.66332	[1, 1, 0, 2, 1, 2, 2, 2, 1, 2]
-j/t	-0.2	1.46969	[1, -1, -1, -2, 1, 1, 2, -2, 1, -2]
-j/w	1.0	1.0	[1, 1, 1, 3, 0, 0, 0, 2, 0, 2]
-j4f	1.4	0.8	[2, 1, 1, 0, 3, 1, 1, 1, 2, 2]
-j4g	1.7	1.18743	[1, 4, 1, 1, 3, 1, 3, 0, 2, 1]
-jho	0.8	0.4	[1, 1, 1, 1, 0, 1, 1, 1, 0, 1]
-jhomf	1.0	0.63246	[1, 1, 1, 0, 1, 0, 2, 2, 1, 1]
-jj	1.0	0.63246	[1, 1, 1, 1, 2, 0, 2, 1, 1, 0]
-jk	0.9	1.22066	[1, 0, 0, 1, 0, 0, 2, 1, 4, 0]
-jp	0.8	0.74833	[1, 1, 1, 0, 2, 0, 2, 0, 1, 0]
-jt	0.9	0.83066	[1, 1, 0, 2, 2, 0, 2, 0, 1, 0]
-jw	1.6	1.68523	[3, 0, 0, 0, 0, 0, 3, 4, 2, 4]
-jealz	-1.2	0.9798	[-1, -1, -1, 1, -2, -2, -1, -3, -1, -1]
-k4y	2.3	1.00499	[2, 1, 1, 2, 4, 2, 3, 4, 2, 2]
-kfy	2.3	0.64031	[2, 2, 2, 1, 3, 2, 3, 3, 2, 3]
-kia	-3.2	0.6	[-3, -3, -3, -4, -3, -2, -3, -3, -4, -4]
-kk	1.5	1.0247	[2, 1, 0, 0, 1, 2, 3, 3, 2, 1]
-kmuf	2.2	1.4	[2, 2, 2, 3, 4, 3, -1, 1, 4, 2]
-l	2.0	0.7746	[2, 1, 2, 3, 2, 3, 1, 3, 2, 1]
-l&r	2.2	0.74833	[3, 2, 2, 3, 1, 3, 1, 3, 2, 2]
-laoj	1.3	1.73494	[1, -2, -1, 3, 3, 2, 4, 1, 1, 1]
-lmao	2.0	1.18322	[3, 0, 3, 0, 3, 1, 3, 2, 3, 2]
-lmbao	1.8	1.77764	[3, 2, 2, 2, 1, 3, -3, 2, 4, 2]
-lmfao	2.5	1.28452	[3, 2, 3, 3, 3, -1, 4, 2, 3, 2]
-lmso	2.7	0.78102	[3, 3, 4, 3, 3, 1, 3, 3, 2, 2]
-lol	2.9	0.83066	[4, 2, 2, 2, 4, 2, 3, 3, 4, 3]
-lolz	2.7	0.78102	[2, 3, 3, 2, 2, 4, 4, 3, 2, 2]
-lts	1.6	0.66332	[1, 1, 2, 2, 1, 3, 1, 1, 2, 2]
-ly	2.6	0.91652	[2, 2, 1, 3, 4, 4, 3, 2, 2, 3]
-ly4e	2.7	0.78102	[3, 3, 3, 2, 1, 3, 3, 4, 2, 3]
-lya	3.3	0.78102	[3, 4, 4, 4, 2, 2, 3, 4, 3, 4]
-lyb	3.0	0.63246	[3, 3, 4, 3, 2, 3, 2, 4, 3, 3]
-lyl	3.1	0.7	[4, 3, 4, 3, 2, 3, 3, 2, 4, 3]
-lylab	2.7	0.78102	[3, 3, 3, 1, 3, 4, 2, 2, 3, 3]
-lylas	2.6	0.8	[3, 3, 3, 1, 3, 4, 2, 2, 2, 3]
-lylb	1.6	1.56205	[2, 2, 3, -2, 4, 1, 3, 1, 1, 1]
-m8	1.4	1.0198	[3, 0, 1, 0, 1, 3, 2, 2, 1, 1]
-mia	-1.2	0.4	[-2, -1, -1, -2, -1, -1, -1, -1, -1, -1]
-mml	2.0	1.0	[1, 1, 2, 3, 3, 2, 1, 2, 4, 1]
-mofo	-2.4	2.2	[-4, -4, -4, 0, -3, -2, -2, -4, 3, -4]
-muah	2.8	1.07703	[1, 2, 4, 4, 4, 2, 4, 2, 2, 3]
-mubar	-1.0	2.36643	[-4, -2, -3, -2, -2, -2, 1, 4, 2, -2]
-musm	0.9	2.07123	[-1, 1, 1, 1, 4, 3, 1, -4, 1, 2]
-mwah	2.5	0.80623	[2, 2, 2, 4, 2, 3, 2, 2, 4, 2]
-n1	1.9	1.04403	[1, 1, 3, 2, 2, 3, 4, 1, 1, 1]
-nbd	1.3	1.34536	[2, 1, 0, 0, 0, 4, 2, 0, 3, 1]
-nbif	-0.5	0.67082	[-1, -2, 0, 0, 0, 0, -1, -1, 0, 0]
-nfc	-2.7	0.9	[-3, -2, -2, -3, -1, -2, -4, -3, -4, -3]
-nfw	-2.4	1.0198	[-2, -2, -1, -3, -1, -2, -4, -3, -4, -2]
-nh	2.2	0.6	[2, 2, 2, 2, 1, 3, 3, 3, 2, 2]
-nimby	-0.8	0.6	[0, 0, -1, 0, -1, -2, -1, -1, -1, -1]
-nimjd	-0.7	0.78102	[0, -2, -1, -2, 0, -1, 0, 0, 0, -1]
-nimq	-0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, -2, 0]
-nimy	-1.4	1.68523	[-1, -2, -3, -2, -1, 2, -3, 0, 0, -4]
-nitl	-1.5	0.92195	[-1, -1, -2, -3, -1, -3, -1, -2, 0, -1]
-nme	-2.1	1.13578	[-1, -2, -2, -1, -4, -2, -3, -3, 0, -3]
-noyb	-0.7	1.67631	[-1, -2, 0, -1, -1, -2, -2, -1, 4, -1]
-np	1.4	1.0198	[0, 1, 1, 1, 1, 2, 2, 4, 1, 1]
-ntmu	1.4	0.66332	[1, 1, 0, 1, 2, 2, 2, 2, 2, 1]
-o-8	-0.5	1.5	[2, -1, 0, 0, -2, -2, 0, -2, 2, -2]
-o-:	-0.3	1.18743	[2, -1, 0, 0, -1, -2, 0, -2, 1, 0]
-o-|	-1.1	0.53852	[-1, -1, -1, 0, -1, -1, -1, -2, -2, -1]
-o.o	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
-O.o	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
-o.O	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
-o:	-0.2	0.87178	[-1, 0, -1, -2, 0, 1, 0, 1, 0, 0]
-o:)	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
-o:-)	2.0	1.18322	[1, 4, 1, 2, 4, 1, 1, 2, 3, 1]
-o:-3	2.2	0.9798	[1, 4, 2, 3, 3, 2, 1, 2, 3, 1]
-o:3	2.3	0.78102	[3, 3, 2, 2, 1, 2, 4, 2, 2, 2]
-o:<	-0.3	1.1	[-1, -1, -2, 0, -1, 0, 1, 2, 0, -1]
-o;^)	1.6	0.8	[1, 2, 1, 2, 1, 2, 2, 0, 3, 2]
-ok	1.6	1.42829	[0, 0, 1, 1, 1, 4, 3, 4, 1, 1]
-o_o	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
-O_o	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
-o_O	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
-pita	-2.4	1.2	[-2, -1, -1, -4, -4, -2, -4, -2, -3, -1]
-pls	0.3	0.45826	[0, 1, 1, 1, 0, 0, 0, 0, 0, 0]
-plz	0.3	0.45826	[0, 1, 1, 1, 0, 0, 0, 0, 0, 0]
-pmbi	0.8	1.32665	[3, 0, 0, 1, 1, -2, 2, 2, 0, 1]
-pmfji	0.3	0.78102	[0, 0, 1, 0, 2, -1, 0, 1, 0, 0]
-pmji	0.7	1.00499	[1, 2, 0, -1, 0, 0, 2, 2, 1, 0]
-po	-2.6	0.91652	[-2, -3, -4, -3, -3, -3, -1, -3, -1, -3]
-ptl	2.6	1.11355	[3, 4, 2, 4, 1, 2, 3, 1, 4, 2]
-pu	-1.1	1.3	[-3, -1, -3, -2, -1, -1, -1, -1, 1, 1]
-qq	-2.2	0.6	[-2, -2, -1, -3, -3, -2, -2, -3, -2, -2]
-qt	1.8	0.6	[2, 2, 1, 2, 1, 3, 2, 1, 2, 2]
-r&r	2.4	1.0198	[2, 4, 2, 3, 1, 4, 2, 2, 1, 3]
-rofl	2.7	0.78102	[3, 2, 2, 2, 4, 4, 2, 3, 3, 2]
-roflmao	2.5	1.11803	[4, 2, 2, 4, 1, 1, 2, 4, 3, 2]
-rotfl	2.6	0.66332	[3, 2, 3, 3, 1, 3, 3, 3, 2, 3]
-rotflmao	2.8	1.07703	[4, 3, 2, 4, 1, 1, 4, 3, 3, 3]
-rotflmfao	2.5	1.11803	[3, 4, 1, 3, 3, 3, 0, 3, 2, 3]
-rotflol	3.0	1.09545	[1, 4, 4, 4, 2, 2, 2, 3, 4, 4]
-rotgl	2.9	0.7	[4, 3, 2, 2, 3, 3, 3, 2, 4, 3]
-rotglmao	1.8	2.4	[3, 3, 4, 3, -1, 1, 4, -4, 2, 3]
-s:	-1.1	0.83066	[-1, -1, -2, -2, -1, -1, -2, -1, 1, -1]
-sapfu	-1.1	1.57797	[-2, 0, -3, -1, -1, 1, -2, 2, -2, -3]
-sete	2.8	0.87178	[3, 3, 3, 2, 3, 3, 4, 4, 1, 2]
-sfete	2.7	0.78102	[4, 3, 3, 3, 2, 4, 2, 2, 2, 2]
-sgtm	2.4	1.0198	[2, 1, 1, 2, 3, 3, 2, 2, 4, 4]
-slap	0.6	2.15407	[2, -1, 1, -1, 0, 4, -3, 4, 1, -1]
-slaw	2.1	1.04403	[3, 2, 0, 2, 2, 2, 3, 1, 4, 2]
-smh	-1.3	0.64031	[-2, -1, 0, -1, -1, -2, -2, -1, -2, -1]
-snafu	-2.5	1.11803	[-3, -4, -3, -3, -1, 0, -2, -3, -3, -3]
-sob	-2.8	0.9798	[-3, -4, -3, -2, -2, -1, -2, -4, -4, -3]
-swak	2.3	1.00499	[2, 2, 2, 1, 4, 2, 3, 2, 1, 4]
-tgif	2.3	1.34536	[1, 3, 3, 3, -1, 2, 4, 2, 3, 3]
-thks	1.4	0.4899	[1, 2, 1, 2, 1, 2, 1, 1, 2, 1]
-thx	1.5	0.92195	[0, 1, 3, 2, 1, 2, 1, 1, 3, 1]
-tia	2.3	0.9	[3, 1, 2, 1, 4, 3, 2, 3, 2, 2]
-tmi	-0.3	1.61555	[-1, -1, 2, -1, 1, -2, -2, -1, 3, -1]
-tnx	1.1	0.53852	[2, 1, 1, 0, 1, 1, 2, 1, 1, 1]
-true	1.8	1.32665	[2, 1, 1, 0, 1, 4, 3, 1, 4, 1]
-tx	1.5	0.92195	[3, 2, 1, 0, 2, 1, 3, 1, 1, 1]
-txs	1.1	0.7	[1, 2, 0, 1, 2, 0, 1, 2, 1, 1]
-ty	1.6	0.66332	[1, 2, 3, 1, 2, 2, 1, 2, 1, 1]
-tyvm	2.5	1.11803	[2, 2, 1, 3, 1, 4, 2, 4, 2, 4]
-urw	1.9	1.13578	[1, 2, 1, 2, 4, 2, 4, 1, 1, 1]
-vbg	2.1	1.75784	[2, 3, 3, 3, 3, -3, 3, 2, 2, 3]
-vbs	3.1	0.53852	[2, 3, 3, 3, 4, 4, 3, 3, 3, 3]
-vip	2.3	1.00499	[2, 1, 1, 3, 4, 2, 2, 4, 2, 2]
-vwd	2.6	0.91652	[4, 2, 4, 2, 1, 3, 3, 2, 3, 2]
-vwp	2.1	0.7	[3, 1, 2, 2, 3, 2, 2, 3, 1, 2]
-wag	-0.2	0.74833	[-1, 0, 0, 0, 0, 0, -2, 1, 0, 0]
-wd	2.7	1.1	[3, 1, 4, 3, 4, 2, 1, 3, 2, 4]
-wilco	0.9	0.9434	[1, 3, 1, 0, 1, 0, 2, 1, 0, 0]
-wp	1.0	0.0	[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
-wtf	-2.8	0.74833	[-4, -3, -2, -3, -2, -2, -2, -4, -3, -3]
-wtg	2.1	0.7	[1, 3, 2, 3, 2, 2, 2, 1, 2, 3]
-wth	-2.4	0.4899	[-2, -3, -2, -3, -2, -2, -2, -3, -3, -2]
-x-d	2.7	0.78102	[1, 3, 4, 2, 3, 3, 3, 2, 3, 3]
-x-p	1.8	0.87178	[2, 1, 3, 1, 3, 1, 3, 1, 2, 1]
-xd	2.7	0.9	[1, 4, 4, 3, 2, 2, 3, 3, 2, 3]
-xlnt	3.0	0.89443	[4, 3, 3, 1, 4, 4, 3, 3, 3, 2]
-xoxo	3.0	0.7746	[2, 2, 4, 2, 3, 3, 4, 3, 3, 4]
-xoxozzz	2.3	0.78102	[3, 1, 2, 2, 2, 2, 3, 2, 4, 2]
-xp	1.2	0.4	[1, 1, 1, 1, 2, 1, 2, 1, 1, 1]
-xqzt	1.6	1.42829	[0, 2, 1, 2, 4, -1, 3, 1, 1, 3]
-xtc	0.8	1.93907	[2, 0, -3, 3, 3, -1, 3, 1, -1, 1]
-yolo	1.1	0.83066	[0, 1, 1, 2, 1, 1, 1, 3, 0, 1]
-yoyo	0.4	1.85472	[-1, 0, -1, -1, 4, 2, -2, 2, 2, -1]
-yvw	1.6	0.4899	[1, 2, 1, 1, 2, 2, 2, 1, 2, 2]
-yw	1.8	1.32665	[1, 1, 1, 4, 1, 1, 4, 0, 3, 2]
-ywia	2.5	1.11803	[3, 2, 3, 4, 1, 1, 1, 3, 3, 4]
-zzz	-1.2	0.87178	[0, -1, 0, -1, -3, -1, -1, -2, -2, -1]
-[-;	0.5	1.28452	[1, -1, -1, 1, 1, 1, 2, -2, 2, 1]
-[:	1.3	0.45826	[1, 1, 2, 1, 2, 2, 1, 1, 1, 1]
-[;	1.0	1.34164	[2, 1, 2, 2, 1, 2, 2, -2, -1, 1]
-[=	1.7	0.64031	[2, 2, 1, 1, 1, 2, 2, 3, 2, 1]
-\-:	-1.0	1.18322	[-3, -1, -1, -1, -1, -1, 2, -2, -1, -1]
-\:	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
-\:<	-1.7	1.18743	[-1, -3, -2, -2, -3, -3, -2, -1, 1, -1]
-\=	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -1, -2, -1, -1]
-\^:	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -1, -2, -2, -1]
-\o/	2.2	0.9798	[2, 1, 1, 2, 4, 2, 2, 4, 2, 2]
-\o:	-1.2	0.4	[-1, -1, -1, -1, -2, -1, -1, -2, -1, -1]
-]-:	-2.1	0.53852	[-2, -3, -3, -2, -2, -2, -1, -2, -2, -2]
-]:	-1.6	0.66332	[-1, -2, -1, -2, -3, -2, -1, -1, -1, -2]
-]:<	-2.5	0.80623	[-2, -2, -2, -3, -4, -2, -2, -2, -2, -4]
-^<_<	1.4	1.11355	[3, 1, 3, 2, 1, 1, 1, -1, 2, 1]
-^urs	-2.8	0.6	[-2, -3, -3, -2, -3, -3, -2, -3, -4, -3]
-abandon	-1.9	0.53852	[-1, -2, -2, -2, -2, -3, -2, -2, -1, -2]
-abandoned	-2.0	1.09545	[-1, -1, -3, -2, -1, -4, -1, -3, -3, -1]
-abandoner	-1.9	0.83066	[-1, -1, -3, -2, -1, -3, -1, -2, -3, -2]
-abandoners	-1.9	0.83066	[-2, -3, -2, -3, -2, -1, -2, -2, 0, -2]
-abandoning	-1.6	0.8	[-3, -2, -3, -2, -1, -1, -1, -1, -1, -1]
-abandonment	-2.4	1.0198	[-4, -2, -1, -4, -2, -1, -2, -3, -3, -2]
-abandonments	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
-abandons	-1.3	0.9	[-2, -1, -1, -2, -1, -2, -1, -2, 1, -2]
-abducted	-2.3	1.18743	[-3, -1, 0, -3, -1, -3, -4, -2, -3, -3]
-abduction	-2.8	0.87178	[-4, -3, -3, -4, -1, -3, -2, -2, -3, -3]
-abductions	-2.0	1.41421	[-3, -4, -1, -3, -1, -3, 1, -2, -1, -3]
-abhor	-2.0	1.09545	[-3, -3, -1, -1, -2, -1, -3, -3, 0, -3]
-abhorred	-2.4	1.49666	[-4, -4, 0, -3, -2, -1, -4, -3, -3, 0]
-abhorrent	-3.1	1.3	[-4, -4, -4, -2, 0, -4, -2, -3, -4, -4]
-abhors	-2.9	1.51327	[0, -4, -3, -3, -4, -4, 0, -4, -3, -4]
-abilities	1.0	0.63246	[1, 2, 0, 1, 0, 1, 1, 1, 1, 2]
-ability	1.3	0.64031	[1, 1, 1, 0, 1, 2, 2, 2, 2, 1]
-aboard	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
-absentee	-1.1	0.53852	[-1, -1, 0, -2, -1, -1, -2, -1, -1, -1]
-absentees	-0.8	0.6	[-1, 0, 0, -1, -1, 0, -2, -1, -1, -1]
-absolve	1.2	1.46969	[2, -3, 2, 2, 1, 1, 2, 1, 2, 2]
-absolved	1.5	0.92195	[3, 1, 2, 1, 0, 2, 3, 1, 1, 1]
-absolves	1.3	1.00499	[3, 1, 1, 0, 0, 2, 3, 1, 1, 1]
-absolving	1.6	0.8	[3, 1, 2, 1, 1, 2, 3, 1, 1, 1]
-abuse	-3.2	0.6	[-4, -2, -3, -4, -3, -4, -3, -3, -3, -3]
-abused	-2.3	0.64031	[-2, -2, -3, -2, -2, -4, -2, -2, -2, -2]
-abuser	-2.6	0.4899	[-3, -2, -3, -3, -2, -3, -2, -2, -3, -3]
-abusers	-2.6	1.0198	[-2, -3, -3, -3, -3, -2, -3, -4, -3, 0]
-abuses	-2.6	0.66332	[-3, -2, -3, -3, -3, -3, -1, -2, -3, -3]
-abusing	-2.0	1.41421	[-1, -2, -2, -4, -4, -2, -3, -1, 1, -2]
-abusive	-3.2	0.74833	[-4, -3, -3, -4, -4, -3, -4, -2, -3, -2]
-abusively	-2.8	0.6	[-3, -4, -3, -2, -3, -2, -2, -3, -3, -3]
-abusiveness	-2.5	0.92195	[-2, -4, -2, -3, -2, -3, -4, -2, -1, -2]
-abusivenesses	-3.0	0.63246	[-3, -3, -4, -3, -4, -2, -2, -3, -3, -3]
-accept	1.6	0.91652	[2, 1, 2, 1, 1, 2, 4, 1, 1, 1]
-acceptabilities	1.6	0.66332	[0, 2, 2, 2, 1, 2, 2, 2, 1, 2]
-acceptability	1.1	0.53852	[1, 0, 1, 2, 1, 2, 1, 1, 1, 1]
-acceptable	1.3	0.45826	[1, 2, 1, 1, 1, 2, 1, 1, 2, 1]
-acceptableness	1.3	0.9	[1, 0, 2, 1, 2, 1, 1, 0, 2, 3]
-acceptably	1.5	0.67082	[3, 2, 1, 1, 1, 2, 1, 1, 2, 1]
-acceptance	2.0	0.63246	[3, 1, 3, 2, 1, 2, 2, 2, 2, 2]
-acceptances	1.7	0.78102	[3, 1, 1, 1, 2, 2, 1, 2, 3, 1]
-acceptant	1.6	0.8	[0, 1, 2, 2, 2, 1, 2, 1, 3, 2]
-acceptation	1.3	0.78102	[0, 1, 2, 1, 1, 1, 1, 3, 2, 1]
-acceptations	0.9	0.83066	[1, 2, 0, 2, 0, 1, 0, 2, 1, 0]
-accepted	1.1	0.3	[1, 1, 1, 1, 1, 2, 1, 1, 1, 1]
-accepting	1.6	0.66332	[2, 2, 2, 1, 1, 2, 1, 3, 1, 1]
-accepts	1.3	0.45826	[1, 2, 1, 1, 1, 2, 2, 1, 1, 1]
-accident	-2.1	0.83066	[-2, -2, -1, -3, -4, -2, -2, -1, -2, -2]
-accidental	-0.3	0.45826	[-1, -1, 0, 0, 0, 0, 0, 0, -1, 0]
-accidentally	-1.4	0.91652	[-2, 0, -2, 0, -3, -1, -1, -1, -2, -2]
-accidents	-1.3	0.78102	[-1, -1, -1, -1, -2, 0, -3, -1, -2, -1]
-accomplish	1.8	0.6	[1, 2, 3, 2, 2, 2, 1, 1, 2, 2]
-accomplished	1.9	0.53852	[2, 2, 2, 1, 2, 2, 3, 1, 2, 2]
-accomplishes	1.7	0.9	[2, 2, 1, 0, 2, 3, 3, 1, 1, 2]
-accusation	-1.0	1.09545	[-1, -1, -2, -2, -2, -1, -1, -1, 2, -1]
-accusations	-1.3	1.26886	[-2, -2, -1, -3, -2, -1, -1, 2, -2, -1]
-accuse	-0.8	1.53623	[-3, -1, -1, -2, 1, -2, 1, -2, 2, -1]
-accused	-1.2	1.46969	[-2, -1, -2, 2, -2, -3, -2, -2, -1, 1]
-accuses	-1.4	1.0198	[-2, -1, -2, 1, -2, -3, -1, -2, -1, -1]
-accusing	-0.7	1.34536	[-2, -1, -1, 1, -3, -1, -1, 2, -1, 0]
-ache	-1.6	1.2	[-1, -2, -2, -2, -1, -4, -1, 1, -2, -2]
-ached	-1.6	0.8	[-2, -2, -1, -2, -1, -2, -3, 0, -1, -2]
-aches	-1.0	0.7746	[-1, -2, -1, -1, -1, 1, -2, -1, -1, -1]
-achievable	1.3	0.45826	[2, 1, 1, 1, 1, 1, 1, 2, 2, 1]
-aching	-2.2	0.74833	[-2, -3, -2, -1, -3, -3, -2, -3, -1, -2]
-acquit	0.8	1.72047	[-3, 3, -1, 3, 2, 1, 1, 1, 0, 1]
-acquits	0.1	1.37477	[1, -3, -1, 0, 2, 0, -1, 1, 1, 1]
-acquitted	1.0	0.89443	[2, 2, 1, 1, 2, 0, 1, 1, -1, 1]
-acquitting	1.3	0.78102	[3, 2, 0, 1, 1, 1, 2, 1, 1, 1]
-acrimonious	-1.7	1.73494	[-1, -3, -2, -3, 3, -3, -1, -2, -2, -3]
-active	1.7	1.26886	[1, 2, 1, 1, 1, 4, 2, 4, 0, 1]
-actively	1.3	0.78102	[0, 1, 0, 2, 2, 1, 1, 2, 2, 2]
-activeness	0.6	0.8	[0, 2, 0, 0, 1, 0, 1, 0, 2, 0]
-activenesses	0.8	0.74833	[2, 0, 1, 0, 0, 0, 1, 2, 1, 1]
-actives	1.1	0.7	[2, 1, 0, 1, 1, 0, 1, 1, 2, 2]
-adequate	0.9	0.7	[0, 0, 1, 1, 0, 2, 1, 1, 2, 1]
-admirability	2.4	0.4899	[2, 3, 3, 3, 3, 2, 2, 2, 2, 2]
-admirable	2.6	0.66332	[2, 3, 3, 3, 4, 3, 2, 2, 2, 2]
-admirableness	2.2	0.87178	[2, 2, 3, 3, 3, 1, 3, 1, 3, 1]
-admirably	2.5	0.67082	[2, 3, 3, 3, 4, 2, 2, 2, 2, 2]
-admiral	1.3	1.18743	[0, 0, 1, 3, 3, 2, 2, 0, 2, 0]
-admirals	1.5	0.80623	[2, 2, 0, 2, 2, 0, 1, 2, 2, 2]
-admiralties	1.6	0.66332	[2, 2, 2, 1, 0, 2, 2, 2, 1, 2]
-admiralty	1.2	1.53623	[0, 4, 0, 0, 0, 2, 2, 3, 2, -1]
-admiration	2.5	0.80623	[3, 1, 1, 3, 3, 2, 3, 3, 3, 3]
-admirations	1.6	0.66332	[2, 2, 1, 1, 2, 2, 2, 2, 2, 0]
-admire	2.1	0.83066	[3, 3, 1, 3, 3, 2, 1, 2, 1, 2]
-admired	2.3	0.78102	[4, 2, 2, 2, 2, 2, 3, 3, 1, 2]
-admirer	1.8	0.74833	[2, 1, 1, 2, 3, 2, 3, 1, 1, 2]
-admirers	1.7	1.00499	[2, 3, 2, 2, 2, 1, -1, 2, 2, 2]
-admires	1.5	0.67082	[3, 1, 1, 2, 1, 2, 2, 1, 1, 1]
-admiring	1.6	0.8	[1, 2, 1, 1, 3, 3, 2, 1, 1, 1]
-admiringly	2.3	0.64031	[1, 3, 3, 2, 2, 2, 2, 3, 3, 2]
-admit	0.8	1.07703	[0, 0, 0, 0, 0, 1, 3, 2, 2, 0]
-admits	1.2	0.87178	[1, 2, 2, 2, 0, 0, 1, 2, 0, 2]
-admitted	0.4	0.66332	[0, 1, 0, 1, 0, 0, 2, 0, 0, 0]
-admonished	-1.9	0.9434	[-2, -2, -2, -1, -2, -3, -1, -1, -1, -4]
-adopt	0.7	0.64031	[0, 0, 1, 1, 1, 0, 1, 0, 1, 2]
-adopts	0.7	0.64031	[0, 0, 1, 2, 1, 0, 1, 1, 0, 1]
-adorability	2.2	0.74833	[2, 2, 2, 2, 1, 2, 3, 2, 4, 2]
-adorable	2.2	0.6	[3, 2, 2, 3, 2, 2, 1, 3, 2, 2]
-adorableness	2.5	0.67082	[2, 3, 3, 2, 3, 2, 1, 3, 3, 3]
-adorably	2.1	0.7	[3, 1, 2, 3, 2, 2, 1, 3, 2, 2]
-adoration	2.9	0.7	[3, 3, 3, 2, 3, 3, 4, 2, 4, 2]
-adorations	2.2	0.87178	[2, 2, 3, 1, 3, 1, 3, 3, 1, 3]
-adore	2.6	0.91652	[3, 3, 1, 2, 3, 3, 3, 4, 1, 3]
-adored	1.8	0.87178	[2, 3, 3, 2, 2, 1, 1, 0, 2, 2]
-adorer	1.7	1.1	[2, 4, 3, 1, 2, 1, 1, 0, 2, 1]
-adorers	2.1	0.7	[3, 2, 1, 2, 2, 2, 3, 2, 3, 1]
-adores	1.6	0.66332	[2, 1, 3, 2, 2, 1, 1, 1, 2, 1]
-adoring	2.6	0.66332	[2, 3, 3, 3, 1, 3, 3, 2, 3, 3]
-adoringly	2.4	0.8	[2, 3, 2, 3, 3, 3, 3, 1, 1, 3]
-adorn	0.9	0.53852	[1, 1, 1, 0, 2, 1, 1, 0, 1, 1]
-adorned	0.8	1.249	[1, 1, 0, 2, -1, 3, -1, 2, 1, 0]
-adorner	1.3	0.78102	[1, 1, 1, 2, 1, 3, 1, 2, 1, 0]
-adorners	0.9	0.9434	[2, 2, 0, 1, -1, 2, 1, 1, 0, 1]
-adorning	1.0	0.7746	[0, 0, 1, 1, 1, 2, 2, 1, 0, 2]
-adornment	1.3	0.78102	[1, 3, 1, 0, 2, 2, 1, 1, 1, 1]
-adornments	0.8	1.16619	[2, -1, 0, 0, 2, 1, 2, -1, 1, 2]
-adorns	0.5	1.56525	[3, -1, 1, 0, 2, -1, 3, -1, 0, -1]
-advanced	1.0	0.63246	[1, 0, 1, 1, 1, 0, 1, 2, 1, 2]
-advantage	1.0	0.63246	[1, 2, 1, 1, 2, 0, 1, 0, 1, 1]
-advantaged	1.4	0.91652	[1, 0, 3, 0, 1, 1, 2, 2, 2, 2]
-advantageous	1.5	0.67082	[2, 0, 2, 2, 2, 1, 1, 1, 2, 2]
-advantageously	1.9	0.53852	[2, 2, 2, 3, 2, 2, 2, 1, 1, 2]
-advantageousness	1.6	1.28062	[-2, 2, 3, 1, 2, 2, 2, 2, 2, 2]
-advantages	1.5	0.80623	[1, 0, 3, 1, 1, 1, 2, 2, 2, 2]
-advantaging	1.6	0.66332	[3, 1, 1, 2, 1, 1, 2, 2, 2, 1]
-adventure	1.3	0.45826	[1, 2, 1, 1, 2, 1, 1, 1, 1, 2]
-adventured	1.3	0.45826	[1, 2, 1, 2, 1, 2, 1, 1, 1, 1]
-adventurer	1.2	0.6	[1, 2, 0, 2, 1, 2, 1, 1, 1, 1]
-adventurers	0.9	0.9434	[0, 1, 0, 1, 0, 1, 0, 1, 3, 2]
-adventures	1.4	1.2	[2, 2, 1, 2, -2, 2, 2, 1, 2, 2]
-adventuresome	1.7	1.1	[0, 3, 0, 1, 2, 2, 3, 1, 2, 3]
-adventuresomeness	1.3	1.00499	[1, 0, 0, 2, 3, 2, 2, 0, 1, 2]
-adventuress	0.8	1.72047	[3, -1, 2, 2, 0, 0, 1, 2, -3, 2]
-adventuresses	1.4	1.11355	[1, 0, 0, 3, 2, 2, 3, 0, 1, 2]
-adventuring	2.3	0.78102	[2, 3, 2, 3, 1, 3, 3, 1, 2, 3]
-adventurism	1.5	0.67082	[1, 0, 2, 2, 2, 2, 1, 1, 2, 2]
-adventurist	1.4	0.4899	[1, 1, 2, 1, 2, 2, 2, 1, 1, 1]
-adventuristic	1.7	0.64031	[2, 1, 1, 2, 2, 1, 3, 2, 2, 1]
-adventurists	1.2	0.9798	[3, 1, 0, 0, 1, 2, 1, 0, 2, 2]
-adventurous	1.4	1.11355	[0, 1, 2, 1, 2, 0, 3, 2, 3, 0]
-adventurously	1.3	0.9	[0, 1, 2, 2, 1, 2, 1, 1, 0, 3]
-adventurousness	1.8	0.87178	[0, 1, 3, 2, 1, 3, 2, 2, 2, 2]
-adversarial	-1.5	0.92195	[-2, 0, -1, -3, -2, -2, 0, -1, -2, -2]
-adversaries	-1.0	0.63246	[-1, -1, -1, -1, 0, -2, -2, -1, -1, 0]
-adversary	-0.8	1.72047	[-3, -1, -2, -2, -2, 2, 1, -1, 2, -2]
-adversative	-1.2	0.74833	[-1, -1, -2, -1, -1, -1, -3, -1, 0, -1]
-adversatively	-0.1	1.37477	[0, -2, -1, 0, -1, -1, 1, 1, 3, -1]
-adversatives	-1.0	0.7746	[-1, -1, -2, -1, -2, 1, -1, -1, -1, -1]
-adverse	-1.5	0.80623	[-2, -2, -2, -1, -1, 0, -1, -3, -1, -2]
-adversely	-0.8	1.6	[-2, -2, 0, -2, -2, 2, -2, 2, -2, 0]
-adverseness	-0.6	1.35647	[-1, -2, -1, 2, -1, -2, -1, 2, -1, -1]
-adversities	-1.5	0.67082	[-2, -2, -1, -1, -2, 0, -2, -1, -2, -2]
-adversity	-1.8	0.6	[-3, -2, -1, -2, -2, -2, -1, -1, -2, -2]
-affected	-0.6	1.35647	[-1, -2, 0, -2, 0, 0, 2, -2, 1, -2]
-affection	2.4	0.8	[3, 2, 2, 3, 4, 1, 3, 2, 2, 2]
-affectional	1.9	1.04403	[3, 3, 2, 0, 2, 2, 2, 3, 2, 0]
-affectionally	1.5	0.92195	[1, 1, 3, 1, 1, 0, 2, 2, 3, 1]
-affectionate	1.9	1.13578	[1, 0, 3, 1, 3, 2, 2, 1, 2, 4]
-affectionately	2.2	0.87178	[4, 1, 1, 2, 2, 2, 3, 3, 2, 2]
-affectioned	1.8	0.4	[2, 2, 1, 2, 2, 1, 2, 2, 2, 2]
-affectionless	-2.0	0.44721	[-2, -1, -2, -2, -2, -2, -2, -2, -2, -3]
-affections	1.5	1.11803	[-1, 3, 2, 2, 1, 1, 2, 1, 3, 1]
-afflicted	-1.5	1.0247	[-1, -2, -3, -2, 1, -1, -1, -2, -2, -2]
-affronted	0.2	2.03961	[1, -2, 2, -2, -2, 4, 0, 2, 1, -2]
-aggravate	-2.5	0.80623	[-3, -3, -2, -3, -2, -4, -3, -2, -2, -1]
-aggravated	-1.9	1.04403	[-4, -3, -3, -1, -1, -1, -1, -2, -2, -1]
-aggravates	-1.9	0.83066	[-3, -2, -2, -2, -3, -1, -2, -2, 0, -2]
-aggravating	-1.2	0.9798	[-2, -2, -1, -2, -2, -1, 0, 1, -1, -2]
-aggress	-1.3	1.55242	[-2, -2, 2, -2, -1, -3, -3, -1, 1, -2]
-aggressed	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -2, -2, -1]
-aggresses	-0.5	1.43178	[-1, -2, -1, -1, -3, 0, -1, 1, 2, 1]
-aggressing	-0.6	1.28062	[-1, -2, -1, 0, -1, -2, 2, -2, 1, 0]
-aggression	-1.2	1.77764	[-2, -2, 1, 1, -4, 2, -2, -2, -2, -2]
-aggressions	-1.3	1.48661	[-1, -2, -2, -2, -2, -3, 1, -2, 2, -2]
-aggressive	-0.6	1.28062	[-2, 1, -2, -2, 0, -2, -1, 1, 1, 0]
-aggressively	-1.3	1.55242	[-1, -2, 3, -2, -3, -2, -1, -1, -2, -2]
-aggressiveness	-1.8	0.74833	[-1, -2, -1, -2, -2, -1, -3, -1, -3, -2]
-aggressivities	-1.4	1.28062	[-1, -1, -1, -2, 2, -2, -2, -2, -3, -2]
-aggressivity	-0.6	1.35647	[-3, -1, 1, 0, 0, 0, -3, -1, 1, 0]
-aggressor	-0.8	1.32665	[-2, 0, -1, 2, -2, -2, -1, -1, -2, 1]
-aggressors	-0.9	1.13578	[-2, -2, -1, -1, -1, 1, 1, 0, -2, -2]
-aghast	-1.9	1.04403	[-2, -3, -1, 0, -2, -1, -4, -2, -2, -2]
-agitate	-1.7	0.64031	[-2, -2, -3, -1, -1, -1, -2, -1, -2, -2]
-agitated	-2.0	0.63246	[-2, -2, -2, -2, -1, -3, -3, -2, -2, -1]
-agitatedly	-1.6	0.8	[-1, -2, -1, -3, -1, -3, -1, -1, -2, -1]
-agitates	-1.4	0.8	[-2, 0, -1, -2, -1, -1, -3, -1, -2, -1]
-agitating	-1.8	0.87178	[-2, -1, -1, -1, -2, -3, -1, -3, -3, -1]
-agitation	-1.0	1.09545	[-2, -1, 1, -1, -2, -1, -2, -1, 1, -2]
-agitational	-1.2	1.66132	[-3, -3, -2, 1, -1, -2, 0, 2, -1, -3]
-agitations	-1.3	1.18743	[-1, -2, -1, -3, -2, -3, 0, -1, 1, -1]
-agitative	-1.3	1.26886	[-2, -2, -1, -2, -1, -3, 1, -2, 1, -2]
-agitato	-0.1	1.13578	[1, 2, 0, 0, 0, 0, -2, 0, -2, 0]
-agitator	-1.4	0.8	[-1, -1, -1, -2, -1, -1, -2, -3, -2, 0]
-agitators	-2.1	0.9434	[-2, -3, -3, -2, -2, -1, -3, -2, 0, -3]
-agog	1.9	0.7	[2, 1, 3, 3, 2, 1, 2, 2, 1, 2]
-agonise	-2.1	0.9434	[-3, -3, -2, -3, -1, -3, -1, -3, -1, -1]
-agonised	-2.3	0.64031	[-2, -3, -3, -2, -2, -2, -2, -3, -1, -3]
-agonises	-2.4	0.91652	[-1, -4, -3, -3, -2, -2, -2, -3, -1, -3]
-agonising	-1.5	1.43178	[-3, -2, -3, -3, -1, 1, 0, 0, -1, -3]
-agonize	-2.3	0.9	[-2, -3, -1, -2, -2, -2, -4, -1, -3, -3]
-agonized	-2.2	1.249	[-2, -3, -3, -3, -3, -2, -1, -3, 1, -3]
-agonizes	-2.3	1.18743	[-1, -3, -4, -3, -3, -2, -1, -3, 0, -3]
-agonizing	-2.7	0.78102	[-3, -2, -2, -2, -4, -3, -3, -2, -4, -2]
-agonizingly	-2.3	1.48661	[-3, -1, -3, -4, -4, -2, -3, 1, -1, -3]
-agony	-1.8	1.16619	[-3, -1, -2, -4, -2, -1, 0, -3, -1, -1]
-agree	1.5	1.11803	[1, 0, 3, 1, 2, 1, 4, 1, 1, 1]
-agreeability	1.9	1.04403	[1, 1, 1, 3, 3, 2, 1, 2, 4, 1]
-agreeable	1.8	0.4	[2, 1, 2, 1, 2, 2, 2, 2, 2, 2]
-agreeableness	1.8	0.9798	[2, 3, 2, 1, 1, 1, 4, 1, 2, 1]
-agreeablenesses	1.3	0.45826	[2, 1, 1, 2, 1, 2, 1, 1, 1, 1]
-agreeably	1.6	0.4899	[1, 1, 2, 1, 1, 2, 2, 2, 2, 2]
-agreed	1.1	0.53852	[1, 1, 2, 1, 1, 2, 1, 0, 1, 1]
-agreeing	1.4	0.4899	[1, 1, 1, 1, 2, 1, 1, 2, 2, 2]
-agreement	2.2	0.74833	[2, 1, 1, 3, 3, 3, 2, 2, 2, 3]
-agreements	1.1	1.13578	[0, 1, 0, 1, 1, 2, 1, 0, 4, 1]
-agrees	0.8	1.4	[1, 1, 1, 1, 3, 1, -3, 1, 1, 1]
-alarm	-1.4	0.91652	[-1, -1, -2, -2, -2, -2, -1, 1, -2, -2]
-alarmed	-1.4	0.4899	[-2, -1, -2, -2, -1, -1, -1, -2, -1, -1]
-alarming	-0.5	1.62788	[-1, 1, -1, 1, -3, 1, -2, -3, 1, 1]
-alarmingly	-2.6	0.91652	[-3, -3, -4, -3, -2, -1, -3, -3, -1, -3]
-alarmism	-0.3	1.26886	[-2, 0, -2, -1, 0, 1, 1, -1, 2, -1]
-alarmists	-1.1	1.3	[-1, -2, -3, -2, -1, -2, 1, 1, 0, -2]
-alarms	-1.1	1.04403	[-2, 0, -2, -1, 0, 0, 0, -1, -2, -3]
-alas	-1.1	1.22066	[-1, -2, -1, 0, -1, 0, 1, -3, -1, -3]
-alert	1.2	0.87178	[1, 2, 0, 1, 0, 2, 2, 0, 2, 2]
-alienation	-1.1	1.51327	[-3, -2, -3, -1, -2, -1, 2, -1, 1, -1]
-alive	1.6	0.8	[1, 1, 2, 3, 3, 2, 1, 1, 1, 1]
-allergic	-1.2	0.4	[-1, -2, -1, -2, -1, -1, -1, -1, -1, -1]
-allow	0.9	0.83066	[0, 0, 0, 1, 2, 2, 1, 1, 2, 0]
-alone	-1.0	0.63246	[-2, -1, -1, -1, -2, -1, 0, -1, -1, 0]
-alright	1.0	0.7746	[0, 1, 0, 3, 1, 1, 1, 1, 1, 1]
-amaze	2.5	1.0247	[3, 2, 3, 4, 2, 3, 1, 4, 2, 1]
-amazed	2.2	1.07703	[1, 0, 3, 2, 2, 4, 3, 3, 2, 2]
-amazedly	2.1	0.53852	[2, 2, 2, 2, 3, 2, 2, 3, 1, 2]
-amazement	2.5	0.80623	[3, 3, 2, 4, 1, 2, 2, 3, 2, 3]
-amazements	2.2	0.87178	[3, 1, 1, 3, 3, 2, 1, 2, 3, 3]
-amazes	2.2	0.9798	[1, 0, 3, 2, 2, 3, 3, 3, 2, 3]
-amazing	2.8	0.87178	[1, 4, 3, 2, 4, 2, 3, 3, 3, 3]
-amazon	0.7	0.64031	[0, 1, 1, 0, 1, 0, 1, 0, 1, 2]
-amazonite	0.2	0.6	[0, 0, 2, 0, 0, 0, 0, 0, 0, 0]
-amazons	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, -1, 0]
-amazonstone	1.0	1.61245	[0, 0, 0, 0, 4, 4, 2, 0, 0, 0]
-amazonstones	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
-ambitious	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 2, 3, 1]
-ambivalent	0.5	0.92195	[0, 0, -1, 2, 1, 1, 1, -1, 1, 1]
-amor	3.0	0.63246	[3, 3, 2, 4, 3, 2, 4, 3, 3, 3]
-amoral	-1.6	0.66332	[-1, -2, 0, -2, -2, -2, -2, -2, -1, -2]
-amoralism	-0.7	1.34536	[-2, -1, -2, 0, 0, -3, 2, 0, -1, 0]
-amoralisms	-0.7	1.00499	[-2, 0, 1, -1, -2, -1, -1, 1, -1, -1]
-amoralities	-1.2	1.6	[-3, 0, 0, -2, 1, -1, 0, -4, -3, 0]
-amorality	-1.5	0.92195	[0, -1, -1, -2, -1, -3, -1, -3, -2, -1]
-amorally	-1.0	1.61245	[-2, 0, 1, -4, -1, 1, 1, -2, -2, -2]
-amoretti	0.2	0.4	[0, 0, 0, 1, 0, 0, 0, 0, 0, 1]
-amoretto	0.6	0.8	[0, 1, 0, 1, 0, 0, 2, 0, 0, 2]
-amorettos	0.3	0.64031	[0, 1, 0, 1, 0, 0, 0, 1, 1, -1]
-amorino	1.2	0.87178	[2, 1, 1, 0, 3, 1, 1, 0, 1, 2]
-amorist	1.6	1.0198	[3, 0, 0, 2, 2, 1, 3, 1, 2, 2]
-amoristic	1.0	1.67332	[1, 0, 2, 3, -1, 3, 1, 3, 0, -2]
-amorists	0.1	0.9434	[0, 2, 0, 0, 1, 0, -2, 0, 0, 0]
-amoroso	2.3	0.78102	[3, 1, 1, 2, 3, 3, 3, 3, 2, 2]
-amorous	1.8	0.9798	[3, 1, 2, 2, 1, 1, 3, 0, 2, 3]
-amorously	2.3	0.78102	[1, 1, 3, 2, 3, 3, 2, 3, 2, 3]
-amorousness	2.0	0.89443	[2, 3, 1, 2, 0, 2, 2, 3, 3, 2]
-amorphous	-0.2	0.4	[0, 0, 0, 0, 0, 0, -1, 0, 0, -1]
-amorphously	0.1	0.7	[-1, 0, 0, 0, 0, 0, 2, 0, 0, 0]
-amorphousness	0.3	0.45826	[0, 0, 0, 0, 0, 1, 1, 1, 0, 0]
-amort	-2.1	0.83066	[-3, -1, -2, -2, -2, -2, -2, -4, -1, -2]
-amortise	0.5	1.43178	[0, 1, 1, 0, -3, 2, 0, 0, 2, 2]
-amortised	-0.2	1.16619	[-1, -3, 0, 0, 0, 2, 0, 0, 0, 0]
-amortises	0.1	0.83066	[-1, -1, 0, 0, 0, 2, 1, 0, 0, 0]
-amortizable	0.5	1.0247	[2, 0, 1, 0, 1, 1, -2, 1, 0, 1]
-amortization	0.6	1.0198	[0, 0, 0, 0, 1, 0, 0, 0, 3, 2]
-amortizations	0.2	1.07703	[-1, 1, 0, 0, 1, 0, 2, 1, -2, 0]
-amortize	-0.1	1.04403	[0, 0, 0, 0, 2, -2, -1, 1, -1, 0]
-amortized	0.8	0.74833	[0, 2, 0, 0, 1, 1, 1, 0, 1, 2]
-amortizes	0.6	0.8	[0, 2, 0, 0, 1, 1, 0, 0, 0, 2]
-amortizing	0.8	1.249	[0, 3, 0, 0, 0, 0, 0, 0, 3, 2]
-amusable	0.7	1.18743	[2, 1, 1, 1, 1, 1, 2, -2, -1, 1]
-amuse	1.7	0.78102	[1, 2, 1, 1, 2, 1, 1, 3, 3, 2]
-amused	1.8	0.6	[1, 2, 2, 2, 2, 2, 1, 2, 3, 1]
-amusedly	2.2	0.74833	[3, 3, 2, 2, 3, 2, 2, 3, 1, 1]
-amusement	1.5	1.11803	[3, 2, 3, 1, 2, 2, -1, 1, 1, 1]
-amusements	1.5	1.0247	[2, 1, 2, 1, 2, 2, 3, -1, 2, 1]
-amuser	1.1	1.7	[2, 1, -3, 2, 2, 3, -1, 1, 2, 2]
-amusers	1.3	0.45826	[1, 1, 2, 1, 2, 1, 2, 1, 1, 1]
-amuses	1.7	0.64031	[1, 2, 1, 2, 2, 2, 1, 2, 3, 1]
-amusia	0.3	1.48661	[0, -1, 1, -1, 2, 2, -1, -1, -1, 3]
-amusias	-0.4	0.66332	[-1, 0, 0, 1, 0, 0, -1, -1, -1, -1]
-amusing	1.6	0.91652	[2, 2, 2, -1, 2, 2, 1, 2, 2, 2]
-amusingly	0.8	1.249	[1, 2, 1, 1, 1, 2, 2, -2, -1, 1]
-amusingness	1.8	0.6	[1, 2, 3, 2, 1, 2, 2, 1, 2, 2]
-amusive	1.7	1.1	[3, 1, 3, 1, 2, 2, 2, 2, -1, 2]
-anger	-2.7	1.18743	[-1, -2, -3, -2, -4, -4, -2, -1, -4, -4]
-angered	-2.3	0.78102	[-2, -3, -2, -4, -2, -2, -3, -2, -2, -1]
-angering	-2.2	0.6	[-3, -2, -1, -3, -2, -2, -3, -2, -2, -2]
-angerly	-1.9	0.53852	[-2, -2, -1, -1, -3, -2, -2, -2, -2, -2]
-angers	-2.3	0.9	[-3, -1, -2, -3, -2, -2, -4, -1, -3, -2]
-angrier	-2.3	0.64031	[-2, -3, -2, -3, -1, -3, -2, -3, -2, -2]
-angriest	-3.1	0.83066	[-4, -3, -2, -2, -2, -4, -3, -4, -4, -3]
-angrily	-1.8	0.4	[-2, -1, -2, -2, -2, -1, -2, -2, -2, -2]
-angriness	-1.7	0.64031	[-2, 0, -2, -2, -1, -2, -2, -2, -2, -2]
-angry	-2.3	0.9	[-2, -2, -1, -3, -1, -2, -4, -2, -3, -3]
-anguish	-2.9	0.83066	[-3, -3, -2, -3, -4, -1, -3, -3, -4, -3]
-anguished	-1.8	1.4	[-3, -4, -1, -3, -2, -1, -1, 1, -1, -3]
-anguishes	-2.1	1.44568	[-4, -4, -2, -3, 1, -2, -1, -1, -2, -3]
-anguishing	-2.7	0.9	[-2, -2, -1, -3, -2, -4, -4, -3, -3, -3]
-animosity	-1.9	1.75784	[-2, -3, -3, -3, -2, 2, 1, -3, -3, -3]
-annoy	-1.9	0.53852	[-2, -2, -1, -2, -2, -1, -2, -2, -2, -3]
-annoyance	-1.3	1.55242	[-2, -3, -2, -2, -1, 1, -3, -2, 2, -1]
-annoyances	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -3, -1, -2, -2]
-annoyed	-1.6	1.11355	[-3, -1, 1, -3, -1, -1, -2, -2, -2, -2]
-annoyer	-2.2	0.87178	[-3, -2, -1, -3, -2, -4, -2, -1, -2, -2]
-annoyers	-1.5	1.0247	[-2, -1, -2, -3, -2, -1, -1, -2, 1, -2]
-annoying	-1.7	0.64031	[-1, -2, -1, -2, -1, -1, -2, -2, -3, -2]
-annoys	-1.8	0.6	[-1, -2, -3, -2, -2, -2, -1, -2, -1, -2]
-antagonism	-1.9	1.04403	[-1, -1, -3, -2, -4, -2, -2, 0, -2, -2]
-antagonisms	-1.2	1.53623	[0, -2, -2, -2, -2, -2, 3, -2, -1, -2]
-antagonist	-1.9	0.7	[-3, -1, -2, -3, -2, -2, -1, -2, -2, -1]
-antagonistic	-1.7	0.9	[-2, -2, -2, 1, -2, -2, -2, -2, -2, -2]
-antagonistically	-2.2	0.87178	[-2, -3, -4, -2, -2, -3, -2, -2, -1, -1]
-antagonists	-1.7	0.64031	[-2, -1, -1, -2, -1, -2, -2, -3, -1, -2]
-antagonize	-2.0	0.44721	[-2, -2, -2, -3, -2, -1, -2, -2, -2, -2]
-antagonized	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -2, -1, -1, -2]
-antagonizes	-0.5	1.9105	[-2, 4, -2, -2, 1, 0, -2, 1, -1, -2]
-antagonizing	-2.7	0.64031	[-4, -2, -2, -3, -2, -3, -3, -2, -3, -3]
-anti	-1.3	0.78102	[0, -2, -3, -1, -1, -2, -1, -1, -1, -1]
-anticipation	0.4	1.28062	[1, 1, -1, 0, -1, 1, 1, 2, -2, 2]
-anxieties	-0.6	1.85472	[-2, -3, -3, -2, -1, 2, -1, 1, 1, 2]
-anxiety	-0.7	2.1	[-2, -2, -2, -3, 3, -1, -3, 2, 2, -1]
-anxious	-1.0	0.44721	[-1, -2, -1, -1, 0, -1, -1, -1, -1, -1]
-anxiously	-0.9	0.83066	[-1, -1, -2, -1, -1, -1, -1, 0, 1, -2]
-anxiousness	-1.0	1.48324	[-2, -1, -1, -1, -1, -2, 3, -3, -1, -1]
-aok	2.0	0.89443	[2, 3, 2, 1, 2, 1, 1, 4, 2, 2]
-apathetic	-1.2	0.87178	[-1, -1, 0, -2, -2, -1, -1, 0, -3, -1]
-apathetically	-0.4	1.28062	[-1, -1, 0, -1, -2, 2, -1, -1, 2, -1]
-apathies	-0.6	1.0198	[-1, -1, -1, -2, 0, 1, -1, -2, 1, 0]
-apathy	-1.2	1.32665	[-2, -2, -1, 1, -1, -3, -1, 1, -1, -3]
-apeshit	-0.9	2.21133	[-4, -3, 2, -3, -2, -3, 1, 0, 2, 1]
-apocalyptic	-3.4	0.66332	[-4, -2, -3, -4, -3, -4, -4, -3, -3, -4]
-apologise	1.6	0.66332	[2, 3, 2, 2, 1, 1, 2, 1, 1, 1]
-apologised	0.4	0.91652	[-1, 0, 2, 0, 0, 1, 0, 2, 0, 0]
-apologises	0.8	1.07703	[2, 0, 2, 0, 0, 1, 0, 3, 0, 0]
-apologising	0.2	1.6	[0, -1, -1, 2, 2, 1, -2, -1, 3, -1]
-apologize	0.4	0.8	[1, -1, 0, 1, 1, 1, -1, 1, 0, 1]
-apologized	1.3	0.64031	[1, 1, 1, 2, 0, 2, 1, 2, 2, 1]
-apologizes	1.5	0.80623	[2, 1, 1, 2, 0, 2, 1, 2, 3, 1]
-apologizing	-0.3	1.34536	[1, 2, -1, 1, -1, 0, -3, 0, -1, -1]
-apology	0.2	1.249	[1, 1, 1, 1, -1, 1, -1, -1, -2, 2]
-appall	-2.4	0.66332	[-3, -2, -2, -3, -2, -3, -1, -3, -2, -3]
-appalled	-2.0	0.63246	[-3, -2, -3, -2, -2, -1, -1, -2, -2, -2]
-appalling	-1.5	1.5	[-2, -4, 1, -1, 1, -1, -2, -3, -2, -2]
-appallingly	-2.0	1.67332	[-3, -2, 0, -2, 2, -3, -4, -3, -2, -3]
-appalls	-1.9	1.37477	[0, -3, -2, -3, -3, -2, -1, -3, 1, -3]
-appease	1.1	0.9434	[1, 1, 1, -1, 2, 0, 1, 2, 2, 2]
-appeased	0.9	0.53852	[0, 1, 1, 1, 1, 1, 0, 1, 2, 1]
-appeases	0.9	0.53852	[0, 1, 1, 1, 1, 1, 0, 1, 2, 1]
-appeasing	1.0	1.09545	[1, 2, -1, 1, 2, 1, 2, 2, 1, -1]
-applaud	2.0	0.63246	[3, 2, 2, 2, 1, 2, 3, 1, 2, 2]
-applauded	1.5	0.5	[2, 2, 1, 2, 2, 2, 1, 1, 1, 1]
-applauding	2.1	0.83066	[2, 2, 4, 1, 2, 2, 2, 1, 2, 3]
-applauds	1.4	0.66332	[1, 1, 2, 1, 3, 1, 1, 1, 2, 1]
-applause	1.8	0.6	[2, 1, 1, 2, 3, 2, 1, 2, 2, 2]
-appreciate	1.7	0.78102	[2, 1, 2, 1, 1, 3, 1, 2, 3, 1]
-appreciated	2.3	0.78102	[2, 1, 3, 2, 3, 4, 2, 2, 2, 2]
-appreciates	2.3	0.9	[3, 1, 3, 1, 2, 4, 2, 3, 2, 2]
-appreciating	1.9	0.7	[1, 1, 2, 2, 2, 2, 1, 3, 2, 3]
-appreciation	2.3	0.9	[3, 3, 2, 1, 1, 3, 3, 1, 3, 3]
-appreciations	1.7	0.78102	[3, 2, 1, 2, 2, 1, 3, 1, 1, 1]
-appreciative	2.6	0.8	[3, 3, 3, 2, 1, 3, 4, 2, 2, 3]
-appreciatively	1.8	0.6	[2, 2, 2, 2, 2, 1, 3, 2, 1, 1]
-appreciativeness	1.6	0.8	[2, 1, 1, 2, 1, 1, 3, 3, 1, 1]
-appreciator	2.6	0.8	[2, 3, 2, 3, 3, 2, 1, 3, 4, 3]
-appreciators	1.5	0.80623	[1, 3, 1, 3, 1, 1, 2, 1, 1, 1]
-appreciatory	1.7	0.78102	[1, 2, 1, 3, 1, 3, 2, 2, 1, 1]
-apprehensible	1.1	1.04403	[2, 0, -1, 3, 1, 2, 1, 1, 1, 1]
-apprehensibly	-0.2	1.16619	[0, 0, -1, 2, -1, 2, -1, -1, -1, -1]
-apprehension	-2.1	0.83066	[-1, -2, -2, -1, -2, -3, -3, -3, -1, -3]
-apprehensions	-0.9	1.04403	[-1, -1, -1, -1, -2, -2, -1, -1, -1, 2]
-apprehensively	-0.3	1.18743	[-1, -1, -1, 0, 1, -2, -1, 1, -1, 2]
-apprehensiveness	-0.7	0.9	[-1, 1, -1, -1, 1, -1, -2, -1, -1, -1]
-approval	2.1	0.53852	[2, 2, 2, 2, 2, 1, 3, 3, 2, 2]
-approved	1.8	0.6	[1, 1, 1, 2, 3, 2, 2, 2, 2, 2]
-approves	1.7	0.64031	[1, 1, 1, 2, 3, 2, 2, 2, 2, 1]
-ardent	2.1	0.7	[3, 3, 2, 2, 3, 1, 2, 2, 1, 2]
-arguable	-1.0	0.63246	[-1, -1, -2, -1, -1, -2, 0, 0, -1, -1]
-arguably	-1.0	1.09545	[0, -2, 0, -2, 0, 1, -1, -2, -2, -2]
-argue	-1.4	0.66332	[-1, -2, -1, -3, -2, -1, -1, -1, -1, -1]
-argued	-1.5	0.5	[-2, -2, -1, -1, -1, -1, -2, -2, -2, -1]
-arguer	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -1]
-arguers	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -1]
-argues	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -1]
-arguing	-2.0	0.63246	[-3, -3, -1, -1, -2, -2, -2, -2, -2, -2]
-argument	-1.5	0.80623	[-3, -1, -1, -1, -1, -2, 0, -2, -2, -2]
-argumentative	-1.5	0.67082	[-3, -2, -1, -1, -1, -1, -1, -2, -2, -1]
-argumentatively	-1.8	0.9798	[-4, -2, -1, -1, -3, -1, -2, -2, -1, -1]
-argumentive	-1.5	0.80623	[-3, -2, -2, -1, 0, -1, -1, -1, -2, -2]
-arguments	-1.7	0.64031	[-1, -1, -2, -2, -2, -3, -2, -1, -1, -2]
-arrest	-1.4	1.42829	[-1, 0, -1, 0, -2, -3, 0, -4, -3, 0]
-arrested	-2.1	1.04403	[-2, -2, -2, -1, -1, -4, -1, -4, -2, -2]
-arrests	-1.9	0.83066	[-4, -2, -1, -1, -1, -2, -2, -2, -2, -2]
-arrogance	-2.4	0.66332	[-3, -2, -2, -3, -1, -2, -3, -3, -2, -3]
-arrogances	-1.9	0.53852	[-1, -2, -3, -2, -2, -2, -2, -1, -2, -2]
-arrogant	-2.2	0.6	[-2, -2, -2, -3, -2, -3, -3, -2, -1, -2]
-arrogantly	-1.8	1.4	[-3, -2, 2, -3, -1, -3, -2, -2, -2, -2]
-ashamed	-2.1	1.3	[-3, -3, -3, -2, -2, 1, -2, -4, -1, -2]
-ashamedly	-1.7	0.64031	[-2, -2, -2, -1, -2, -3, -1, -2, -1, -1]
-ass	-2.5	1.43178	[-4, -1, -2, -1, -3, 0, -2, -4, -4, -4]
-assassination	-2.9	0.9434	[-2, -4, -4, -3, -3, -4, -2, -3, -3, -1]
-assassinations	-2.7	1.34536	[-4, -2, -3, -2, -3, -1, -4, -4, 0, -4]
-assault	-2.8	0.9798	[-3, -4, -2, -2, -4, -3, -1, -3, -2, -4]
-assaulted	-2.4	1.28062	[-3, -3, 1, -3, -3, -3, -1, -3, -3, -3]
-assaulting	-2.3	1.1	[-4, -3, -2, -1, -2, -1, -1, -4, -3, -2]
-assaultive	-2.8	0.87178	[-3, -4, -2, -4, -3, -2, -3, -1, -3, -3]
-assaults	-2.5	0.92195	[-1, -3, -3, -3, -4, -3, -1, -2, -2, -3]
-asset	1.5	0.80623	[2, 1, 1, 3, 2, 0, 2, 2, 1, 1]
-assets	0.7	1.00499	[0, 0, 1, 3, 0, 1, 0, 0, 2, 0]
-assfucking	-2.5	1.43178	[-3, -3, 0, -3, 0, -2, -4, -4, -4, -2]
-assholes	-2.8	0.74833	[-3, -3, -3, -3, -4, -3, -2, -3, -1, -3]
-assurance	1.4	0.4899	[1, 1, 2, 2, 1, 1, 1, 2, 2, 1]
-assurances	1.4	0.4899	[2, 2, 1, 1, 1, 2, 2, 1, 1, 1]
-assure	1.4	0.4899	[1, 1, 1, 1, 2, 1, 1, 2, 2, 2]
-assured	1.5	0.67082	[1, 1, 2, 1, 1, 3, 2, 1, 2, 1]
-assuredly	1.6	0.66332	[1, 1, 1, 3, 2, 2, 2, 1, 2, 1]
-assuredness	1.4	0.8	[2, 2, 2, 1, 1, 0, 2, 0, 2, 2]
-assurer	0.9	1.13578	[2, 1, 0, 1, -2, 2, 2, 1, 1, 1]
-assurers	1.1	0.9434	[2, 0, 0, 1, 3, 2, 0, 1, 1, 1]
-assures	1.3	0.45826	[2, 1, 1, 1, 2, 1, 2, 1, 1, 1]
-assurgent	1.3	0.9	[2, 1, 0, 0, 1, 2, 1, 2, 3, 1]
-assuring	1.6	0.66332	[1, 2, 2, 3, 1, 1, 1, 1, 2, 2]
-assuror	0.5	0.67082	[0, 1, 0, 1, 2, 0, 0, 1, 0, 0]
-assurors	0.7	1.34536	[2, -1, 0, 2, 0, -2, 2, 1, 1, 2]
-astonished	1.6	0.8	[3, 1, 0, 2, 2, 1, 2, 2, 1, 2]
-astound	1.7	1.26886	[2, 2, 2, 2, 0, 3, 4, 0, 0, 2]
-astounded	1.8	0.9798	[1, 3, 0, 1, 2, 2, 3, 2, 1, 3]
-astounding	1.8	1.4	[3, 4, 2, 0, 1, 2, -1, 3, 2, 2]
-astoundingly	2.1	1.44568	[3, 0, 4, 1, 4, 3, 1, 3, 0, 2]
-astounds	2.1	1.22066	[3, 3, 1, 0, 3, 2, 3, 3, 0, 3]
-attachment	1.2	0.9798	[2, 0, 1, 2, 3, 1, 1, 2, 0, 0]
-attachments	1.1	0.7	[1, 1, 2, 0, 2, 1, 2, 0, 1, 1]
-attack	-2.1	0.83066	[-1, -3, -2, -3, -3, -1, -2, -1, -2, -3]
-attacked	-2.0	1.78885	[-2, 3, -2, -2, -3, -3, -3, -4, -2, -2]
-attacker	-2.7	0.9	[-2, -3, -2, -1, -3, -3, -4, -4, -2, -3]
-attackers	-2.7	0.64031	[-3, -3, -3, -2, -3, -3, -4, -2, -2, -2]
-attacking	-2.0	0.89443	[-3, -1, -1, -3, -3, -1, -3, -1, -2, -2]
-attacks	-1.9	0.9434	[-2, -2, 0, -2, -2, -2, -1, -4, -2, -2]
-attract	1.5	0.92195	[1, 3, 1, 1, 3, 1, 1, 2, 0, 2]
-attractancy	0.9	0.7	[1, 0, 2, 1, 0, 2, 1, 1, 0, 1]
-attractant	1.3	0.9	[0, 1, 0, 1, 1, 2, 3, 2, 1, 2]
-attractants	1.4	0.8	[1, 1, 0, 2, 2, 2, 3, 1, 1, 1]
-attracted	1.8	0.6	[1, 3, 1, 2, 2, 2, 2, 2, 2, 1]
-attracting	2.1	0.83066	[3, 1, 2, 2, 3, 1, 1, 3, 2, 3]
-attraction	2.0	0.7746	[2, 2, 1, 1, 2, 3, 3, 2, 3, 1]
-attractions	1.8	0.87178	[1, 3, 0, 2, 2, 2, 2, 3, 1, 2]
-attractive	1.9	0.53852	[2, 2, 2, 1, 3, 2, 1, 2, 2, 2]
-attractively	2.2	0.6	[3, 2, 2, 3, 2, 2, 2, 3, 1, 2]
-attractiveness	1.8	1.16619	[3, 2, 2, 1, 4, 2, 0, 0, 2, 2]
-attractivenesses	2.1	0.7	[2, 1, 2, 3, 2, 3, 3, 1, 2, 2]
-attractor	1.2	1.16619	[1, 1, 2, 2, 2, -2, 2, 1, 2, 1]
-attractors	1.2	0.87178	[1, 1, 2, 2, 0, 1, 3, 1, 0, 1]
-attracts	1.7	1.00499	[2, 1, 2, 0, 2, 4, 2, 1, 1, 2]
-audacious	0.9	2.02237	[3, -1, -2, 2, 1, 2, -3, 2, 2, 3]
-authority	0.3	0.64031	[0, 0, 0, 1, 0, 0, 2, 0, 0, 0]
-aversion	-1.9	1.04403	[-3, -3, -1, -2, 0, -3, -1, -2, -1, -3]
-aversions	-1.1	1.13578	[-2, -1, -2, -2, -2, 1, -1, -2, 1, -1]
-aversive	-1.6	0.66332	[-2, -1, -1, -1, -2, -2, -1, -2, -3, -1]
-aversively	-0.8	1.53623	[-3, -1, -2, -1, 1, -2, 2, -2, 1, -1]
-avert	-0.7	0.78102	[-1, 0, -2, -1, -1, 1, -1, 0, -1, -1]
-averted	-0.3	1.00499	[-1, 1, 0, 0, 1, 0, -2, 0, 0, -2]
-averts	-0.4	1.0198	[-2, -2, -1, -1, 0, 0, 1, 0, 1, 0]
-avid	1.2	0.87178	[-1, 2, 2, 1, 1, 1, 2, 2, 1, 1]
-avoid	-1.2	0.6	[-1, -1, -1, -1, -2, -2, -1, -2, 0, -1]
-avoidance	-1.7	0.45826	[-2, -2, -1, -1, -1, -2, -2, -2, -2, -2]
-avoidances	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -2, -1, -1]
-avoided	-1.4	0.4899	[-2, -1, -2, -1, -1, -1, -2, -1, -2, -1]
-avoider	-1.8	0.6	[-2, -1, -3, -1, -2, -2, -2, -1, -2, -2]
-avoiders	-1.4	0.66332	[-2, -2, -1, -2, -1, -1, 0, -1, -2, -2]
-avoiding	-1.4	0.91652	[-2, 1, -2, -2, -1, -2, -1, -1, -2, -2]
-avoids	-0.7	0.45826	[-1, -1, -1, -1, -1, -1, 0, 0, 0, -1]
-await	0.4	0.4899	[0, 0, 0, 1, 0, 1, 0, 1, 1, 0]
-awaited	-0.1	0.83066	[1, 0, 0, 0, 1, -1, 0, 0, -2, 0]
-awaits	0.3	0.78102	[0, 0, 0, 1, 2, 1, 0, 0, -1, 0]
-award	2.5	0.92195	[2, 1, 1, 3, 3, 2, 4, 3, 3, 3]
-awardable	2.4	0.8	[3, 3, 3, 1, 3, 1, 2, 3, 2, 3]
-awarded	1.7	0.78102	[2, 0, 1, 3, 2, 2, 2, 1, 2, 2]
-awardee	1.8	0.6	[2, 2, 1, 3, 2, 2, 1, 1, 2, 2]
-awardees	1.2	0.74833	[1, 1, 1, 1, 0, 1, 1, 1, 3, 2]
-awarder	0.9	1.04403	[2, 0, 1, 3, 0, 2, 1, 0, 0, 0]
-awarders	1.3	1.18743	[2, 1, 0, 2, 2, 0, 0, 4, 1, 1]
-awarding	1.9	0.7	[3, 2, 1, 2, 1, 2, 3, 1, 2, 2]
-awards	2.0	0.44721	[2, 2, 2, 2, 1, 2, 2, 3, 2, 2]
-awesome	3.1	0.83066	[3, 4, 2, 3, 2, 2, 4, 4, 4, 3]
-awful	-2.0	2.04939	[-2, -2, -3, -3, -2, -3, 4, -3, -3, -3]
-awkward	-0.6	1.56205	[-2, -1, -1, -1, -1, -1, -1, -1, 4, -1]
-awkwardly	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -1, -2, -2, -1]
-awkwardness	-0.7	1.41774	[-1, -2, -2, -1, -2, 2, -1, -1, 2, -1]
-axe	-0.4	0.8	[-2, 0, 0, 0, 0, 0, -1, -1, -1, 1]
-axed	-1.3	0.78102	[-1, -2, 0, -3, -1, -2, -1, -1, -1, -1]
-backed	0.1	0.3	[0, 0, 1, 0, 0, 0, 0, 0, 0, 0]
-backing	0.1	0.83066	[1, 1, -1, 0, 0, 0, -1, 1, -1, 1]
-backs	-0.2	0.4	[0, 0, -1, 0, 0, 0, 0, -1, 0, 0]
-bad	-2.5	0.67082	[-3, -2, -4, -3, -2, -2, -3, -2, -2, -2]
-badass	1.4	1.26491	[1, 3, 2, 0, -1, 1, 3, 2, 1, 2]
-badly	-2.1	0.7	[-2, -3, -2, -1, -3, -2, -3, -2, -1, -2]
-bailout	-0.4	1.35647	[-1, 0, 0, 2, -2, -1, -2, 2, -1, -1]
-bamboozle	-1.5	1.0247	[-3, -2, -2, -1, -2, -2, 1, -1, -1, -2]
-bamboozled	-1.5	1.11803	[-1, 0, -2, -4, -2, -1, -2, -1, 0, -2]
-bamboozles	-1.5	1.0247	[-1, 0, -2, -4, -2, -1, -2, -1, -1, -1]
-ban	-2.6	1.0198	[-4, -3, -4, -3, -2, -1, -3, -2, -1, -3]
-banish	-1.9	0.9434	[-2, -2, -2, -2, -1, -3, -1, -1, -1, -4]
-bankrupt	-2.6	1.0198	[-4, -4, -2, -2, -4, -3, -2, -2, -1, -2]
-bankster	-2.1	0.53852	[-3, -1, -2, -2, -2, -2, -2, -3, -2, -2]
-banned	-2.0	1.0	[-2, -1, -1, -1, -2, -2, -4, -3, -3, -1]
-bargain	0.8	1.16619	[1, 1, 1, 1, 0, 1, 2, 3, -1, -1]
-barrier	-0.5	0.92195	[-2, 0, 0, -2, -1, -1, 1, 0, 0, 0]
-bashful	-0.1	1.13578	[-1, 2, -1, 0, -1, 2, 0, 0, -1, -1]
-bashfully	0.2	0.9798	[0, 0, 0, -1, 1, 1, 1, 1, -2, 1]
-bashfulness	-0.8	0.9798	[-2, -1, 1, 1, -1, -2, -1, -1, -1, -1]
-bastard	-2.5	0.67082	[-2, -4, -2, -3, -2, -2, -3, -3, -2, -2]
-bastardies	-1.8	0.87178	[-2, -1, -3, -2, -2, -2, -1, 0, -2, -3]
-bastardise	-2.1	0.83066	[-2, -1, -4, -2, -2, -3, -2, -2, -2, -1]
-bastardised	-2.3	0.9	[-3, -2, -3, -1, -2, -3, -4, -1, -2, -2]
-bastardises	-2.3	1.18743	[-1, -4, -2, -3, -3, 0, -2, -4, -2, -2]
-bastardising	-2.6	0.8	[-3, -2, -3, -2, -2, -1, -3, -4, -3, -3]
-bastardization	-2.4	1.28062	[-1, -3, -4, -4, -2, -2, -2, 0, -2, -4]
-bastardizations	-2.1	0.7	[-2, -1, -3, -3, -2, -2, -3, -1, -2, -2]
-bastardize	-2.4	0.66332	[-2, -2, -3, -2, -2, -3, -4, -2, -2, -2]
-bastardized	-2.0	0.7746	[-2, -1, -1, -2, -3, -2, -3, -2, -1, -3]
-bastardizes	-1.8	0.87178	[-2, -1, -1, -2, -2, -2, -3, -3, 0, -2]
-bastardizing	-2.3	0.9	[-2, -2, -1, -4, -3, -2, -1, -2, -3, -3]
-bastardly	-2.7	0.64031	[-3, -3, -2, -2, -3, -2, -2, -4, -3, -3]
-bastards	-3.0	0.63246	[-4, -2, -3, -3, -4, -3, -3, -3, -3, -2]
-bastardy	-2.7	1.1	[-4, -3, -2, -2, -4, -3, -3, -3, -3, 0]
-battle	-1.6	1.28062	[-1, -3, 0, -3, -2, -3, -2, -2, 1, -1]
-battled	-1.2	0.87178	[0, 0, -2, 0, -2, -1, -2, -1, -2, -2]
-battlefield	-1.6	0.8	[-2, -2, 0, -1, -2, -1, -3, -2, -1, -2]
-battlefields	-0.9	1.22066	[-1, -1, 0, 0, -4, -1, 0, 0, 0, -2]
-battlefront	-1.2	0.87178	[-1, 0, -2, -1, 0, -3, -1, -2, -1, -1]
-battlefronts	-0.8	1.16619	[0, 0, -2, -1, 0, -3, -1, 1, -2, 0]
-battleground	-1.7	0.78102	[-2, 0, -2, -2, -1, -2, -2, -3, -1, -2]
-battlegrounds	-0.6	1.35647	[2, -2, 0, -1, 0, -2, -2, -2, 0, 1]
-battlement	-0.4	0.8	[0, -1, 0, -1, 0, -2, 0, 1, 0, -1]
-battlements	-0.4	0.66332	[0, 0, 0, 0, 0, -1, -2, 0, -1, 0]
-battler	-0.8	1.4	[2, 0, -2, 0, -2, 1, -2, -1, -2, -2]
-battlers	-0.2	0.9798	[-1, 0, 2, -2, 0, 0, 0, -1, 0, 0]
-battles	-1.6	0.4899	[-1, -1, -2, -1, -2, -2, -2, -1, -2, -2]
-battleship	-0.1	1.3	[2, -3, -1, -1, 0, 0, 1, 1, 0, 0]
-battleships	-0.5	0.80623	[-2, 0, 0, 0, 0, -1, -2, 0, 0, 0]
-battlewagon	-0.3	0.64031	[0, 0, -1, -2, 0, 0, 0, 0, 0, 0]
-battlewagons	-0.5	0.67082	[0, 0, 0, -1, -2, -1, 0, -1, 0, 0]
-battling	-1.1	1.04403	[0, -1, -2, -2, -1, 1, -2, 0, -2, -2]
-beaten	-1.8	0.6	[-1, -2, -2, -2, -3, -2, -2, -2, -1, -1]
-beatific	1.8	1.6	[3, 0, 2, 4, -2, 2, 2, 2, 2, 3]
-beating	-2.0	0.63246	[-2, -3, -2, -2, -1, -1, -2, -3, -2, -2]
-beaut	1.6	1.2	[2, 2, 2, 0, 1, -1, 2, 3, 3, 2]
-beauteous	2.5	1.0247	[2, 1, 4, 3, 3, 2, 1, 4, 2, 3]
-beauteously	2.6	0.8	[2, 3, 3, 3, 2, 1, 3, 4, 2, 3]
-beauteousness	2.7	1.00499	[1, 3, 4, 3, 4, 1, 2, 3, 3, 3]
-beautician	1.2	0.9798	[0, 0, 3, 2, 2, 0, 1, 1, 1, 2]
-beauticians	0.4	0.66332	[0, 1, 0, 0, 0, 0, 1, 0, 2, 0]
-beauties	2.4	0.8	[2, 3, 3, 3, 3, 1, 2, 1, 3, 3]
-beautification	1.9	0.7	[2, 2, 2, 1, 2, 1, 3, 1, 2, 3]
-beautifications	2.4	0.8	[3, 2, 3, 3, 1, 3, 2, 3, 1, 3]
-beautified	2.1	0.7	[2, 2, 3, 1, 2, 2, 3, 1, 2, 3]
-beautifier	1.7	0.64031	[2, 1, 2, 1, 2, 1, 3, 1, 2, 2]
-beautifiers	1.7	0.78102	[3, 3, 1, 2, 1, 2, 2, 1, 1, 1]
-beautifies	1.8	0.74833	[2, 1, 2, 1, 2, 1, 3, 1, 2, 3]
-beautiful	2.9	0.7	[2, 3, 2, 3, 2, 3, 4, 4, 3, 3]
-beautifuler	2.1	0.83066	[2, 0, 2, 2, 3, 2, 2, 2, 3, 3]
-beautifulest	2.6	0.8	[3, 3, 3, 3, 2, 2, 4, 2, 1, 3]
-beautifully	2.7	0.64031	[3, 3, 2, 2, 3, 3, 2, 2, 4, 3]
-beautifulness	2.6	0.8	[3, 3, 3, 2, 3, 4, 3, 2, 2, 1]
-beautify	2.3	0.45826	[2, 3, 3, 2, 2, 3, 2, 2, 2, 2]
-beautifying	2.3	0.78102	[1, 2, 1, 3, 2, 2, 3, 3, 3, 3]
-beauts	1.7	0.78102	[1, 2, 0, 3, 1, 2, 2, 2, 2, 2]
-beauty	2.8	0.74833	[3, 3, 2, 3, 4, 4, 2, 2, 3, 2]
-belittle	-1.9	0.53852	[-2, -2, -2, -1, -2, -2, -1, -2, -3, -2]
-belittled	-2.0	1.0	[-3, -2, -3, -3, -2, -3, -1, -1, -2, 0]
-beloved	2.3	0.45826	[2, 2, 3, 2, 2, 2, 2, 3, 3, 2]
-benefic	1.4	0.4899	[2, 2, 1, 1, 1, 2, 2, 1, 1, 1]
-benefice	0.4	0.66332	[0, 2, 0, 1, 0, 0, 1, 0, 0, 0]
-beneficed	1.1	0.7	[1, 1, 1, 0, 2, 0, 1, 1, 2, 2]
-beneficence	2.8	0.87178	[1, 4, 3, 4, 2, 2, 3, 3, 3, 3]
-beneficences	1.5	0.67082	[1, 1, 2, 2, 1, 1, 1, 3, 2, 1]
-beneficent	2.3	0.45826	[3, 2, 3, 2, 2, 2, 2, 3, 2, 2]
-beneficently	2.2	0.6	[3, 2, 3, 3, 2, 2, 1, 2, 2, 2]
-benefices	1.1	0.83066	[1, 1, 1, 0, 1, 0, 1, 1, 2, 3]
-beneficial	1.9	0.53852	[2, 2, 1, 2, 2, 1, 3, 2, 2, 2]
-beneficially	2.4	0.8	[3, 3, 2, 2, 2, 1, 3, 4, 2, 2]
-beneficialness	1.7	0.64031	[2, 1, 2, 2, 1, 1, 2, 2, 1, 3]
-beneficiaries	1.8	1.16619	[0, 1, 2, 1, 3, 4, 3, 1, 2, 1]
-beneficiary	2.1	0.83066	[1, 3, 2, 2, 2, 1, 3, 3, 1, 3]
-beneficiate	1.0	1.18322	[0, 0, 1, 3, 1, 0, 2, 0, 3, 0]
-beneficiation	0.4	1.0198	[2, 2, 0, -1, 1, 0, -1, 0, 0, 1]
-benefit	2.0	0.63246	[2, 3, 1, 2, 2, 3, 2, 1, 2, 2]
-benefits	1.6	0.4899	[2, 2, 2, 1, 2, 1, 2, 2, 1, 1]
-benefitted	1.7	0.64031	[2, 2, 1, 2, 2, 2, 2, 2, 0, 2]
-benefitting	1.9	0.7	[1, 2, 2, 3, 1, 1, 2, 3, 2, 2]
-benevolence	1.7	1.1	[2, 1, 3, 2, 2, 1, 2, 2, -1, 3]
-benevolences	1.9	1.64012	[3, 2, -1, -1, 3, 1, 3, 4, 2, 3]
-benevolent	2.7	0.78102	[2, 2, 3, 2, 4, 2, 3, 2, 4, 3]
-benevolently	1.4	1.11355	[2, 1, 2, 2, 1, -1, 2, 3, 0, 2]
-benevolentness	1.2	1.249	[2, 2, 1, -1, 2, 2, 3, -1, 1, 1]
-benign	1.3	0.9	[1, 3, 2, 2, 1, 1, 2, 0, 0, 1]
-benignancy	0.6	1.2	[2, -1, -2, 1, 0, 1, 1, 2, 1, 1]
-benignant	2.2	0.9798	[2, 2, 2, 2, 2, 2, 4, 0, 3, 3]
-benignantly	1.1	1.3	[3, 2, 3, 0, 1, 1, -1, 2, 0, 0]
-benignities	0.9	0.9434	[-1, 2, 1, 0, 1, 1, 2, 2, 1, 0]
-benignity	1.3	1.18743	[2, -2, 2, 2, 2, 1, 2, 1, 1, 2]
-benignly	0.2	1.07703	[0, -1, 1, 1, 1, 0, 2, 0, -2, 0]
-bereave	-2.1	1.13578	[0, -2, -2, -3, -3, -4, -3, -2, -1, -1]
-bereaved	-2.1	0.9434	[-2, -2, -2, -1, -2, -1, -4, -1, -3, -3]
-bereaves	-1.9	1.22066	[0, -3, 0, -1, -3, -2, -3, -1, -3, -3]
-bereaving	-1.3	1.84662	[-3, -4, -3, 1, -2, 0, -3, -1, 1, 1]
-best	3.2	0.6	[2, 4, 4, 3, 4, 3, 3, 3, 3, 3]
-betray	-3.2	0.6	[-3, -4, -4, -3, -2, -3, -4, -3, -3, -3]
-betrayal	-2.8	0.74833	[-3, -4, -4, -2, -3, -2, -3, -3, -2, -2]
-betrayed	-3.0	0.63246	[-2, -3, -3, -3, -4, -4, -3, -3, -2, -3]
-betraying	-2.5	0.67082	[-2, -2, -3, -2, -3, -2, -4, -2, -2, -3]
-betrays	-2.5	0.67082	[-2, -3, -3, -2, -2, -2, -4, -2, -3, -2]
-better	1.9	0.7	[2, 1, 2, 1, 1, 3, 2, 2, 3, 2]
-bias	-0.4	1.11355	[-1, -2, 0, -2, -1, 1, -1, 1, 0, 1]
-biased	-1.1	0.83066	[-2, -2, -1, -1, -1, -1, -1, 1, -2, -1]
-bitch	-2.8	0.87178	[-1, -4, -2, -4, -3, -2, -3, -3, -3, -3]
-bitched	-2.6	1.0198	[-1, -3, -2, -3, -2, -1, -4, -3, -3, -4]
-bitcheries	-2.3	0.78102	[-2, -2, -2, -4, -2, -2, -3, -1, -3, -2]
-bitchery	-2.7	1.18743	[-2, -2, -4, -2, -4, -4, -1, -1, -3, -4]
-bitches	-2.9	0.9434	[-2, -1, -3, -3, -2, -4, -4, -3, -3, -4]
-bitchier	-2.0	0.63246	[-2, -3, -1, -2, -3, -1, -2, -2, -2, -2]
-bitchiest	-3.0	0.7746	[-2, -4, -2, -3, -4, -3, -3, -4, -2, -3]
-bitchily	-2.6	1.11355	[-4, -4, -2, -2, -1, -4, -1, -2, -3, -3]
-bitchiness	-2.6	0.66332	[-3, -3, -2, -2, -3, -3, -1, -3, -3, -3]
-bitching	-1.1	1.64012	[-2, 2, -2, -1, 2, -1, -2, -2, -3, -2]
-bitchy	-2.3	1.00499	[-4, -1, -2, -3, -3, -2, -1, -1, -3, -3]
-bitter	-1.8	0.4	[-2, -2, -2, -1, -2, -2, -1, -2, -2, -2]
-bitterbrush	-0.2	0.74833	[0, 0, 0, 0, -2, 1, 0, 0, -1, 0]
-bitterbrushes	-0.6	0.8	[-1, 0, -2, -1, -2, 0, 0, 0, 0, 0]
-bittered	-1.8	1.07703	[-1, -1, -3, -1, -2, -4, -2, 0, -2, -2]
-bitterer	-1.9	1.04403	[-1, -2, -3, -1, -1, -4, -3, -1, -2, -1]
-bitterest	-2.3	1.41774	[-4, -4, -2, -1, 1, -2, -3, -3, -2, -3]
-bittering	-1.2	0.87178	[0, 0, -1, -2, 0, -2, -1, -2, -2, -2]
-bitterish	-1.6	0.8	[0, -2, -1, -1, -2, -2, -2, -1, -3, -2]
-bitterly	-2.0	0.63246	[-2, -2, -1, -1, -2, -2, -3, -2, -2, -3]
-bittern	-0.2	0.6	[0, 0, -2, 0, 0, 0, 0, 0, 0, 0]
-bitterness	-1.7	0.45826	[-2, -2, -1, -2, -1, -2, -1, -2, -2, -2]
-bitterns	-0.4	1.11355	[0, 0, 0, -3, 0, 0, 0, 1, 0, -2]
-bitterroots	-0.2	0.4	[0, 0, 0, -1, -1, 0, 0, 0, 0, 0]
-bitters	-0.4	0.4899	[-1, -1, -1, 0, 0, 0, 0, -1, 0, 0]
-bittersweet	-0.3	0.64031	[0, -1, 0, 0, 0, 0, 0, 0, -2, 0]
-bittersweetness	-0.6	0.91652	[0, 0, 0, -2, 0, -2, 0, 0, -2, 0]
-bittersweets	-0.2	0.9798	[-2, 1, 0, 0, 0, -2, 0, 0, 0, 1]
-bitterweeds	-0.5	0.67082	[0, -2, 0, -1, -1, 0, 0, -1, 0, 0]
-bizarre	-1.3	1.00499	[-2, 0, 0, -2, 0, -1, -3, -2, -1, -2]
-blah	-0.4	1.49666	[-2, -1, -1, -1, -1, -1, -1, 3, 2, -1]
-blam	-0.2	1.16619	[-1, 0, 0, -1, -1, -2, -1, 1, 2, 1]
-blamable	-1.8	0.4	[-2, -2, -2, -2, -1, -1, -2, -2, -2, -2]
-blamably	-1.8	0.4	[-2, -2, -2, -2, -1, -1, -2, -2, -2, -2]
-blame	-1.4	1.42829	[-4, -2, -2, -1, -1, -1, -2, 2, -2, -1]
-blamed	-2.1	0.53852	[-2, -2, -2, -2, -3, -2, -2, -2, -3, -1]
-blameful	-1.7	0.45826	[-2, -2, -2, -2, -2, -2, -1, -1, -2, -1]
-blamefully	-1.6	0.66332	[-1, -2, -1, -1, -2, -1, -1, -2, -2, -3]
-blameless	0.7	1.73494	[3, 1, 2, 3, -2, 1, -1, 1, 1, -2]
-blamelessly	0.9	1.37477	[2, 0, 2, 0, 1, -1, 1, 4, 0, 0]
-blamelessness	0.6	1.35647	[0, 2, 1, 2, 1, 0, 1, -3, 1, 1]
-blamer	-2.1	0.83066	[-2, -2, -1, -2, -3, -3, -3, -1, -1, -3]
-blamers	-2.0	0.63246	[-3, -2, -2, -3, -1, -2, -2, -1, -2, -2]
-blames	-1.7	0.45826	[-2, -2, -1, -2, -2, -2, -2, -1, -1, -2]
-blameworthiness	-1.6	0.66332	[-2, -2, -1, -2, -2, -1, -3, -1, -1, -1]
-blameworthy	-2.3	0.78102	[-3, -3, -2, -2, -2, -1, -1, -3, -3, -3]
-blaming	-2.2	0.6	[-2, -3, -1, -3, -2, -2, -3, -2, -2, -2]
-bless	1.8	0.6	[3, 2, 2, 1, 2, 2, 1, 2, 2, 1]
-blessed	2.9	0.3	[2, 3, 3, 3, 3, 3, 3, 3, 3, 3]
-blesseder	2.0	0.63246	[3, 3, 2, 2, 1, 1, 2, 2, 2, 2]
-blessedest	2.8	0.87178	[2, 4, 1, 4, 3, 3, 2, 3, 3, 3]
-blessedly	1.7	1.1	[2, 2, 1, -1, 3, 2, 3, 1, 2, 2]
-blessedness	1.6	1.35647	[2, 2, 2, 2, 2, 3, 3, -1, -1, 2]
-blesser	2.6	0.66332	[1, 3, 2, 3, 3, 3, 2, 3, 3, 3]
-blessers	1.9	0.7	[2, 2, 1, 2, 2, 2, 3, 1, 3, 1]
-blesses	2.6	0.66332	[1, 3, 3, 3, 3, 3, 2, 3, 2, 3]
-blessing	2.2	1.07703	[3, 1, 0, 3, 1, 3, 2, 3, 3, 3]
-blessings	2.5	0.92195	[3, 3, 3, 2, 1, 3, 2, 3, 4, 1]
-blind	-1.7	1.00499	[-4, -1, -1, -2, -1, -1, -3, -2, -1, -1]
-bliss	2.7	0.78102	[3, 3, 3, 2, 1, 2, 4, 3, 3, 3]
-blissful	2.9	0.83066	[4, 4, 2, 3, 3, 3, 1, 3, 3, 3]
-blithe	1.2	1.16619	[2, 2, -1, 1, 1, 2, 2, 2, -1, 2]
-block	-1.9	1.13578	[-3, -2, -1, -2, 0, 0, -3, -2, -3, -3]
-blockbuster	2.9	0.9434	[3, 4, 3, 2, 3, 4, 3, 2, 1, 4]
-blocked	-1.1	1.13578	[-1, 0, 0, -1, -2, -1, -1, -4, -1, 0]
-blocking	-1.6	0.91652	[-1, -1, -1, -1, -2, -2, -4, -1, -2, -1]
-blocks	-0.9	1.13578	[-1, 0, -1, -2, -2, -2, -1, -1, 2, -1]
-bloody	-1.9	0.7	[-2, -2, -2, 0, -2, -2, -3, -2, -2, -2]
-blurry	-0.4	1.28062	[-1, -1, -1, -1, 2, -2, -1, 2, 0, -1]
-bold	1.6	0.66332	[2, 2, 2, 2, 1, 2, 0, 2, 1, 2]
-bolder	1.2	0.6	[2, 1, 1, 1, 1, 2, 1, 2, 0, 1]
-boldest	1.6	1.11355	[1, 3, 2, 3, 0, 0, 2, 3, 1, 1]
-boldface	0.3	0.64031	[1, 0, 0, 0, 0, 0, 0, 2, 0, 0]
-boldfaced	-0.1	1.22066	[0, 0, 0, 2, -1, -2, 2, -1, -1, 0]
-boldfaces	0.1	1.3	[0, 0, 0, 2, -2, -2, 2, 1, 0, 0]
-boldfacing	0.1	0.7	[0, 0, -1, 2, 0, 0, 0, 0, 0, 0]
-boldly	1.5	1.62788	[3, -2, -1, 1, 2, 3, 2, 3, 2, 2]
-boldness	1.5	1.0247	[0, 1, 3, 1, 2, 0, 3, 1, 2, 2]
-boldnesses	0.9	0.83066	[0, 0, 1, 0, 2, 1, 1, 2, 0, 2]
-bolds	1.3	0.78102	[2, 2, 1, 1, 0, 2, 0, 2, 1, 2]
-bomb	-2.2	0.87178	[-2, -2, -1, -3, -4, -3, -2, -1, -2, -2]
-bonus	2.5	0.67082	[2, 2, 2, 3, 4, 3, 2, 2, 3, 2]
-bonuses	2.6	0.91652	[2, 2, 3, 4, 3, 4, 3, 1, 2, 2]
-boost	1.7	0.64031	[1, 1, 2, 2, 2, 3, 1, 1, 2, 2]
-boosted	1.5	1.5	[-1, 1, 0, 2, 1, 2, 3, 3, 4, 0]
-boosting	1.4	0.91652	[1, 1, 3, 0, 2, 2, 0, 2, 1, 2]
-boosts	1.3	0.9	[1, 1, 1, 1, 3, 0, 1, 1, 3, 1]
-bore	-1.0	0.44721	[-1, -2, 0, -1, -1, -1, -1, -1, -1, -1]
-boreal	-0.3	0.9	[0, 0, 0, 0, 1, -2, 0, 0, -2, 0]
-borecole	-0.2	0.74833	[1, 0, 0, 0, -1, -2, 0, 0, 0, 0]
-borecoles	-0.3	0.45826	[-1, 0, 0, 0, 0, 0, -1, 0, -1, 0]
-bored	-1.1	0.9434	[-2, -1, -2, -1, 0, 0, -3, 0, -1, -1]
-boredom	-1.3	0.45826	[-1, -1, -1, -1, -2, -1, -1, -2, -2, -1]
-boredoms	-1.1	0.83066	[-1, -1, -1, -2, 1, -1, -2, -1, -1, -2]
-boreen	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
-boreens	0.2	0.6	[0, 0, 0, 2, 0, 0, 0, 0, 0, 0]
-boreholes	-0.2	0.74833	[0, 0, 0, 0, 0, 1, -1, 0, -2, 0]
-borer	-0.4	0.4899	[0, -1, 0, 0, -1, -1, 0, 0, 0, -1]
-borers	-1.2	0.9798	[-1, 0, -2, -1, -1, -3, -2, 0, -2, 0]
-bores	-1.3	0.78102	[-2, -1, -2, -1, -1, -1, -3, 0, -1, -1]
-borescopes	-0.1	0.83066	[-1, 0, -1, 2, 0, 0, 0, 0, -1, 0]
-boresome	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -1, -2, -1]
-boring	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -1, -1, -2, -2]
-bother	-1.4	0.91652	[-1, -1, -1, -2, -3, -3, -1, -1, -1, 0]
-botheration	-1.7	0.64031	[-1, -1, -1, -2, -2, -1, -2, -2, -2, -3]
-botherations	-1.3	0.64031	[-2, -2, -2, -1, -2, 0, -1, -1, -1, -1]
-bothered	-1.3	0.45826	[-1, -1, -2, -1, -2, -1, -1, -1, -1, -2]
-bothering	-1.6	0.4899	[-2, -1, -2, -2, -1, -1, -1, -2, -2, -2]
-bothers	-0.8	0.9798	[-1, -2, -1, -1, 2, -1, -1, -1, -1, -1]
-bothersome	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -2, -1, -1]
-boycott	-1.3	0.45826	[-2, -1, -1, -1, -1, -2, -1, -1, -2, -1]
-boycotted	-1.7	0.64031	[-1, -2, -2, -3, -1, -1, -2, -2, -2, -1]
-boycotting	-1.7	0.64031	[-2, -2, -2, 0, -2, -1, -2, -2, -2, -2]
-boycotts	-1.4	0.91652	[-2, -2, -2, -2, -1, -2, -1, 1, -1, -2]
-brainwashing	-1.5	1.28452	[-2, -2, -2, -3, -1, -2, 2, -1, -2, -2]
-brave	2.4	0.8	[2, 3, 4, 3, 1, 3, 2, 2, 2, 2]
-braved	1.9	0.83066	[3, 1, 3, 1, 1, 2, 3, 2, 2, 1]
-bravely	2.3	0.78102	[1, 3, 2, 2, 2, 4, 2, 2, 2, 3]
-braver	2.4	0.8	[3, 2, 2, 1, 4, 2, 3, 3, 2, 2]
-braveries	2.0	1.0	[2, 4, 2, 3, 1, 1, 2, 3, 1, 1]
-bravery	2.2	0.74833	[1, 2, 2, 2, 3, 2, 3, 3, 1, 3]
-braves	1.9	0.83066	[3, 1, 3, 1, 2, 2, 3, 2, 1, 1]
-bravest	2.3	0.64031	[1, 3, 3, 2, 3, 2, 3, 2, 2, 2]
-breathtaking	2.0	1.26491	[3, 1, 3, 2, -1, 1, 2, 3, 3, 3]
-bribe	-0.8	1.98997	[-3, 0, -1, -2, -1, -2, -4, 1, 3, 1]
-bright	1.9	0.7	[2, 2, 1, 2, 1, 2, 1, 3, 3, 2]
-brighten	1.9	0.7	[2, 1, 1, 2, 3, 2, 1, 2, 2, 3]
-brightened	2.1	0.83066	[2, 3, 1, 1, 2, 2, 3, 1, 3, 3]
-brightener	1.0	1.18322	[0, 0, 0, 1, 0, 1, 2, 0, 3, 3]
-brighteners	1.0	0.89443	[0, 1, 0, 1, 1, 3, 0, 1, 2, 1]
-brightening	2.5	0.92195	[2, 3, 2, 1, 2, 3, 4, 4, 2, 2]
-brightens	1.5	0.5	[2, 1, 1, 2, 2, 1, 2, 2, 1, 1]
-brighter	1.6	0.66332	[1, 1, 1, 2, 2, 2, 1, 2, 1, 3]
-brightest	3.0	0.63246	[3, 3, 2, 3, 4, 3, 2, 3, 4, 3]
-brightly	1.5	0.67082	[2, 3, 1, 2, 1, 1, 2, 1, 1, 1]
-brightness	1.6	0.91652	[2, 2, 1, 1, 1, 3, 3, 0, 2, 1]
-brightnesses	1.4	0.91652	[2, 3, 1, 2, 1, 1, 0, 0, 2, 2]
-brights	0.4	0.66332	[0, 0, 2, 0, 0, 1, 0, 0, 1, 0]
-brightwork	1.1	0.83066	[1, 0, 1, 2, 1, 0, 3, 1, 1, 1]
-brilliance	2.9	0.83066	[4, 3, 2, 4, 4, 3, 2, 3, 2, 2]
-brilliances	2.9	0.83066	[3, 4, 3, 4, 4, 2, 3, 2, 2, 2]
-brilliancies	2.3	1.18743	[1, 4, 1, 3, 3, 2, 1, 3, 4, 1]
-brilliancy	2.6	1.0198	[4, 3, 2, 4, 2, 3, 1, 3, 1, 3]
-brilliant	2.8	0.6	[2, 3, 3, 2, 3, 3, 4, 2, 3, 3]
-brilliantine	0.8	1.16619	[-1, 3, 1, 0, 1, 0, 2, 0, 2, 0]
-brilliantines	2.0	1.34164	[0, 1, 4, 2, 3, 1, 3, 0, 3, 3]
-brilliantly	3.0	0.44721	[3, 2, 3, 3, 3, 3, 3, 3, 4, 3]
-brilliants	1.9	0.83066	[3, 1, 2, 1, 2, 1, 3, 2, 1, 3]
-brisk	0.6	0.8	[0, 0, 0, 0, 1, 1, 0, 2, 0, 2]
-broke	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -1, -2, -2]
-broken	-2.1	0.53852	[-2, -2, -2, -2, -3, -2, -1, -3, -2, -2]
-brooding	0.1	1.3	[3, 0, -1, -1, -1, 1, 1, -1, 1, -1]
-brutal	-3.1	0.7	[-3, -3, -4, -2, -3, -4, -3, -4, -3, -2]
-brutalise	-2.7	1.1	[-4, -3, -3, -4, -3, -2, -2, -3, 0, -3]
-brutalised	-2.9	0.83066	[-3, -3, -2, -3, -3, -4, -4, -1, -3, -3]
-brutalises	-3.2	0.4	[-3, -3, -3, -3, -3, -4, -4, -3, -3, -3]
-brutalising	-2.8	0.74833	[-3, -3, -4, -3, -2, -3, -3, -3, -1, -3]
-brutalities	-2.6	1.0198	[-4, -2, -2, -4, -2, -4, -2, -3, -1, -2]
-brutality	-3.0	0.63246	[-2, -3, -4, -2, -3, -3, -3, -4, -3, -3]
-brutalization	-2.1	2.16564	[-3, -2, -4, -2, -4, -4, 2, -3, 2, -3]
-brutalizations	-2.3	0.64031	[-2, -2, -3, -2, -1, -3, -3, -2, -2, -3]
-brutalize	-2.9	0.7	[-3, -4, -3, -3, -2, -2, -3, -4, -2, -3]
-brutalized	-2.4	0.4899	[-3, -2, -2, -3, -2, -2, -3, -3, -2, -2]
-brutalizes	-3.2	0.6	[-4, -4, -3, -2, -3, -4, -3, -3, -3, -3]
-brutalizing	-3.4	0.66332	[-4, -3, -4, -3, -4, -4, -3, -4, -2, -3]
-brutally	-3.0	0.44721	[-3, -3, -3, -3, -3, -3, -3, -2, -3, -4]
-bullied	-3.1	0.9434	[-4, -4, -4, -2, -2, -4, -4, -3, -2, -2]
-bullshit	-2.8	0.6	[-3, -3, -3, -3, -3, -4, -2, -3, -2, -2]
-bully	-2.2	1.6	[-2, -3, -3, -4, -2, -1, 2, -3, -3, -3]
-bullying	-2.9	0.7	[-3, -2, -3, -2, -4, -2, -3, -3, -4, -3]
-bummer	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -1, -2, -2, -1]
-buoyant	0.9	0.83066	[0, 1, 1, 2, 1, 0, 0, 2, 0, 2]
-burden	-1.9	0.53852	[-2, -2, -1, -2, -3, -2, -1, -2, -2, -2]
-burdened	-1.7	0.45826	[-2, -2, -2, -2, -1, -2, -1, -2, -2, -1]
-burdener	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -2, -1, -2, -1]
-burdeners	-1.7	1.00499	[-2, -2, -2, -1, -3, -2, 0, 0, -2, -3]
-burdening	-1.4	0.66332	[-2, -1, -2, -2, -1, -1, -1, 0, -2, -2]
-burdens	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -1, -2, -2]
-burdensome	-1.8	0.9798	[-1, -1, -3, -2, -1, -2, -2, -1, -4, -1]
-bwahaha	0.4	1.0198	[0, 1, 0, 1, 0, 2, -1, -1, 2, 0]
-bwahahah	2.5	0.92195	[3, 4, 2, 2, 2, 3, 1, 2, 2, 4]
-calm	1.3	0.78102	[1, 1, 0, 1, 2, 3, 2, 1, 1, 1]
-calmative	1.1	0.9434	[3, 2, -1, 1, 1, 1, 1, 1, 1, 1]
-calmatives	0.5	0.80623	[-1, 1, 0, 1, 0, 0, 1, 2, 0, 1]
-calmed	1.6	0.4899	[2, 2, 2, 1, 1, 1, 2, 1, 2, 2]
-calmer	1.5	0.67082	[1, 2, 3, 1, 1, 1, 2, 1, 2, 1]
-calmest	1.6	0.8	[3, 2, 2, 2, 1, 1, 0, 2, 1, 2]
-calming	1.7	0.78102	[2, 1, 3, 2, 2, 1, 3, 1, 1, 1]
-calmly	1.3	0.9	[0, 0, 1, 3, 2, 2, 1, 1, 2, 1]
-calmness	1.7	0.9	[1, 1, 1, 2, 2, 2, 1, 4, 1, 2]
-calmnesses	1.6	0.4899	[1, 2, 1, 2, 1, 2, 2, 2, 1, 2]
-calmodulin	0.2	0.4	[0, 0, 0, 0, 0, 0, 1, 0, 0, 1]
-calms	1.3	0.64031	[2, 1, 1, 2, 0, 1, 1, 2, 2, 1]
-can't stand	-2.0	0.63246	[-2, -2, -2, -1, -1, -2, -3, -2, -2, -3]
-cancel	-1.0	0.63246	[-2, -1, -1, -1, -1, 0, -1, 0, -2, -1]
-cancelled	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -2, -1, -1]
-cancelling	-0.8	0.74833	[0, 0, -1, 0, -1, -1, 0, -2, -1, -2]
-cancels	-0.9	0.53852	[0, -1, 0, -1, -1, -1, -1, -1, -2, -1]
-cancer	-3.4	0.8	[-2, -4, -3, -4, -4, -2, -3, -4, -4, -4]
-capable	1.6	0.4899	[1, 2, 2, 2, 1, 1, 2, 2, 1, 2]
-captivated	1.6	0.4899	[2, 1, 2, 2, 2, 2, 1, 2, 1, 1]
-care	2.2	0.74833	[2, 1, 2, 1, 2, 2, 3, 3, 3, 3]
-cared	1.8	0.74833	[1, 2, 1, 3, 1, 2, 2, 2, 3, 1]
-carefree	1.7	0.64031	[1, 1, 2, 2, 2, 2, 1, 1, 2, 3]
-careful	0.6	1.11355	[3, 0, 0, 0, 1, 0, -1, 2, 1, 0]
-carefully	0.5	0.67082	[1, 0, 1, 1, 0, 1, 0, 1, 1, -1]
-carefulness	2.0	0.44721	[3, 2, 2, 1, 2, 2, 2, 2, 2, 2]
-careless	-1.5	0.5	[-2, -1, -1, -2, -2, -1, -2, -2, -1, -1]
-carelessly	-1.0	0.44721	[-1, -1, -1, -2, -1, 0, -1, -1, -1, -1]
-carelessness	-1.4	0.4899	[-2, -1, -1, -2, -1, -2, -1, -1, -2, -1]
-carelessnesses	-1.6	1.11355	[-4, -2, -2, -3, -1, 0, -1, -1, -1, -1]
-cares	2.0	0.7746	[2, 3, 1, 3, 1, 2, 2, 2, 3, 1]
-caring	2.2	0.4	[2, 3, 2, 2, 2, 2, 2, 3, 2, 2]
-casual	0.8	0.74833	[1, 1, 0, 1, 0, 2, 0, 1, 2, 0]
-casually	0.7	1.00499	[1, 0, 0, 0, 1, 0, 0, 3, 2, 0]
-casualty	-2.4	0.91652	[-4, -3, -3, -2, -1, -2, -3, -1, -2, -3]
-catastrophe	-3.4	0.4899	[-3, -3, -3, -4, -4, -3, -3, -3, -4, -4]
-catastrophic	-2.2	2.22711	[-3, -2, -4, -4, -4, -3, -2, -4, 2, 2]
-cautious	-0.4	0.66332	[0, 1, -1, 0, 0, 0, -1, -1, -1, -1]
-celebrate	2.7	1.00499	[4, 4, 3, 2, 4, 2, 2, 2, 3, 1]
-celebrated	2.7	0.78102	[2, 3, 3, 2, 3, 4, 3, 3, 1, 3]
-celebrates	2.7	0.64031	[2, 3, 3, 2, 2, 3, 3, 3, 4, 2]
-celebrating	2.7	0.64031	[3, 3, 4, 2, 2, 2, 3, 3, 2, 3]
-censor	-2.0	1.34164	[0, -3, -2, -3, -3, 0, -4, -1, -1, -3]
-censored	-0.6	1.68523	[-1, -1, -1, 2, -3, -2, -1, -1, -1, 3]
-censors	-1.2	1.07703	[-1, 0, -3, 0, -1, 0, -1, -2, -1, -3]
-certain	1.1	0.7	[1, 0, 2, 0, 2, 2, 1, 1, 1, 1]
-certainly	1.4	1.0198	[3, 2, 0, 1, 3, 1, 0, 1, 1, 2]
-certainties	0.9	1.44568	[0, -2, 4, 0, 1, 1, 1, 1, 2, 1]
-certainty	1.0	0.89443	[2, 1, 0, 1, 0, 0, 2, 2, 2, 0]
-chagrin	-1.9	0.53852	[-1, -2, -3, -2, -1, -2, -2, -2, -2, -2]
-chagrined	-1.4	1.2	[-1, -2, 2, -1, -2, -2, -2, -2, -2, -2]
-challenge	0.3	1.00499	[1, 0, -1, 1, 1, -1, 1, 0, 2, -1]
-challenged	-0.4	1.62481	[0, -2, 1, -1, -3, -1, 3, -1, 1, -1]
-challenger	0.5	1.43178	[0, 0, 2, -1, -2, 1, 3, 0, 2, 0]
-challengers	0.4	1.56205	[0, -2, -1, 1, 1, 2, 3, 2, -1, -1]
-challenges	0.3	1.48661	[0, -1, 2, -1, -2, 0, 3, 0, 2, 0]
-challenging	0.6	0.91652	[0, 0, 0, 1, 1, -1, 0, 2, 2, 1]
-challengingly	-0.6	1.68523	[0, -1, -2, 1, -3, 2, -2, -1, 2, -2]
-champ	2.1	0.83066	[2, 2, 2, 3, 2, 3, 2, 0, 3, 2]
-champac	-0.2	0.6	[0, 0, -2, 0, 0, 0, 0, 0, 0, 0]
-champagne	1.2	1.07703	[1, 2, 2, 3, 0, 2, 0, 0, 2, 0]
-champagnes	0.5	0.92195	[0, 0, 0, 0, 0, 1, 1, 3, 0, 0]
-champaign	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
-champaigns	0.5	0.67082	[1, 0, 0, 0, 0, 0, 0, 1, 2, 1]
-champaks	-0.2	0.6	[0, 0, 0, 0, 0, 0, -2, 0, 0, 0]
-champed	1.0	0.63246	[1, 1, 2, 1, 1, 2, 1, 0, 0, 1]
-champer	-0.1	0.53852	[0, -1, 1, 0, 0, 0, 0, -1, 0, 0]
-champers	0.5	0.67082	[1, 0, 0, 0, 0, 0, 0, 1, 1, 2]
-champerties	-0.1	0.83066	[0, -1, 1, 1, 0, 0, 0, 0, -2, 0]
-champertous	0.3	0.78102	[0, 0, 0, 1, -1, 2, 1, 0, 0, 0]
-champerty	-0.2	1.32665	[-2, -1, 0, -1, 0, 0, 0, -2, 2, 2]
-champignon	0.4	0.8	[0, 0, 0, 0, 0, 2, 0, 2, 0, 0]
-champignons	0.2	0.6	[0, 2, 0, 0, 0, 0, 0, 0, 0, 0]
-champing	0.7	1.34536	[0, 2, 0, 3, 1, 1, 2, 0, -2, 0]
-champion	2.9	0.83066	[3, 2, 3, 4, 4, 3, 2, 2, 4, 2]
-championed	1.2	1.53623	[2, 1, 3, 1, 1, -3, 2, 2, 1, 2]
-championing	1.8	0.9798	[1, 3, 2, 0, 3, 1, 2, 2, 1, 3]
-champions	2.4	1.42829	[4, 0, 0, 3, 1, 3, 4, 3, 3, 3]
-championship	1.9	1.04403	[3, 1, 1, 3, 2, 1, 3, 3, 0, 2]
-championships	2.2	0.74833	[2, 2, 1, 2, 3, 2, 4, 2, 2, 2]
-champs	1.8	0.4	[2, 2, 2, 2, 1, 2, 1, 2, 2, 2]
-champy	1.0	1.0	[3, 0, 0, 0, 0, 2, 1, 2, 1, 1]
-chance	1.0	0.7746	[1, 1, 0, 0, 0, 2, 1, 2, 1, 2]
-chances	0.8	0.4	[0, 1, 1, 0, 1, 1, 1, 1, 1, 1]
-chaos	-2.7	0.9	[-2, -2, -3, -1, -4, -3, -3, -2, -3, -4]
-chaotic	-2.2	1.4	[-3, -2, -1, -2, -3, 1, -2, -2, -4, -4]
-charged	-0.8	0.87178	[-1, -2, -2, -1, -1, 0, -1, 1, 0, -1]
-charges	-1.1	0.7	[-2, -2, -2, -1, -1, 0, -1, -1, 0, -1]
-charitable	1.7	0.64031	[1, 2, 1, 2, 2, 1, 2, 1, 3, 2]
-charitableness	1.9	0.9434	[3, 1, 1, 3, 1, 3, 3, 2, 1, 1]
-charitablenesses	1.6	1.74356	[2, 2, 3, 4, 1, -1, -2, 3, 2, 2]
-charitably	1.4	0.66332	[1, 2, 1, 2, 2, 1, 0, 1, 2, 2]
-charities	2.2	0.6	[3, 3, 2, 2, 1, 2, 2, 3, 2, 2]
-charity	1.8	0.87178	[1, 3, 2, 2, 2, 1, 2, 0, 2, 3]
-charm	1.7	0.78102	[3, 1, 1, 3, 2, 2, 1, 1, 1, 2]
-charmed	2.0	0.63246	[3, 1, 2, 2, 2, 3, 1, 2, 2, 2]
-charmer	1.9	0.53852	[3, 2, 2, 2, 2, 2, 1, 1, 2, 2]
-charmers	2.1	0.83066	[2, 1, 2, 2, 4, 3, 2, 1, 2, 2]
-charmeuse	0.3	0.78102	[0, 0, 0, 1, 0, 2, 1, 0, -1, 0]
-charmeuses	0.4	0.66332	[0, 0, 1, 0, 1, 0, 0, 0, 0, 2]
-charming	2.8	0.4	[3, 3, 3, 3, 3, 3, 2, 3, 2, 3]
-charminger	1.5	0.67082	[2, 3, 1, 2, 1, 1, 2, 1, 1, 1]
-charmingest	2.4	0.66332	[2, 3, 3, 1, 3, 2, 3, 3, 2, 2]
-charmingly	2.2	0.87178	[2, 2, 2, 1, 2, 2, 3, 3, 4, 1]
-charmless	-1.8	0.87178	[-3, -1, -3, -1, -1, -1, -2, -1, -3, -2]
-charms	1.9	0.7	[1, 2, 3, 2, 1, 2, 3, 1, 2, 2]
-chastise	-2.5	0.92195	[-4, -3, -2, -1, -4, -3, -2, -2, -2, -2]
-chastised	-2.2	1.16619	[-2, -3, -2, -4, -1, -1, -3, 0, -3, -3]
-chastises	-1.7	1.61555	[-3, -3, -3, -1, 1, -2, 1, -1, -2, -4]
-chastising	-1.7	0.78102	[-2, -3, -2, -2, -2, 0, -1, -1, -2, -2]
-cheat	-2.0	0.7746	[-2, -3, -3, -2, -2, -1, -1, -1, -2, -3]
-cheated	-2.3	0.64031	[-2, -4, -2, -2, -2, -2, -3, -2, -2, -2]
-cheater	-2.5	0.67082	[-2, -4, -2, -3, -2, -2, -3, -2, -3, -2]
-cheaters	-1.9	0.83066	[-2, -2, -2, -1, -1, -4, -2, -1, -2, -2]
-cheating	-2.6	0.91652	[-2, -3, -3, -2, -4, -4, -3, -2, -1, -2]
-cheats	-1.8	0.6	[-3, -1, -2, -1, -2, -1, -2, -2, -2, -2]
-cheer	2.3	0.64031	[2, 1, 2, 2, 2, 3, 3, 3, 2, 3]
-cheered	2.3	0.78102	[2, 3, 3, 4, 2, 1, 2, 2, 2, 2]
-cheerer	1.7	0.45826	[1, 2, 2, 2, 1, 1, 2, 2, 2, 2]
-cheerers	1.8	0.87178	[2, 2, 3, 2, 1, 2, 0, 1, 3, 2]
-cheerful	2.5	0.67082	[3, 2, 3, 2, 2, 2, 4, 2, 3, 2]
-cheerfuller	1.9	0.83066	[3, 3, 2, 3, 2, 1, 1, 2, 1, 1]
-cheerfullest	3.2	0.87178	[4, 4, 4, 4, 3, 2, 2, 3, 2, 4]
-cheerfully	2.1	0.83066	[3, 2, 2, 2, 1, 3, 1, 3, 1, 3]
-cheerfulness	2.1	0.9434	[3, 2, 1, 2, 3, 4, 1, 2, 1, 2]
-cheerier	2.6	0.4899	[2, 2, 3, 3, 2, 3, 3, 2, 3, 3]
-cheeriest	2.2	0.6	[3, 2, 3, 1, 2, 2, 3, 2, 2, 2]
-cheerily	2.5	0.67082	[3, 3, 2, 3, 2, 4, 2, 2, 2, 2]
-cheeriness	2.5	0.67082	[3, 2, 4, 2, 3, 2, 3, 2, 2, 2]
-cheering	2.3	0.64031	[3, 3, 2, 1, 3, 2, 2, 2, 3, 2]
-cheerio	1.2	0.6	[2, 1, 1, 1, 2, 1, 1, 1, 2, 0]
-cheerlead	1.7	0.78102	[1, 2, 0, 2, 2, 2, 2, 3, 1, 2]
-cheerleader	0.9	0.9434	[1, 1, 0, 2, 1, 0, 0, 1, 0, 3]
-cheerleaders	1.2	1.07703	[2, 0, 0, 1, 1, 0, 3, 3, 1, 1]
-cheerleading	1.2	1.07703	[2, 2, 0, 0, 1, 0, 3, 2, 0, 2]
-cheerleads	1.2	1.07703	[2, 3, 0, 3, 1, 0, 0, 1, 1, 1]
-cheerled	1.5	1.11803	[0, 2, 1, 4, 2, 2, 2, 1, 1, 0]
-cheerless	-1.7	1.1	[-2, -3, -2, -2, -3, -2, -1, -1, 1, -2]
-cheerlessly	-0.8	1.98997	[-2, 4, -1, -2, -1, -2, -2, -2, 2, -2]
-cheerlessness	-1.7	1.48661	[-2, -1, -2, -3, -2, -4, -1, 2, -2, -2]
-cheerly	2.4	0.66332	[2, 2, 3, 2, 2, 3, 4, 2, 2, 2]
-cheers	2.1	1.3	[2, 2, 1, 3, 2, 3, 3, 4, -1, 2]
-cheery	2.6	0.66332	[3, 2, 2, 3, 2, 3, 4, 2, 3, 2]
-cherish	1.6	1.49666	[0, 3, 3, 3, 2, 2, 2, 1, -2, 2]
-cherishable	2.0	1.41421	[-2, 2, 2, 2, 3, 2, 3, 3, 2, 3]
-cherished	2.3	0.64031	[3, 2, 2, 3, 2, 2, 1, 3, 2, 3]
-cherisher	2.2	0.4	[2, 2, 3, 2, 2, 2, 2, 3, 2, 2]
-cherishers	1.9	0.7	[3, 3, 2, 2, 1, 1, 2, 2, 2, 1]
-cherishes	2.2	0.74833	[2, 2, 3, 2, 2, 2, 2, 4, 2, 1]
-cherishing	2.0	0.7746	[3, 3, 2, 2, 1, 2, 1, 3, 2, 1]
-chic	1.1	1.3	[1, 2, 2, -2, 2, 0, 1, 1, 3, 1]
-childish	-1.2	0.74833	[-1, -1, -2, -3, -1, 0, -1, -1, -1, -1]
-chilling	-0.1	1.92094	[3, -2, 0, 1, -2, -2, -1, -2, 1, 3]
-choke	-2.5	0.92195	[-1, -2, -3, -3, -2, -4, -2, -4, -2, -2]
-choked	-2.1	1.3	[-4, -3, 0, -2, -1, -3, -3, -2, 0, -3]
-chokes	-2.0	0.89443	[-4, -3, -1, -2, -1, -2, -2, -2, -1, -2]
-choking	-2.0	1.26491	[-4, -2, -2, -3, -2, -2, -3, -1, 1, -2]
-chuckle	1.7	0.45826	[2, 1, 2, 2, 2, 2, 1, 1, 2, 2]
-chuckled	1.2	0.9798	[2, 2, 1, 1, 2, 0, 1, 2, -1, 2]
-chucklehead	-1.9	0.53852	[-2, -2, -1, -3, -2, -2, -2, -2, -1, -2]
-chuckleheaded	-1.3	1.84662	[-3, -4, -2, 0, 3, -1, -2, 0, -2, -2]
-chuckleheads	-1.1	0.9434	[-1, -2, 0, -1, -1, -3, 0, 0, -2, -1]
-chuckler	0.8	1.07703	[2, 1, -1, 0, 2, 1, 1, 2, -1, 1]
-chucklers	1.2	0.87178	[1, 1, 2, 3, 1, 0, 1, 0, 2, 1]
-chuckles	1.1	1.13578	[2, 2, -1, 1, 2, 1, 1, 2, -1, 2]
-chucklesome	1.1	0.53852	[1, 1, 2, 1, 1, 1, 0, 2, 1, 1]
-chuckling	1.4	0.4899	[1, 2, 1, 2, 1, 1, 2, 2, 1, 1]
-chucklingly	1.2	0.4	[1, 1, 1, 1, 2, 1, 1, 1, 2, 1]
-clarifies	0.9	1.13578	[-2, 1, 0, 2, 1, 2, 2, 1, 1, 1]
-clarity	1.7	0.78102	[2, 1, 2, 3, 3, 1, 1, 2, 1, 1]
-classy	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
-clean	1.7	0.78102	[3, 1, 2, 1, 2, 1, 3, 2, 1, 1]
-cleaner	0.7	0.78102	[1, 0, 1, 0, 0, 0, 2, 1, 2, 0]
-clear	1.6	1.2	[2, 1, 1, 0, 3, 1, 2, 4, 2, 0]
-cleared	0.4	0.4899	[0, 0, 1, 1, 0, 0, 0, 0, 1, 1]
-clearly	1.7	0.78102	[2, 2, 2, 2, 1, 2, 0, 2, 1, 3]
-clears	0.3	0.78102	[0, 1, 0, 0, 0, -1, 1, 2, 0, 0]
-clever	2.0	0.7746	[2, 1, 2, 2, 2, 1, 3, 1, 3, 3]
-cleverer	2.0	0.44721	[2, 2, 2, 3, 2, 2, 1, 2, 2, 2]
-cleverest	2.6	0.91652	[4, 3, 2, 2, 4, 3, 2, 1, 2, 3]
-cleverish	1.0	1.18322	[1, 1, 1, 1, 1, 1, 2, 1, -2, 3]
-cleverly	2.3	0.45826	[2, 3, 2, 2, 2, 3, 2, 2, 3, 2]
-cleverness	2.3	0.9	[2, 4, 2, 2, 1, 3, 3, 3, 1, 2]
-clevernesses	1.4	0.66332	[1, 1, 1, 2, 2, 2, 2, 0, 2, 1]
-clouded	-0.2	0.9798	[-2, 0, 2, 0, 0, -1, 0, -1, 0, 0]
-clueless	-1.5	0.5	[-1, -2, -1, -2, -2, -1, -1, -1, -2, -2]
-cock	-0.6	1.49666	[0, 0, -4, 0, 0, 1, 0, -3, 0, 0]
-cocksucker	-3.1	0.83066	[-3, -4, -2, -2, -4, -4, -4, -2, -3, -3]
-cocksuckers	-2.6	1.42829	[-4, -3, -4, -3, -3, 1, -3, -1, -3, -3]
-cocky	-0.5	1.0247	[2, 0, -1, 0, -1, -2, 0, -1, -1, -1]
-coerced	-1.5	0.67082	[-1, -2, -2, -2, -1, 0, -1, -2, -2, -2]
-collapse	-2.2	0.87178	[-3, -1, -2, -4, -3, -2, -2, -2, -1, -2]
-collapsed	-1.1	1.64012	[-1, -2, -2, -1, -2, -2, 2, 2, -3, -2]
-collapses	-1.2	0.87178	[-2, -1, -2, 0, -2, 0, 0, -2, -1, -2]
-collapsing	-1.2	0.6	[-1, -1, -2, -2, -2, -1, 0, -1, -1, -1]
-collide	-0.3	1.61555	[-3, 0, -1, 3, 0, -1, -1, 2, -1, -1]
-collides	-1.1	1.22066	[-2, -2, -1, -1, 0, -2, 2, -2, -1, -2]
-colliding	-0.5	1.36015	[-2, 2, -1, -1, 0, -1, -2, 2, -1, -1]
-collision	-1.5	0.67082	[-1, -1, -2, -1, -2, -1, -1, -3, -2, -1]
-collisions	-1.1	0.7	[0, -2, -1, 0, -1, -1, -2, -2, -1, -1]
-colluding	-1.2	1.32665	[-1, -1, -2, -2, 0, -3, 2, -2, -1, -2]
-combat	-1.4	1.0198	[0, -2, 0, -2, -2, -2, -1, -3, 0, -2]
-combats	-0.8	1.16619	[0, -2, -3, -1, 0, 0, 0, -1, 1, -2]
-comedian	1.6	1.0198	[1, 0, 2, 3, 2, 0, 3, 1, 2, 2]
-comedians	1.2	1.16619	[0, 0, 0, 2, 3, 1, 3, 2, 0, 1]
-comedic	1.7	0.64031	[2, 1, 1, 3, 1, 2, 2, 2, 1, 2]
-comedically	2.1	0.7	[3, 2, 2, 1, 2, 3, 3, 2, 1, 2]
-comedienne	0.6	0.66332	[0, 2, 1, 0, 1, 1, 0, 1, 0, 0]
-comediennes	1.6	1.11355	[2, 1, 3, 0, 0, 3, 1, 1, 2, 3]
-comedies	1.7	1.00499	[0, 2, 1, 3, 3, 3, 1, 1, 2, 1]
-comedo	0.3	0.9	[0, 0, 0, 0, -1, 0, 2, 0, 2, 0]
-comedones	-0.8	0.9798	[0, 0, 0, -1, 0, -3, 0, -1, -1, -2]
-comedown	-0.8	1.07703	[-1, -1, -1, 0, -2, -1, 2, -1, -2, -1]
-comedowns	-0.9	0.53852	[-1, -1, -1, -1, 0, -2, 0, -1, -1, -1]
-comedy	1.5	0.67082	[1, 1, 2, 1, 3, 2, 1, 1, 2, 1]
-comfort	1.5	0.67082	[1, 3, 1, 2, 1, 1, 2, 1, 1, 2]
-comfortable	2.3	0.64031	[1, 2, 3, 2, 2, 3, 3, 3, 2, 2]
-comfortableness	1.3	1.48661	[4, 2, 2, 3, 1, 1, 1, -1, -1, 1]
-comfortably	1.8	0.74833	[1, 2, 2, 1, 3, 3, 1, 2, 1, 2]
-comforted	1.8	0.6	[2, 2, 2, 0, 2, 2, 2, 2, 2, 2]
-comforter	1.9	0.53852	[2, 3, 2, 2, 2, 1, 2, 2, 2, 1]
-comforters	1.2	0.6	[2, 1, 0, 2, 1, 1, 2, 1, 1, 1]
-comforting	1.7	0.64031	[1, 2, 1, 1, 2, 2, 2, 3, 2, 1]
-comfortingly	1.7	0.45826	[1, 2, 1, 2, 2, 1, 2, 2, 2, 2]
-comfortless	-1.8	0.6	[-3, -2, -1, -2, -1, -2, -1, -2, -2, -2]
-comforts	2.1	0.7	[3, 1, 3, 1, 2, 2, 3, 2, 2, 2]
-commend	1.9	0.7	[1, 2, 2, 1, 2, 1, 2, 3, 2, 3]
-commended	1.9	0.9434	[1, 3, 2, 3, 2, 2, 0, 1, 3, 2]
-commit	1.2	0.87178	[1, 0, 2, 2, 0, 0, 2, 2, 1, 2]
-commitment	1.6	0.91652	[3, 1, 2, 0, 3, 1, 2, 1, 2, 1]
-commitments	0.5	0.92195	[1, 3, 0, 0, 0, 0, 0, 0, 0, 1]
-commits	0.1	1.13578	[0, -1, 0, 2, 1, -1, 1, 1, -2, 0]
-committed	1.1	0.7	[0, 1, 1, 2, 0, 2, 1, 1, 2, 1]
-committing	0.3	1.18743	[0, 1, 0, 3, 0, -2, 1, 0, 0, 0]
-compassion	2.0	0.7746	[3, 2, 1, 1, 2, 1, 3, 2, 2, 3]
-compassionate	2.2	0.87178	[0, 3, 3, 2, 2, 3, 3, 2, 2, 2]
-compassionated	1.6	0.66332	[3, 1, 2, 2, 1, 2, 2, 1, 1, 1]
-compassionately	1.7	1.41774	[1, 3, 3, 2, 1, 2, 3, 2, -2, 2]
-compassionateness	0.9	1.37477	[-3, 2, 2, 1, 1, 1, 2, 1, 1, 1]
-compassionates	1.6	0.4899	[2, 1, 2, 2, 1, 2, 2, 1, 1, 2]
-compassionating	1.6	0.91652	[3, 0, 2, 1, 3, 1, 2, 1, 2, 1]
-compassionless	-2.6	0.8	[-3, -2, -2, -3, -4, -3, -1, -2, -3, -3]
-compelled	0.2	1.07703	[-1, 0, 0, 0, 1, 2, -1, -1, 2, 0]
-compelling	0.9	0.94339	[1, 1, 1, 0, 1, 2, 2, -1, 2, 0]
-competent	1.3	0.78102	[1, 3, 1, 1, 2, 1, 1, 0, 2, 1]
-competitive	0.7	0.9	[0, 2, 0, 2, 0, 1, 0, 0, 0, 2]
-complacent	-0.3	1.1	[2, -1, -1, 1, -1, -1, -1, 1, -1, -1]
-complain	-1.5	0.67082	[-1, -1, -1, -2, -1, -2, -3, -2, -1, -1]
-complainant	-0.7	0.78102	[0, 0, -1, 0, 0, -2, 0, -1, -2, -1]
-complainants	-1.1	1.3	[-2, -1, 0, -2, -3, -2, -1, 1, -2, 1]
-complained	-1.7	0.64031	[-1, -3, -2, -2, -1, -1, -2, -2, -1, -2]
-complainer	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -2, -1, -2]
-complainers	-1.3	1.00499	[-2, -1, -1, -2, -3, 1, -1, -1, -2, -1]
-complaining	-0.8	1.249	[-2, -1, -1, -1, -2, -1, -1, 2, 1, -2]
-complainingly	-1.7	0.64031	[-1, -2, -1, -2, -1, -2, -1, -2, -3, -2]
-complains	-1.6	0.66332	[-1, -2, -1, -2, -2, -3, -1, -1, -1, -2]
-complaint	-1.2	1.249	[-1, -1, -2, -2, -1, -3, -1, -1, 2, -2]
-complaints	-1.7	0.45826	[-2, -2, -2, -1, -2, -2, -2, -1, -1, -2]
-compliment	2.1	0.7	[2, 2, 3, 1, 2, 3, 3, 1, 2, 2]
-complimentarily	1.7	0.45826	[2, 2, 2, 2, 1, 1, 2, 1, 2, 2]
-complimentary	1.9	0.7	[1, 2, 2, 1, 2, 1, 2, 3, 3, 2]
-complimented	1.8	1.4	[3, 2, 2, 2, 3, 2, -2, 3, 1, 2]
-complimenting	2.3	0.64031	[2, 2, 1, 3, 3, 2, 2, 3, 3, 2]
-compliments	1.7	0.45826	[2, 1, 2, 2, 1, 2, 2, 1, 2, 2]
-comprehensive	1.0	0.63246	[1, 1, 1, 0, 2, 2, 1, 0, 1, 1]
-conciliate	1.0	1.18322	[2, 1, 1, 0, 2, 2, -2, 2, 1, 1]
-conciliated	1.1	0.9434	[1, 3, 0, 0, 2, 0, 2, 1, 1, 1]
-conciliates	1.1	0.9434	[1, 3, 0, 0, 2, 0, 2, 1, 1, 1]
-conciliating	1.3	0.78102	[2, 2, 1, 1, 2, 0, 2, 1, 2, 0]
-condemn	-1.6	1.0198	[-2, -2, -1, -2, -2, 1, -2, -3, -1, -2]
-condemnation	-2.8	0.9798	[-3, -4, -2, -4, -2, -4, -2, -1, -3, -3]
-condemned	-1.9	1.81384	[2, -2, -2, -3, -2, -3, -3, -4, 1, -3]
-condemns	-2.3	0.64031	[-2, -2, -3, -3, -3, -2, -2, -3, -1, -2]
-confidence	2.3	0.64031	[3, 3, 3, 3, 1, 2, 2, 2, 2, 2]
-confident	2.2	0.87178	[1, 3, 3, 2, 3, 1, 3, 2, 1, 3]
-confidently	2.1	0.53852	[2, 2, 3, 1, 2, 2, 2, 2, 3, 2]
-conflict	-1.3	0.45826	[-2, -2, -1, -2, -1, -1, -1, -1, -1, -1]
-conflicting	-1.7	0.64031	[-1, -2, -3, -1, -2, -1, -2, -1, -2, -2]
-conflictive	-1.8	0.6	[-2, -2, -2, -2, -1, -1, -3, -2, -1, -2]
-conflicts	-1.6	0.8	[-1, -1, -1, -2, -1, -1, -3, -2, -1, -3]
-confront	-0.7	0.78102	[0, -1, -1, 0, 1, -1, -1, -2, -1, -1]
-confrontation	-1.3	1.55242	[-3, -2, -3, -2, -1, -2, 1, 2, -1, -2]
-confrontational	-1.6	0.66332	[-1, -2, -1, -2, -1, -2, -1, -2, -3, -1]
-confrontationist	-1.0	1.34164	[-1, -2, -2, 2, 1, -1, -2, -1, -2, -2]
-confrontationists	-1.2	1.46969	[-2, -3, -1, -2, 2, 1, -1, -2, -2, -2]
-confrontations	-1.5	1.0247	[-1, -3, -2, -1, -3, 0, -2, -2, 0, -1]
-confronted	-0.8	0.74833	[-1, -2, -1, -1, -1, -1, -1, -1, 1, 0]
-confronter	-0.3	1.1	[0, -2, 1, -2, 0, -1, -1, 0, 1, 1]
-confronters	-1.3	1.26886	[-3, -2, -2, -2, -1, -2, 1, 1, -1, -2]
-confronting	-0.6	1.11355	[-2, -1, -1, 0, -2, 2, -1, 0, 0, -1]
-confronts	-0.9	0.53852	[-1, -1, -1, -1, 0, -1, 0, -1, -2, -1]
-confuse	-0.9	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, 0, -1]
-confused	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -2]
-confusedly	-0.6	1.42829	[-3, -1, -1, 1, -1, -1, -2, 2, 1, -1]
-confusedness	-1.5	0.67082	[-3, -1, -1, -2, -1, -2, -2, -1, -1, -1]
-confuses	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -2]
-confusing	-0.9	0.7	[-1, -1, -1, -2, -1, -1, 1, -1, -1, -1]
-confusingly	-1.4	0.66332	[-1, -1, -1, -1, -3, -1, -2, -1, -1, -2]
-confusion	-1.2	0.6	[-1, -1, -1, -1, -1, -2, 0, -1, -2, -2]
-confusional	-1.2	0.6	[-2, -2, 0, -1, -2, -1, -1, -1, -1, -1]
-confusions	-0.9	1.04403	[-1, -2, -1, -1, -1, 2, -2, -1, -1, -1]
-congrats	2.4	0.91652	[1, 3, 3, 3, 2, 2, 4, 1, 2, 3]
-congratulate	2.2	1.249	[3, 3, 2, 3, -1, 2, 1, 3, 3, 3]
-congratulation	2.9	0.9434	[3, 3, 3, 2, 4, 2, 4, 3, 4, 1]
-congratulations	2.9	0.53852	[2, 3, 3, 3, 3, 3, 3, 3, 4, 2]
-consent	0.9	0.7	[0, 0, 1, 1, 1, 2, 1, 2, 0, 1]
-consents	1.0	0.63246	[0, 2, 1, 0, 1, 1, 1, 2, 1, 1]
-considerate	1.9	1.22066	[2, -1, 3, 2, 2, 2, 4, 1, 2, 2]
-consolable	1.1	0.53852	[1, 1, 2, 1, 0, 1, 1, 1, 2, 1]
-conspiracy	-2.4	0.66332	[-2, -2, -3, -3, -2, -2, -4, -2, -2, -2]
-constrained	-0.4	1.0198	[-1, 0, -1, -1, -1, -1, 2, -1, 1, -1]
-contagion	-2.0	1.18322	[-1, 0, -2, -1, -2, -4, -2, -4, -2, -2]
-contagions	-1.5	0.92195	[-2, -2, -2, -2, 1, -2, -1, -1, -2, -2]
-contagious	-1.4	0.91652	[-2, -2, -2, 0, -1, -1, -2, 0, -1, -3]
-contempt	-2.8	0.6	[-3, -3, -4, -2, -3, -2, -3, -3, -2, -3]
-contemptibilities	-2.0	1.09545	[-2, 1, -2, -2, -3, -3, -3, -2, -2, -2]
-contemptibility	-0.9	1.51327	[-2, -1, -3, -1, 0, -3, -1, 1, 2, -1]
-contemptible	-1.6	1.68523	[-2, -2, -3, -3, -2, -3, -1, -3, 1, 2]
-contemptibleness	-1.9	0.7	[-2, -2, -1, -2, -2, -1, -1, -2, -3, -3]
-contemptibly	-1.4	1.49666	[-3, 0, -2, -3, -2, -2, -1, -3, 1, 1]
-contempts	-1.0	1.48324	[-2, -2, -1, 0, 1, -1, -2, -3, 2, -2]
-contemptuous	-2.2	1.83303	[-2, -3, -4, -2, -3, -3, 3, -2, -3, -3]
-contemptuously	-2.4	0.8	[-1, -3, -2, -3, -3, -2, -1, -3, -3, -3]
-contemptuousness	-1.1	1.57797	[-3, -1, -2, 3, -2, 0, -1, -1, -2, -2]
-contend	0.2	1.07703	[0, 0, 1, 1, -2, 1, -1, 0, 2, 0]
-contender	0.5	1.0247	[1, 3, -1, 0, 0, 1, 0, 1, 0, 0]
-contented	1.4	1.56205	[1, 1, 3, 2, 2, 2, -3, 2, 2, 2]
-contentedly	1.9	0.9434	[3, 1, 2, 3, 2, 3, 0, 2, 1, 2]
-contentedness	1.4	0.4899	[1, 2, 1, 1, 2, 2, 2, 1, 1, 1]
-contentious	-1.2	1.4	[-2, -2, -2, -2, -2, -2, -1, 2, 1, -2]
-contentment	1.5	1.74642	[2, 1, 3, 2, 2, 1, 2, 4, 1, -3]
-contestable	0.6	1.0198	[2, -1, 1, 0, 1, -1, 1, 1, 2, 0]
-contradict	-1.3	0.78102	[-2, -1, -1, 0, -2, 0, -1, -2, -2, -2]
-contradictable	-1.0	0.63246	[-1, -1, -2, 0, -1, -1, 0, -1, -1, -2]
-contradicted	-1.3	0.45826	[-1, -1, -1, -1, -2, -1, -2, -1, -1, -2]
-contradicting	-1.3	0.9	[-2, -2, -2, -1, -2, -1, 1, -1, -1, -2]
-contradiction	-1.0	0.89443	[-1, 0, 0, -1, 0, -3, -2, -1, -1, -1]
-contradictions	-1.3	0.78102	[0, -2, -1, -2, -1, -2, -1, 0, -2, -2]
-contradictious	-1.9	1.04403	[-2, -3, 0, -3, -3, -1, -2, -1, -1, -3]
-contradictor	-1.0	0.63246	[-1, -1, -1, -2, -1, -2, 0, 0, -1, -1]
-contradictories	-0.5	1.11803	[-1, 0, -1, -2, 2, 1, -1, -1, -1, -1]
-contradictorily	-0.9	1.3	[0, -1, -1, -1, -3, -1, 1, 1, -3, -1]
-contradictoriness	-1.4	0.4899	[-2, -1, -1, -1, -2, -1, -1, -2, -2, -1]
-contradictors	-1.6	0.66332	[-1, -2, -1, -2, -1, -1, -3, -1, -2, -2]
-contradictory	-1.4	0.4899	[-1, -2, -1, -2, -1, -1, -1, -1, -2, -2]
-contradicts	-1.4	0.66332	[-1, -2, -1, -2, -2, -2, 0, -1, -1, -2]
-controversial	-0.8	0.87178	[0, 0, -1, 1, -2, -1, -1, -1, -1, -2]
-controversially	-1.1	1.04403	[0, -1, -1, -2, -1, -2, -1, 1, -3, -1]
-convince	1.0	0.89443	[-1, 2, 2, 1, 1, 0, 1, 1, 2, 1]
-convinced	1.7	0.64031	[2, 1, 1, 2, 1, 2, 2, 2, 1, 3]
-convincer	0.6	0.66332	[2, 0, 1, 0, 1, 1, 0, 0, 0, 1]
-convincers	0.3	0.64031	[0, 0, 0, 0, 0, 1, 0, 0, 0, 2]
-convinces	0.7	0.78102	[1, 0, 2, 0, 1, 0, 0, 0, 1, 2]
-convincing	1.7	0.9	[2, 2, 0, 3, 3, 1, 1, 2, 2, 1]
-convincingly	1.6	0.66332	[3, 2, 1, 1, 1, 2, 2, 1, 2, 1]
-convincingness	0.7	1.34536	[0, 0, 0, 1, -2, 2, 0, 3, 1, 2]
-convivial	1.2	1.16619	[1, 2, -2, 2, 1, 2, 2, 1, 2, 1]
-cool	1.3	0.64031	[1, 1, 2, 1, 1, 1, 2, 2, 2, 0]
-cornered	-1.1	0.83066	[-1, -1, -3, -1, 0, -1, 0, -1, -2, -1]
-corpse	-2.7	1.18743	[-3, -4, 0, -4, -3, -3, -3, -1, -3, -3]
-costly	-0.4	1.0198	[-1, 0, -1, -1, 2, -1, -1, 1, -1, -1]
-courage	2.2	0.74833	[2, 3, 1, 2, 3, 2, 3, 3, 1, 2]
-courageous	2.4	0.4899	[2, 3, 3, 3, 3, 2, 2, 2, 2, 2]
-courageously	2.3	0.78102	[3, 3, 3, 1, 3, 3, 2, 2, 2, 1]
-courageousness	2.1	0.7	[3, 3, 1, 2, 1, 2, 2, 2, 3, 2]
-courteous	2.3	0.45826	[2, 2, 2, 3, 3, 2, 3, 2, 2, 2]
-courtesy	1.5	0.67082	[1, 1, 2, 3, 1, 2, 1, 1, 2, 1]
-cover-up	-1.2	1.16619	[-1, -1, -4, -1, 0, 0, -2, 0, -1, -2]
-coward	-2.0	0.63246	[-3, -3, -1, -2, -2, -1, -2, -2, -2, -2]
-cowardly	-1.6	0.8	[-1, -1, -1, -3, -1, -2, -3, -2, -1, -1]
-coziness	1.5	1.11803	[2, 3, 1, 3, 1, 2, 2, -1, 1, 1]
-cramp	-0.8	1.66132	[0, -1, -1, -3, -3, 1, -2, 1, -2, 2]
-crap	-1.6	0.66332	[-1, -1, -2, -2, -1, -2, -3, -1, -1, -2]
-crappy	-2.6	0.8	[-1, -3, -3, -2, -3, -4, -2, -2, -3, -3]
-crash	-1.7	1.18743	[-2, -3, -2, -1, -2, 0, 0, -1, -4, -2]
-craze	-0.6	1.49666	[0, -3, -1, -1, -2, 0, 0, -1, 3, -1]
-crazed	-0.5	2.24722	[-2, -1, 3, -3, -3, 1, 1, -1, 3, -3]
-crazes	0.2	1.6	[-2, -1, 3, -1, -1, 1, 2, 0, 2, -1]
-crazier	-0.1	1.7	[2, -2, -2, 0, -1, 1, 3, 1, -1, -2]
-craziest	-0.2	2.13542	[2, -2, -3, 3, -2, 0, 2, 2, -2, -2]
-crazily	-1.5	0.67082	[-2, -1, -1, -2, -1, -3, -2, -1, -1, -1]
-craziness	-1.6	0.66332	[-2, 0, -2, -1, -2, -1, -2, -2, -2, -2]
-crazinesses	-1.0	1.48324	[1, -2, -2, 2, -1, 0, -2, -1, -3, -2]
-crazing	-0.5	0.80623	[0, 0, 0, 0, -2, -1, -2, 0, 0, 0]
-crazy	-1.4	1.35647	[-2, -1, -1, -2, -3, -2, -3, -1, 2, -1]
-crazyweed	0.8	0.9798	[2, 0, 0, 0, 0, 2, 2, 0, 2, 0]
-create	1.1	1.13578	[1, 1, 1, 2, 3, 0, 0, 0, 3, 0]
-created	1.0	0.7746	[2, 0, 0, 1, 1, 2, 0, 1, 1, 2]
-creates	1.1	0.83066	[2, 0, 0, 1, 1, 2, 0, 1, 2, 2]
-creatin	0.1	0.53852	[0, 0, 0, 1, 0, 0, 0, 1, -1, 0]
-creatine	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 0, 2]
-creating	1.2	1.249	[0, 0, 0, 0, 4, 1, 1, 2, 2, 2]
-creatinine	0.4	1.2	[0, 0, 0, 4, 0, 0, 0, 0, 0, 0]
-creation	1.1	0.83066	[2, 1, 1, 2, 0, 0, 0, 1, 2, 2]
-creationism	0.7	0.9	[2, 0, 0, 0, 0, 0, 2, 0, 2, 1]
-creationisms	1.1	1.37477	[2, 4, 0, 3, 0, 0, 1, 1, 0, 0]
-creationist	0.8	0.9798	[2, 0, 0, 0, 0, 0, 2, 0, 2, 2]
-creationists	0.5	0.67082	[0, 0, 0, 1, 1, 0, 2, 0, 1, 0]
-creations	1.6	0.91652	[3, 2, 1, 1, 1, 3, 1, 2, 2, 0]
-creative	1.9	0.53852	[2, 1, 2, 2, 2, 1, 3, 2, 2, 2]
-creatively	1.5	0.80623	[2, 2, 1, 0, 2, 2, 2, 0, 2, 2]
-creativeness	1.8	1.07703	[3, 2, 1, 0, 2, 2, 2, 0, 3, 3]
-creativities	1.7	1.00499	[2, 2, 1, 0, 3, 2, 2, 0, 2, 3]
-creativity	1.6	0.8	[2, 1, 2, 2, 3, 2, 0, 2, 1, 1]
-credit	1.6	0.91652	[1, 1, 0, 2, 3, 3, 2, 2, 1, 1]
-creditabilities	1.4	1.28062	[0, 3, -1, 2, 2, 2, 1, 2, 0, 3]
-creditability	1.9	1.3	[3, 0, 4, 0, 1, 1, 3, 2, 2, 3]
-creditable	1.8	0.6	[2, 1, 1, 1, 2, 2, 3, 2, 2, 2]
-creditableness	1.2	0.74833	[1, 1, 1, 3, 2, 1, 0, 1, 1, 1]
-creditably	1.7	0.78102	[3, 1, 1, 0, 2, 2, 2, 2, 2, 2]
-credited	1.5	1.11803	[1, 1, 1, 0, 3, 2, 0, 3, 1, 3]
-crediting	0.6	0.4899	[1, 0, 0, 0, 1, 1, 1, 0, 1, 1]
-creditor	-0.1	1.44568	[-2, -1, 1, -2, -1, 1, 2, -1, 2, 0]
-credits	1.5	1.0247	[2, -1, 2, 0, 2, 2, 2, 2, 2, 2]
-creditworthiness	1.9	1.3	[4, 0, 3, 1, 2, 1, 4, 2, 1, 1]
-creditworthy	2.4	0.66332	[3, 3, 3, 1, 2, 3, 3, 2, 2, 2]
-crestfallen	-2.5	0.67082	[-2, -3, -3, -2, -3, -2, -4, -2, -2, -2]
-cried	-1.6	0.8	[-1, -3, -1, -2, -2, -2, 0, -2, -1, -2]
-cries	-1.7	0.64031	[-1, -3, -1, -2, -2, -2, -1, -2, -1, -2]
-crime	-2.5	0.80623	[-3, -3, -4, -2, -2, -1, -2, -2, -3, -3]
-criminal	-2.4	0.91652	[-3, -2, -4, -3, -1, -2, -3, -2, -1, -3]
-criminals	-2.7	0.9	[-2, -2, -1, -3, -3, -4, -4, -3, -2, -3]
-crisis	-3.1	0.7	[-3, -2, -4, -3, -3, -2, -4, -4, -3, -3]
-critic	-1.1	0.53852	[-1, 0, -2, -1, -1, -1, -1, -1, -2, -1]
-critical	-1.3	0.78102	[-2, 0, -1, -1, -1, -2, -1, -3, -1, -1]
-criticise	-1.9	0.53852	[-2, -1, -2, -2, -2, -2, -3, -1, -2, -2]
-criticised	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -1, -2, -2, -2]
-criticises	-1.3	1.26886	[-2, -1, -1, -1, 2, -1, -3, -2, -2, -2]
-criticising	-1.7	0.78102	[-1, -1, -1, -3, -1, -2, -2, -2, -1, -3]
-criticism	-1.9	0.53852	[-2, -1, -2, -2, -2, -2, -3, -1, -2, -2]
-criticisms	-0.9	1.37477	[-1, -1, 1, -1, -2, -2, -1, -3, 2, -1]
-criticizable	-1.0	0.63246	[-1, -2, 0, -1, -2, -1, 0, -1, -1, -1]
-criticize	-1.6	1.0198	[-2, -1, 0, -2, -1, -3, 0, -3, -2, -2]
-criticized	-1.5	0.92195	[-1, -2, -3, -1, -1, -1, -3, -1, -2, 0]
-criticizer	-1.5	0.67082	[-1, -2, -2, -1, -1, -1, -3, -1, -2, -1]
-criticizers	-1.6	0.4899	[-1, -1, -1, -2, -2, -2, -1, -2, -2, -2]
-criticizes	-1.4	0.66332	[-1, -1, -2, -1, -1, -1, -3, -1, -2, -1]
-criticizing	-1.5	0.67082	[-1, -1, -1, -2, -2, -1, -2, -1, -3, -1]
-critics	-1.2	0.6	[-2, 0, -1, -1, -1, -1, -2, -1, -2, -1]
-crude	-2.7	0.64031	[-2, -2, -3, -4, -2, -3, -3, -2, -3, -3]
-crudely	-1.2	0.4	[-1, -2, -2, -1, -1, -1, -1, -1, -1, -1]
-crudeness	-2.0	0.7746	[-3, -1, -1, -1, -3, -2, -3, -2, -2, -2]
-crudenesses	-2.0	1.0	[-3, -1, -1, -2, -4, -1, -1, -2, -2, -3]
-cruder	-2.0	0.89443	[-3, -2, -2, -1, -1, -2, -2, -1, -4, -2]
-crudes	-1.1	0.83066	[-2, -1, -1, -1, 0, 0, -1, -1, -3, -1]
-crudest	-2.4	1.0198	[-2, -1, -3, -3, -2, -1, -4, -4, -2, -2]
-cruel	-2.8	1.16619	[-2, -4, -1, -4, -1, -4, -2, -3, -3, -4]
-crueler	-2.3	0.45826	[-2, -3, -2, -2, -2, -3, -2, -2, -3, -2]
-cruelest	-2.6	0.8	[-4, -3, -2, -4, -2, -2, -2, -2, -2, -3]
-crueller	-2.4	0.4899	[-2, -3, -3, -3, -2, -2, -3, -2, -2, -2]
-cruellest	-2.9	1.04403	[-2, -3, -4, -4, -4, -3, -1, -2, -2, -4]
-cruelly	-2.8	0.4	[-3, -3, -3, -3, -3, -3, -2, -2, -3, -3]
-cruelness	-2.9	0.3	[-3, -3, -3, -3, -3, -3, -3, -3, -2, -3]
-cruelties	-2.3	1.00499	[-4, -3, -2, -1, -2, -2, -1, -4, -2, -2]
-cruelty	-2.9	0.83066	[-3, -3, -3, -3, -4, -3, -1, -3, -4, -2]
-crush	-0.6	1.11355	[0, 0, 0, -1, 1, 0, -2, -3, -1, 0]
-crushed	-1.8	0.6	[-2, -2, -2, -1, -2, -1, -1, -3, -2, -2]
-crushes	-1.9	0.53852	[-2, -2, -2, -2, -2, -1, -1, -3, -2, -2]
-crushing	-1.5	1.85742	[-2, -3, -1, -3, 2, -2, -2, -3, 2, -3]
-cry	-2.1	0.53852	[-2, -2, -2, -1, -2, -2, -3, -3, -2, -2]
-crying	-2.1	0.7	[-3, -1, -2, -2, -3, -2, -3, -2, -1, -2]
-cunt	-2.2	2.08806	[-4, -1, -4, -2, 2, -4, -4, -3, 1, -3]
-cunts	-2.9	1.44568	[-3, -4, -3, -4, -4, -4, -3, 1, -3, -2]
-curious	1.3	0.78102	[0, 1, 0, 2, 2, 2, 1, 1, 2, 2]
-curse	-2.5	0.67082	[-3, -3, -4, -2, -2, -3, -2, -2, -2, -2]
-cut	-1.1	0.53852	[-2, -1, -1, -1, 0, -1, -1, -1, -2, -1]
-cute	2.0	0.63246	[1, 3, 1, 2, 2, 2, 2, 3, 2, 2]
-cutely	1.3	1.00499	[3, 1, 1, 2, 2, 1, 1, 2, -1, 1]
-cuteness	2.3	0.45826	[2, 2, 2, 3, 2, 3, 3, 2, 2, 2]
-cutenesses	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
-cuter	2.3	0.9	[1, 2, 3, 4, 1, 2, 2, 3, 3, 2]
-cutes	1.8	0.87178	[1, 2, 3, 0, 1, 2, 2, 2, 3, 2]
-cutesie	1.0	1.18322	[2, 2, 1, 1, 0, 2, 2, -1, 2, -1]
-cutesier	1.5	1.20416	[3, -1, 2, 1, 1, 2, 2, 3, 0, 2]
-cutesiest	2.2	1.4	[3, 3, 4, 2, 2, 4, 2, -1, 2, 1]
-cutest	2.8	0.87178	[2, 3, 3, 4, 4, 3, 1, 3, 2, 3]
-cutesy	2.1	0.83066	[2, 1, 2, 2, 4, 3, 1, 2, 2, 2]
-cutey	2.1	1.04403	[1, 2, 3, 4, 1, 1, 3, 2, 3, 1]
-cuteys	1.5	1.0247	[3, 2, 2, 0, 1, 2, 1, 1, 3, 0]
-cutie	1.5	0.80623	[3, 1, 1, 2, 1, 1, 1, 3, 1, 1]
-cutiepie	2.0	1.09545	[3, 1, 2, 4, 0, 2, 1, 3, 2, 2]
-cuties	2.2	0.6	[3, 2, 2, 2, 3, 1, 2, 2, 3, 2]
-cuts	-1.2	0.6	[-1, -2, -1, 0, -1, -1, -2, -2, -1, -1]
-cutting	-0.5	0.67082	[0, -1, 0, 0, 0, -1, -1, -2, 0, 0]
-cynic	-1.4	0.8	[-1, -2, -1, 0, -2, -3, -1, -1, -1, -2]
-cynical	-1.6	0.66332	[-1, -1, -2, -2, -1, -1, -2, -2, -1, -3]
-cynically	-1.3	1.00499	[-2, -1, -1, -1, -3, -2, -1, -2, 1, -1]
-cynicism	-1.7	0.64031	[-2, -3, -1, -1, -2, -1, -2, -1, -2, -2]
-cynicisms	-1.7	0.78102	[-1, -1, -3, -1, -2, -3, -1, -2, -2, -1]
-cynics	-0.3	1.1	[-1, 0, -2, 0, 0, -1, 1, -1, 2, -1]
-d-:	1.6	0.66332	[1, 1, 1, 2, 2, 3, 1, 1, 2, 2]
-d:	1.2	0.87178	[1, 1, 1, 2, 1, 1, 2, 2, -1, 2]
-d=	1.5	0.67082	[1, 1, 1, 2, 3, 2, 1, 1, 1, 2]
-damage	-2.2	0.4	[-2, -3, -2, -2, -3, -2, -2, -2, -2, -2]
-damaged	-1.9	0.53852	[-2, -2, -2, -1, -2, -1, -2, -2, -3, -2]
-damager	-1.9	0.53852	[-2, -2, -2, -2, -2, -1, -2, -2, -3, -1]
-damagers	-2.0	0.63246	[-2, -3, -1, -2, -2, -1, -3, -2, -2, -2]
-damages	-1.9	1.04403	[-1, 0, -2, -2, -2, -4, -2, -1, -3, -2]
-damaging	-2.3	0.9	[-4, -1, -2, -4, -2, -2, -2, -2, -2, -2]
-damagingly	-2.0	0.7746	[-2, -2, -2, -2, -1, -3, -3, -1, -3, -1]
-damn	-1.7	0.64031	[-2, -1, -2, -1, -1, -3, -1, -2, -2, -2]
-damnable	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
-damnableness	-1.8	0.74833	[-2, -2, -2, -2, -1, -2, -2, 0, -3, -2]
-damnably	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
-damnation	-2.6	1.0198	[-3, -2, -3, -4, -4, -3, -1, -2, -1, -3]
-damnations	-1.4	1.11355	[-2, -1, -2, -3, -2, 0, -1, 1, -2, -2]
-damnatory	-2.6	1.42829	[-4, -1, -4, -2, -1, -3, -3, 0, -4, -4]
-damned	-1.6	0.66332	[-1, -1, -3, -1, -2, -2, -1, -2, -1, -2]
-damnedest	-0.5	1.5	[1, 0, 0, 0, -1, -1, 0, 2, -3, -3]
-damnified	-2.8	0.9798	[-1, -3, -3, -2, -2, -3, -4, -4, -2, -4]
-damnifies	-1.8	0.87178	[-2, -2, -1, -2, -3, -2, -2, 0, -1, -3]
-damnify	-2.2	0.74833	[-2, -2, -4, -2, -3, -2, -1, -2, -2, -2]
-damnifying	-2.4	0.66332	[-3, -1, -2, -2, -2, -2, -3, -3, -3, -3]
-damning	-1.4	0.8	[-1, -3, -1, -1, -1, -1, -3, -1, -1, -1]
-damningly	-2.0	1.61245	[-3, -2, -1, -4, -3, -3, -3, -2, 2, -1]
-damnit	-2.4	1.0198	[-3, -3, -2, -2, -3, -2, -4, -2, 0, -3]
-damns	-2.2	0.74833	[-2, -3, -2, -1, -3, -2, -1, -2, -3, -3]
-danger	-2.4	0.91652	[-3, -1, -2, -3, -3, -3, -2, -1, -2, -4]
-dangered	-2.4	0.66332	[-3, -3, -2, -3, -3, -2, -1, -2, -3, -2]
-dangering	-2.5	0.80623	[-1, -2, -2, -3, -4, -3, -3, -2, -2, -3]
-dangerous	-2.1	0.3	[-2, -3, -2, -2, -2, -2, -2, -2, -2, -2]
-dangerously	-2.0	0.44721	[-2, -2, -2, -1, -2, -3, -2, -2, -2, -2]
-dangerousness	-2.0	0.44721	[-2, -3, -2, -1, -2, -2, -2, -2, -2, -2]
-dangers	-2.2	0.87178	[-1, -1, -2, -4, -2, -3, -3, -2, -2, -2]
-daredevil	0.5	0.92195	[0, 1, -1, 2, 0, 0, 1, 0, 0, 2]
-daring	1.5	1.5	[3, 0, 1, 1, 2, -2, 3, 2, 2, 3]
-daringly	2.1	0.7	[3, 1, 2, 1, 3, 2, 2, 3, 2, 2]
-daringness	1.4	0.8	[0, 2, 1, 3, 1, 2, 2, 1, 1, 1]
-darings	0.4	0.91652	[0, 1, 1, 1, 0, 1, 0, 1, -2, 1]
-darkest	-2.2	0.6	[-3, -3, -2, -2, -3, -2, -1, -2, -2, -2]
-darkness	-1.0	0.44721	[-2, -1, -1, -1, -1, 0, -1, -1, -1, -1]
-darling	2.8	0.6	[3, 3, 2, 2, 3, 3, 4, 2, 3, 3]
-darlingly	1.6	0.66332	[1, 1, 2, 3, 1, 1, 2, 2, 2, 1]
-darlingness	2.3	0.45826	[3, 3, 2, 2, 2, 2, 2, 2, 3, 2]
-darlings	2.2	0.4	[3, 2, 2, 2, 2, 2, 2, 2, 3, 2]
-dauntless	2.3	0.78102	[3, 3, 2, 1, 3, 3, 2, 1, 2, 3]
-daze	-0.7	0.78102	[-1, 0, -1, -1, 1, -1, -1, 0, -1, -2]
-dazed	-0.7	0.64031	[0, -1, -1, 0, -1, -1, 0, -1, 0, -2]
-dazedly	-0.4	1.0198	[-1, -1, -1, -1, -1, 2, -1, 1, 0, -1]
-dazedness	-0.5	1.11803	[-1, 2, 0, -1, -1, -1, 1, -2, -1, -1]
-dazes	-0.3	0.78102	[0, -1, 0, 0, 0, -1, 0, 1, 0, -2]
-dead	-3.3	1.00499	[-4, -4, -1, -4, -4, -3, -4, -2, -3, -4]
-deadlock	-1.4	0.8	[-2, -2, -1, -3, -1, 0, -2, -1, -1, -1]
-deafening	-1.2	1.6	[-4, -2, 0, -3, 1, -2, 1, -2, -1, 0]
-dear	1.6	1.35647	[3, 3, 2, 2, 2, 2, 1, -2, 1, 2]
-dearer	1.9	0.7	[2, 2, 1, 2, 1, 1, 2, 3, 2, 3]
-dearest	2.6	0.8	[1, 2, 3, 3, 2, 2, 3, 3, 4, 3]
-dearie	2.2	0.6	[2, 2, 2, 3, 2, 1, 3, 2, 3, 2]
-dearies	1.0	1.0	[0, 1, 2, -1, 1, 1, 1, 1, 1, 3]
-dearly	1.8	1.07703	[3, 4, 2, 1, 1, 0, 1, 2, 2, 2]
-dearness	2.0	0.7746	[1, 1, 2, 3, 2, 2, 2, 3, 1, 3]
-dears	1.9	0.83066	[3, 2, 2, 2, 1, 2, 2, 2, 0, 3]
-dearth	-2.3	1.00499	[-2, -2, -1, -4, -2, -1, -2, -4, -3, -2]
-dearths	-0.9	0.7	[0, -1, 0, -1, -2, -1, -2, 0, -1, -1]
-deary	1.9	0.83066	[3, 2, 2, 1, 2, 2, 3, 2, 0, 2]
-death	-2.9	1.04403	[-3, -4, -4, -3, -3, -1, -1, -4, -3, -3]
-debonair	0.8	1.72047	[1, -1, -1, -3, 2, 2, 2, 2, 2, 2]
-debt	-1.5	1.0247	[-2, -1, -2, -3, 1, -2, -2, -1, -1, -2]
-decay	-1.7	0.45826	[-2, -2, -2, -1, -2, -1, -1, -2, -2, -2]
-decayed	-1.6	0.91652	[-2, -2, -2, -2, -2, 1, -1, -2, -2, -2]
-decayer	-1.6	0.4899	[-2, -2, -2, -1, -2, -1, -1, -1, -2, -2]
-decayers	-1.6	0.4899	[-2, -1, -1, -2, -1, -2, -2, -2, -1, -2]
-decaying	-1.7	0.64031	[-1, -1, -2, -2, -1, -2, -3, -2, -2, -1]
-decays	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
-deceit	-2.0	1.34164	[-3, -2, -2, -3, -3, 0, 1, -2, -3, -3]
-deceitful	-1.9	1.22066	[-3, -2, -2, -3, -1, -3, -1, -3, -2, 1]
-deceive	-1.7	0.64031	[-1, -2, -2, -1, -2, -1, -1, -3, -2, -2]
-deceived	-1.9	1.3	[1, -3, -3, -1, -1, -2, -2, -2, -4, -2]
-deceives	-1.6	1.56205	[-1, 2, -2, -2, -3, -2, 0, -2, -4, -2]
-deceiving	-1.4	1.68523	[-3, -2, -2, -2, -1, -1, 1, -4, 2, -2]
-deception	-1.9	1.04403	[-1, -2, -2, -4, -2, 0, -2, -1, -3, -2]
-decisive	0.9	0.83066	[2, 2, 0, 1, -1, 1, 1, 1, 1, 1]
-dedicated	2.0	0.44721	[2, 2, 2, 2, 2, 2, 2, 1, 3, 2]
-defeat	-2.0	1.67332	[0, -4, -3, -4, -2, -1, -2, -1, 1, -4]
-defeated	-2.1	0.83066	[-1, -2, -1, -2, -3, -2, -2, -2, -2, -4]
-defeater	-1.4	0.8	[-2, -1, -1, -3, -2, -1, -2, -1, 0, -1]
-defeaters	-0.9	0.9434	[-2, 0, -1, -2, -2, -1, 0, -1, 1, -1]
-defeating	-1.6	0.66332	[-2, -2, -1, -1, -1, -1, -2, -2, -3, -1]
-defeatism	-1.3	1.00499	[-1, -2, -2, -1, -1, -3, 1, -2, -1, -1]
-defeatist	-1.7	0.9	[0, -1, -2, -3, -1, -2, -1, -3, -2, -2]
-defeatists	-2.1	0.9434	[-3, -2, -1, -2, -2, -1, -3, -4, -1, -2]
-defeats	-1.3	1.1	[-1, 0, -1, -2, -1, -2, -3, 1, -2, -2]
-defeature	-1.9	1.22066	[1, -2, -2, -2, -2, -1, -2, -3, -4, -2]
-defeatures	-1.5	1.20416	[-3, -2, -3, 0, -1, -1, -2, 0, -3, 0]
-defect	-1.4	0.8	[-2, -1, -2, -1, 0, -2, -3, -1, -1, -1]
-defected	-1.7	0.64031	[-3, -2, -2, -2, -1, -1, -1, -2, -1, -2]
-defecting	-1.8	0.6	[-2, -1, -2, -2, -2, -1, -3, -1, -2, -2]
-defection	-1.4	0.66332	[-1, -2, -1, -2, 0, -1, -2, -2, -2, -1]
-defections	-1.5	0.67082	[-2, -2, -2, -1, 0, -1, -2, -2, -1, -2]
-defective	-1.9	0.53852	[-2, -1, -2, -3, -2, -2, -2, -2, -1, -2]
-defectively	-2.1	0.83066	[-1, -3, -2, -1, -3, -2, -1, -3, -2, -3]
-defectiveness	-1.8	0.74833	[-1, -1, -2, -2, -2, -3, -1, -1, -2, -3]
-defectives	-1.8	0.74833	[-3, -3, -1, -2, -2, -1, -2, -1, -1, -2]
-defector	-1.9	0.53852	[-2, -3, -2, -2, -1, -2, -1, -2, -2, -2]
-defectors	-1.3	1.26886	[-2, -1, -2, 0, -1, -1, -2, -4, 1, -1]
-defects	-1.7	0.9	[-1, -2, -1, 0, -2, -3, -2, -2, -1, -3]
-defence	0.4	0.91652	[0, 0, 0, 1, 0, 0, 0, 2, 2, -1]
-defenceman	0.4	1.11355	[3, 0, 0, 0, 0, -1, 2, 0, 0, 0]
-defencemen	0.6	0.91652	[0, 0, 0, 2, 0, 2, 0, 2, 0, 0]
-defences	-0.2	1.16619	[0, 0, 0, 1, -2, -1, 0, -2, 0, 2]
-defender	0.4	1.0198	[0, 0, 2, 1, -1, 2, 0, 1, -1, 0]
-defenders	0.3	0.78102	[0, 1, 1, 0, 0, 0, 0, -1, 2, 0]
-defense	0.5	0.67082	[0, 1, 0, 1, 2, 1, 0, 0, 0, 0]
-defenseless	-1.4	0.8	[0, -1, -1, -2, -1, -1, -3, -1, -2, -2]
-defenselessly	-1.1	0.9434	[-2, -2, -2, -1, 0, -1, 1, -1, -1, -2]
-defenselessness	-1.3	1.18743	[-3, -1, -3, 0, -2, -1, -1, -2, 1, -1]
-defenseman	0.1	1.13578	[2, 0, 0, 0, 0, 0, -1, 0, 2, -2]
-defensemen	-0.4	0.66332	[0, 0, -2, 0, -1, -1, 0, 0, 0, 0]
-defenses	0.7	1.41774	[3, 0, 2, 0, -1, 1, -2, 1, 1, 2]
-defensibility	0.4	1.56205	[1, -2, 1, 0, 4, 0, -1, 1, -1, 1]
-defensible	0.8	0.87178	[0, 2, 0, 0, 1, 0, 2, 0, 2, 1]
-defensibly	0.1	1.13578	[0, -1, 0, 0, -1, 0, 3, 0, -1, 1]
-defensive	0.1	1.13578	[2, -1, 0, -1, 2, 0, -1, 1, 0, -1]
-defensively	-0.6	0.91652	[1, 1, -1, -1, -1, -1, -2, -1, 0, -1]
-defensiveness	-0.4	1.11355	[2, -1, -1, -1, -1, 0, 0, 1, -2, -1]
-defensives	-0.3	1.00499	[-1, 0, 0, -1, 0, -1, 0, -2, 2, 0]
-defer	-1.2	0.6	[-1, -2, -1, 0, -1, -2, -2, -1, -1, -1]
-deferring	-0.7	0.64031	[0, 0, -2, -1, -1, -1, -1, 0, -1, 0]
-defiant	-0.9	1.44568	[-1, -2, -1, 2, 1, -2, 0, -1, -3, -2]
-deficit	-1.7	0.78102	[-3, -3, -2, -1, -2, -2, -1, -1, -1, -1]
-definite	1.1	0.7	[2, 1, 0, 1, 0, 1, 1, 2, 2, 1]
-definitely	1.7	0.64031	[2, 2, 2, 2, 2, 1, 2, 2, 0, 2]
-degradable	-1.0	1.26491	[-1, -2, 0, -2, 0, -1, -2, -2, 2, -2]
-degradation	-2.4	1.0198	[-4, -3, -3, -3, -3, -2, -2, -2, 0, -2]
-degradations	-1.5	0.67082	[-2, -1, -3, -1, -2, -2, -1, -1, -1, -1]
-degradative	-2.0	0.63246	[-2, -1, -3, -2, -2, -2, -1, -2, -3, -2]
-degrade	-1.9	0.7	[-3, -2, -1, -3, -1, -2, -2, -2, -1, -2]
-degraded	-1.8	0.87178	[-2, -3, -1, 0, -2, -1, -2, -2, -3, -2]
-degrader	-2.0	0.63246	[-2, -3, -1, -1, -2, -2, -3, -2, -2, -2]
-degraders	-2.0	0.63246	[-2, -3, -1, -2, -2, -2, -3, -2, -1, -2]
-degrades	-2.1	0.83066	[-3, -1, -3, -3, -2, -3, -1, -1, -2, -2]
-degrading	-2.8	0.87178	[-3, -3, -2, -3, -4, -2, -3, -4, -3, -1]
-degradingly	-2.7	0.64031	[-3, -2, -3, -4, -2, -3, -3, -2, -3, -2]
-dehumanize	-1.8	2.18174	[-2, -4, -1, -3, 2, -4, -3, 2, -1, -4]
-dehumanized	-1.9	0.7	[-2, -2, -2, -2, -1, -3, -2, -1, -3, -1]
-dehumanizes	-1.5	0.67082	[-1, -1, -1, -2, -1, -3, -2, -1, -2, -1]
-dehumanizing	-2.4	0.91652	[-2, -3, -4, -2, -3, -2, -3, -1, -1, -3]
-deject	-2.2	0.6	[-2, -3, -2, -3, -2, -2, -3, -2, -1, -2]
-dejected	-2.2	0.74833	[-2, -1, -2, -3, -2, -2, -2, -2, -2, -4]
-dejecting	-2.3	0.64031	[-2, -2, -3, -2, -3, -2, -1, -2, -3, -3]
-dejects	-2.0	0.63246	[-2, -2, -3, -1, -2, -1, -3, -2, -2, -2]
-delay	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -2, -1, -2, -1]
-delayed	-0.9	0.3	[-1, -1, 0, -1, -1, -1, -1, -1, -1, -1]
-delectable	2.9	0.83066	[3, 4, 3, 2, 3, 4, 3, 1, 3, 3]
-delectables	1.4	1.35647	[1, 2, 0, 4, 2, 1, 3, -1, 1, 1]
-delectably	2.8	0.74833	[3, 4, 3, 2, 3, 3, 3, 1, 3, 3]
-delicate	0.2	0.74833	[2, 0, 0, 0, 0, 0, 1, 0, -1, 0]
-delicately	1.0	1.26491	[1, 1, 2, 0, 1, 3, -1, 2, -1, 2]
-delicates	0.6	1.35647	[3, 0, 2, 1, -1, -1, 2, 0, 1, -1]
-delicatessen	0.4	0.8	[0, 0, 0, 0, 0, 0, 0, 2, 2, 0]
-delicatessens	0.4	0.8	[0, 0, 2, 0, 0, 2, 0, 0, 0, 0]
-delicious	2.7	0.64031	[3, 2, 3, 4, 2, 3, 3, 3, 2, 2]
-deliciously	1.9	0.83066	[2, 2, 1, 3, 1, 3, 2, 3, 1, 1]
-deliciousness	1.8	0.87178	[1, 2, 3, 3, 2, 2, 1, 2, 2, 0]
-delight	2.9	0.7	[2, 3, 4, 4, 3, 2, 3, 3, 2, 3]
-delighted	2.3	0.64031	[3, 3, 2, 3, 2, 1, 3, 2, 2, 2]
-delightedly	2.4	0.4899	[2, 3, 3, 3, 2, 2, 3, 2, 2, 2]
-delightedness	2.1	0.53852	[2, 2, 2, 2, 3, 2, 3, 2, 1, 2]
-delighter	2.0	0.63246	[3, 2, 2, 3, 1, 2, 2, 1, 2, 2]
-delighters	2.6	0.66332	[3, 2, 2, 2, 3, 2, 3, 2, 4, 3]
-delightful	2.8	0.6	[4, 3, 2, 3, 3, 3, 2, 2, 3, 3]
-delightfully	2.7	0.45826	[3, 2, 2, 2, 3, 3, 3, 3, 3, 3]
-delightfulness	2.1	0.7	[3, 2, 3, 1, 2, 3, 2, 2, 2, 1]
-delighting	1.6	1.90788	[3, 3, 3, 2, 3, 2, 3, -2, -2, 1]
-delights	2.0	1.54919	[2, 3, 1, -2, 2, 4, 2, 3, 3, 2]
-delightsome	2.3	0.45826	[3, 3, 2, 2, 2, 3, 2, 2, 2, 2]
-demand	-0.5	0.67082	[0, 0, 0, 0, 0, -1, -1, -1, 0, -2]
-demanded	-0.9	0.7	[-2, 0, 0, 0, -2, -1, -1, -1, -1, -1]
-demanding	-0.9	0.53852	[-1, -2, 0, -1, -1, -1, -1, -1, 0, -1]
-demonstration	0.4	0.91652	[0, 0, 0, 0, 0, 0, 3, 1, 0, 0]
-demoralized	-1.6	1.62481	[-2, -2, -2, -2, -3, 2, -2, -3, 1, -3]
-denied	-1.9	0.53852	[-2, -3, -1, -2, -2, -1, -2, -2, -2, -2]
-denier	-1.5	0.67082	[-1, -1, -1, -1, -2, -3, -2, -2, -1, -1]
-deniers	-1.1	1.13578	[-2, 0, -2, -1, -3, 1, 0, -1, -2, -1]
-denies	-1.8	0.6	[-1, -2, -1, -1, -2, -3, -2, -2, -2, -2]
-denounce	-1.4	0.91652	[-2, -1, -2, -1, 1, -2, -2, -1, -2, -2]
-denounces	-1.9	0.7	[-1, -3, -2, -3, -2, -1, -2, -2, -2, -1]
-deny	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -2, -1, -2]
-denying	-1.4	0.4899	[-1, -1, -1, -2, -2, -2, -1, -2, -1, -1]
-depress	-2.2	0.74833	[-2, -1, -3, -3, -2, -2, -3, -3, -1, -2]
-depressant	-1.6	1.11355	[-3, -1, 0, -1, 0, -2, -3, -1, -3, -2]
-depressants	-1.6	0.91652	[-1, -1, -3, -3, -2, 0, -1, -2, -2, -1]
-depressed	-2.3	0.45826	[-2, -2, -2, -2, -2, -3, -3, -3, -2, -2]
-depresses	-2.2	0.6	[-2, -2, -2, -2, -3, -3, -1, -2, -3, -2]
-depressible	-1.7	0.78102	[-2, -1, 0, -3, -2, -2, -2, -1, -2, -2]
-depressing	-1.6	1.28062	[-2, -2, -2, 2, -3, -1, -2, -2, -2, -2]
-depressingly	-2.3	0.45826	[-2, -3, -2, -2, -2, -3, -3, -2, -2, -2]
-depression	-2.7	0.64031	[-3, -2, -2, -2, -2, -3, -4, -3, -3, -3]
-depressions	-2.2	0.6	[-2, -3, -3, -2, -2, -2, -3, -2, -2, -1]
-depressive	-1.6	1.11355	[-2, -1, -1, -2, -1, -2, -3, 1, -3, -2]
-depressively	-2.1	0.53852	[-3, -2, -3, -2, -2, -2, -2, -1, -2, -2]
-depressives	-1.5	0.5	[-2, -1, -1, -2, -1, -1, -1, -2, -2, -2]
-depressor	-1.8	1.16619	[-2, -4, -3, 0, 0, -2, -2, -2, -1, -2]
-depressors	-1.7	0.9	[-1, -1, -1, -2, -1, -2, -4, -2, -2, -1]
-depressurization	-0.3	0.78102	[1, 0, 0, -1, -1, 0, -2, 0, 0, 0]
-depressurizations	-0.4	0.91652	[0, 0, 0, 0, 1, -2, -1, 0, -2, 0]
-depressurize	-0.5	0.80623	[0, 0, -2, 0, -2, 0, 0, 0, 0, -1]
-depressurized	-0.3	0.64031	[0, 0, 0, 0, 0, 0, -1, 0, -2, 0]
-depressurizes	-0.3	0.64031	[0, 0, 0, 0, 0, 0, -1, 0, -2, 0]
-depressurizing	-0.7	1.34536	[2, 0, -1, -1, -2, -2, 1, -2, 0, -2]
-deprival	-2.1	0.7	[-1, -2, -2, -2, -1, -3, -3, -3, -2, -2]
-deprivals	-1.2	0.87178	[0, -1, -2, -1, 0, -2, -1, -1, -3, -1]
-deprivation	-1.8	1.4	[-3, -2, -3, -2, -1, -2, -2, 2, -2, -3]
-deprivations	-1.8	0.74833	[-1, -2, -3, -1, -2, -1, -2, -2, -3, -1]
-deprive	-2.1	0.7	[-3, -2, -1, -3, -1, -2, -2, -3, -2, -2]
-deprived	-2.1	0.7	[-2, -2, -2, -2, -2, -4, -2, -2, -1, -2]
-depriver	-1.6	0.91652	[-1, -2, -1, -2, -1, -4, -2, -1, -1, -1]
-deprivers	-1.4	0.66332	[-2, -1, -1, -3, -1, -1, -1, -1, -2, -1]
-deprives	-1.7	0.64031	[-2, -2, -1, -2, -1, -3, -2, -1, -1, -2]
-depriving	-2.0	0.0	[-2, -2, -2, -2, -2, -2, -2, -2, -2, -2]
-derail	-1.2	1.07703	[-1, 1, -1, -2, -1, -2, -1, -3, -2, 0]
-derailed	-1.4	0.66332	[-1, -2, -2, 0, -1, -1, -2, -1, -2, -2]
-derails	-1.3	0.78102	[-2, -3, -1, -2, -1, -1, 0, -1, -1, -1]
-deride	-1.1	1.22066	[-3, -2, -2, -1, -1, -1, 1, -2, -1, 1]
-derided	-0.8	0.87178	[-2, -1, -2, 0, 0, -1, -1, -1, 1, -1]
-derides	-1.0	1.0	[-1, -2, -2, 0, 0, 1, -1, -2, -1, -2]
-deriding	-1.5	0.80623	[-2, -2, 0, 0, -2, -1, -2, -2, -2, -2]
-derision	-1.2	1.249	[-1, -2, -2, -2, -1, -1, 1, 1, -3, -2]
-desirable	1.3	0.45826	[2, 1, 1, 1, 1, 1, 1, 2, 2, 1]
-desire	1.7	0.78102	[1, 1, 2, 1, 3, 3, 1, 2, 2, 1]
-desired	1.1	1.04403	[1, 1, 0, 3, 1, 0, 1, 1, 3, 0]
-desirous	1.3	0.64031	[1, 2, 1, 2, 2, 1, 2, 1, 0, 1]
-despair	-1.3	1.9	[2, -1, -3, -1, -3, 1, -3, 1, -3, -3]
-despaired	-2.7	0.45826	[-2, -2, -3, -3, -3, -3, -3, -2, -3, -3]
-despairer	-1.3	1.1	[-2, -2, -1, -3, -2, 1, -1, -1, 0, -2]
-despairers	-1.3	1.00499	[-2, -1, -1, 1, -2, -1, -2, -1, -1, -3]
-despairing	-2.3	0.64031	[-2, -1, -3, -2, -3, -2, -2, -2, -3, -3]
-despairingly	-2.2	0.74833	[-2, -2, -2, -2, -4, -2, -3, -1, -2, -2]
-despairs	-2.7	1.00499	[-3, -4, -1, -3, -4, -2, -1, -3, -3, -3]
-desperate	-1.3	1.34536	[-2, -1, -2, 1, -1, -2, -3, -3, -1, 1]
-desperately	-1.6	1.11355	[-3, -3, -2, -1, -2, -1, -2, -2, -1, 1]
-desperateness	-1.5	1.36015	[-1, -2, -2, -2, -3, -3, 1, -2, 1, -2]
-desperation	-2.0	1.0	[-2, -1, -1, -2, -3, -3, -1, -4, -1, -2]
-desperations	-2.2	1.66132	[-1, -4, -2, -4, -4, -1, -1, -2, 1, -4]
-despise	-1.4	1.35647	[-2, -3, -1, -2, -1, 1, -3, 1, -2, -2]
-despised	-1.7	1.48661	[-2, -1, -3, -2, -3, 1, -3, 1, -2, -3]
-despisement	-2.4	0.91652	[-3, -3, -2, -1, -3, -1, -4, -2, -2, -3]
-despisements	-2.5	1.0247	[-2, -2, -3, -2, 0, -3, -4, -3, -3, -3]
-despiser	-1.8	1.07703	[-2, -1, -3, 1, -2, -2, -3, -2, -2, -2]
-despisers	-1.6	1.35647	[-3, -3, -1, -3, -2, -1, -1, 1, 0, -3]
-despises	-2.0	1.26491	[-3, -1, -3, 1, -2, -1, -3, -2, -3, -3]
-despising	-2.7	0.9	[-4, -3, -3, -4, -1, -2, -3, -2, -2, -3]
-despondent	-2.1	0.53852	[-2, -2, -2, -3, -2, -2, -1, -3, -2, -2]
-destroy	-2.5	0.67082	[-2, -3, -3, -1, -3, -3, -3, -2, -2, -3]
-destroyed	-2.2	0.87178	[-1, -3, -3, -2, -1, -2, -1, -3, -3, -3]
-destroyer	-2.0	0.89443	[-2, -3, -3, -3, -1, -2, -2, -2, 0, -2]
-destroyers	-2.3	0.78102	[-1, -3, -3, -3, -2, -2, -3, -3, -1, -2]
-destroying	-2.6	0.91652	[-2, -4, -4, -2, -1, -3, -2, -3, -2, -3]
-destroys	-2.6	0.4899	[-3, -3, -3, -2, -2, -2, -3, -3, -2, -3]
-destruct	-2.4	0.4899	[-3, -3, -3, -2, -2, -2, -3, -2, -2, -2]
-destructed	-1.9	1.04403	[-4, -1, -2, -2, -2, -1, -3, -2, 0, -2]
-destructibility	-1.8	1.07703	[-1, -2, -1, -1, -2, -3, -2, 0, -4, -2]
-destructible	-1.5	1.11803	[-2, -2, -2, -1, 1, -1, -3, -1, -3, -1]
-destructing	-2.5	0.67082	[-2, -3, -2, -3, -2, -2, -2, -3, -2, -4]
-destruction	-2.7	0.9	[-4, -3, -4, -3, -2, -2, -3, -1, -2, -3]
-destructionist	-2.6	0.8	[-3, -4, -2, -2, -2, -3, -3, -1, -3, -3]
-destructionists	-2.1	0.53852	[-3, -1, -2, -2, -3, -2, -2, -2, -2, -2]
-destructions	-2.3	0.78102	[-3, -2, -2, -2, -1, -3, -4, -2, -2, -2]
-destructive	-3.0	0.63246	[-3, -4, -3, -2, -3, -3, -3, -2, -4, -3]
-destructively	-2.4	0.91652	[-2, -3, -1, -4, -2, -3, -3, -3, -1, -2]
-destructiveness	-2.4	0.91652	[-3, -3, -2, -4, -1, -2, -3, -2, -1, -3]
-destructivity	-2.2	1.53623	[2, -3, -3, -4, -3, -2, -2, -2, -2, -3]
-destructs	-2.4	0.91652	[-2, -1, -2, -4, -4, -2, -3, -2, -2, -2]
-detached	-0.5	1.20416	[-1, 2, -1, -1, -2, 0, 1, -2, -1, 0]
-detain	-1.8	0.9798	[-3, -1, -2, -2, -4, -2, -1, -1, -1, -1]
-detained	-1.7	0.9	[-1, -1, -1, -1, -1, -2, -2, -2, -2, -4]
-detention	-1.5	0.67082	[-1, -2, -1, -2, -1, -1, -3, -2, -1, -1]
-determinable	0.9	0.7	[2, 1, 1, 1, 0, 1, 2, 0, 0, 1]
-determinableness	0.2	1.07703	[0, 0, 0, 1, 0, 1, -1, 2, -2, 1]
-determinably	0.9	0.83066	[2, 0, 1, 1, 0, 1, 2, 2, 0, 0]
-determinacy	1.0	1.0	[0, 0, 0, 3, 1, 1, 2, 1, 0, 2]
-determinant	0.2	0.6	[0, 1, -1, 0, 1, 1, 0, 0, 0, 0]
-determinantal	-0.3	1.41774	[0, 0, 0, -4, 0, -1, 0, 0, 2, 0]
-determinate	0.8	0.87178	[2, 1, 0, 0, 0, 2, 2, 0, 1, 0]
-determinately	1.2	0.6	[1, 2, 0, 1, 1, 1, 2, 1, 2, 1]
-determinateness	1.1	0.9434	[1, 1, 1, 0, 0, 2, 3, 1, 0, 2]
-determination	1.7	0.78102	[2, 3, 1, 1, 1, 2, 1, 1, 2, 3]
-determinations	0.8	1.16619	[0, 3, 1, 0, 1, 3, 0, 0, 0, 0]
-determinative	1.1	1.04403	[2, 0, 3, 2, 1, 1, 0, 0, 2, 0]
-determinatives	0.9	1.3	[2, 0, -2, 1, 2, 2, 2, 0, 0, 2]
-determinator	1.1	1.04403	[3, 0, 1, 0, 1, 0, 2, 2, 0, 2]
-determined	1.4	1.35647	[-2, 1, 3, 2, 2, 2, 3, 1, 1, 1]
-devastate	-3.1	0.9434	[-4, -4, -1, -4, -4, -3, -3, -3, -2, -3]
-devastated	-3.0	0.89443	[-4, -3, -3, -4, -3, -1, -3, -4, -3, -2]
-devastates	-2.8	0.9798	[-4, -3, -2, -4, -2, -1, -3, -4, -3, -2]
-devastating	-3.3	0.9	[-4, -3, -4, -4, -1, -4, -3, -3, -3, -4]
-devastatingly	-2.4	1.28062	[-3, -4, -3, 0, -3, 0, -2, -3, -3, -3]
-devastation	-1.8	2.13542	[-1, -1, -3, -3, -4, -3, -4, 2, 2, -3]
-devastations	-1.9	1.92094	[-3, -3, -2, -2, 1, -1, 2, -4, -4, -3]
-devastative	-3.2	1.16619	[-4, -3, 0, -4, -4, -3, -3, -4, -3, -4]
-devastator	-2.8	0.74833	[-3, -3, -2, -2, -3, -2, -3, -4, -2, -4]
-devastators	-2.9	1.22066	[-3, -2, -3, -4, -4, -4, 0, -3, -2, -4]
-devil	-3.4	0.8	[-4, -3, -4, -4, -4, -4, -2, -3, -2, -4]
-deviled	-1.6	1.0198	[-1, -2, 0, -4, -1, -2, -2, -2, -1, -1]
-devilfish	-0.8	1.07703	[-2, -3, -1, 0, 0, 0, 0, -2, 0, 0]
-devilfishes	-0.6	1.0198	[-3, 0, -2, 0, 0, 0, 0, -1, 0, 0]
-deviling	-2.2	0.87178	[-1, -3, -1, -2, -3, -2, -2, -4, -2, -2]
-devilish	-2.1	1.04403	[-1, -2, -4, -1, -1, -2, -2, -4, -2, -2]
-devilishly	-1.6	0.8	[-2, -2, -3, -1, -2, -2, 0, -2, -1, -1]
-devilishness	-2.3	0.9	[-4, -1, -4, -2, -2, -2, -2, -2, -2, -2]
-devilkin	-2.4	0.91652	[-3, -1, -2, -3, -2, -4, -2, -3, -3, -1]
-devilled	-2.3	1.1	[-3, -1, -2, -3, 0, -4, -2, -3, -2, -3]
-devilling	-1.8	1.249	[-3, -1, -1, -2, -2, -3, -4, -2, 0, 0]
-devilment	-1.9	0.9434	[-2, -1, -2, -1, -3, -2, -2, -1, -1, -4]
-devilments	-1.1	0.7	[-2, -1, -2, -2, -1, 0, 0, -1, -1, -1]
-devilries	-1.6	1.35647	[-1, -1, -2, -4, -3, 0, -2, 0, 0, -3]
-devilry	-2.8	1.249	[-4, -3, 0, -2, -2, -2, -3, -4, -4, -4]
-devils	-2.7	0.9	[-3, -1, -3, -2, -2, -3, -4, -3, -2, -4]
-deviltries	-1.5	1.11803	[-1, -2, 1, -2, 0, -2, -2, -3, -2, -2]
-deviltry	-2.8	1.32665	[-4, -4, -3, -3, -3, -3, 1, -3, -3, -3]
-devilwood	-0.8	1.07703	[0, -1, -2, 0, 0, 0, 0, -3, -2, 0]
-devilwoods	-1.0	0.7746	[-2, 0, -2, -1, -1, 0, -1, -2, 0, -1]
-devote	1.4	1.28062	[3, 0, 2, -1, 0, 3, 2, 2, 1, 2]
-devoted	1.7	1.34536	[2, -1, 3, 2, 1, 0, 1, 3, 3, 3]
-devotedly	1.6	1.35647	[1, 1, 2, 2, 3, 2, 2, -2, 2, 3]
-devotedness	2.0	1.0	[0, 3, 2, 1, 3, 2, 2, 3, 1, 3]
-devotee	1.6	1.11355	[1, 3, 0, 2, 1, 2, 1, 1, 4, 1]
-devotees	0.5	1.0247	[0, 0, 3, 0, 0, 0, 2, 0, 0, 0]
-devotement	1.5	1.36015	[2, -1, 3, 2, -1, 1, 2, 3, 2, 2]
-devotements	1.1	1.04403	[0, 1, 0, 0, 0, 2, 2, 2, 3, 1]
-devotes	1.6	0.91652	[2, 3, 0, 2, 2, 3, 1, 1, 1, 1]
-devoting	2.1	0.7	[2, 2, 3, 1, 2, 3, 2, 3, 1, 2]
-devotion	2.0	1.0	[2, 0, 1, 2, 4, 3, 2, 2, 2, 2]
-devotional	1.2	1.16619	[0, 1, 0, 2, 2, 1, 0, 0, 3, 3]
-devotionally	2.2	0.4	[2, 2, 2, 3, 2, 3, 2, 2, 2, 2]
-devotionals	1.2	1.07703	[3, 1, 1, 0, -1, 2, 2, 2, 1, 1]
-devotions	1.8	0.74833	[2, 3, 1, 2, 1, 3, 1, 2, 1, 2]
-diamond	1.4	1.42829	[0, 0, 2, 0, 1, 3, 1, 3, 0, 4]
-dick	-2.3	1.18743	[-2, -3, -4, -2, 0, -4, -2, -1, -3, -2]
-dickhead	-3.1	0.53852	[-4, -3, -3, -3, -4, -2, -3, -3, -3, -3]
-die	-2.9	0.9434	[-4, -3, -1, -2, -4, -3, -3, -3, -2, -4]
-died	-2.6	1.28062	[-3, -1, -3, -4, -2, -4, -3, -4, -2, 0]
-difficult	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -1, -2]
-difficulties	-1.2	0.4	[-1, -2, -1, -1, -1, -2, -1, -1, -1, -1]
-difficultly	-1.7	0.45826	[-1, -2, -1, -2, -2, -1, -2, -2, -2, -2]
-difficulty	-1.4	0.66332	[-2, -2, -2, -2, 0, -1, -1, -2, -1, -1]
-diffident	-1.0	0.44721	[-1, -1, -1, -1, -1, 0, -2, -1, -1, -1]
-dignified	2.2	0.6	[1, 2, 2, 2, 3, 3, 3, 2, 2, 2]
-dignifies	2.0	0.7746	[1, 3, 2, 2, 3, 3, 2, 2, 1, 1]
-dignify	1.8	0.74833	[1, 2, 2, 1, 3, 3, 1, 2, 2, 1]
-dignifying	2.1	1.04403	[1, 1, 1, 3, 1, 4, 2, 3, 2, 3]
-dignitaries	0.6	0.91652	[0, 0, 1, 0, 0, 0, 3, 0, 1, 1]
-dignitary	1.9	1.3	[0, 3, 4, 2, 3, 1, 1, 3, 0, 2]
-dignities	1.4	0.66332	[1, 2, 1, 1, 3, 2, 1, 1, 1, 1]
-dignity	1.7	0.9	[0, 3, 2, 1, 2, 1, 2, 3, 1, 2]
-dilemma	-0.7	1.48661	[2, -1, -2, -2, -1, -1, 2, 0, -2, -2]
-dipshit	-2.1	0.7	[-1, -2, -2, -3, -2, -3, -3, -2, -2, -1]
-dire	-2.0	1.26491	[-2, -3, -3, -2, -3, -1, -1, 1, -3, -3]
-direful	-3.1	0.83066	[-3, -3, -3, -3, -4, -1, -4, -3, -4, -3]
-dirt	-1.4	0.91652	[-1, -1, -1, 0, -3, -1, -1, -2, -3, -1]
-dirtier	-1.4	0.4899	[-2, -1, -1, -2, -1, -2, -1, -1, -2, -1]
-dirtiest	-2.4	1.0198	[-4, -3, -2, -1, -2, -3, -1, -2, -4, -2]
-dirty	-1.9	0.83066	[-2, -1, -1, -1, -2, -2, -1, -3, -3, -3]
-disabling	-2.1	0.53852	[-2, -1, -3, -3, -2, -2, -2, -2, -2, -2]
-disadvantage	-1.8	0.4	[-2, -2, -1, -2, -2, -1, -2, -2, -2, -2]
-disadvantaged	-1.7	0.64031	[-2, -2, -3, -1, -2, -2, -2, -1, -1, -1]
-disadvantageous	-1.8	0.74833	[-1, -2, -2, -1, -3, -1, -1, -2, -3, -2]
-disadvantageously	-2.1	0.83066	[-2, -4, -1, -2, -1, -2, -2, -2, -3, -2]
-disadvantageousness	-1.6	0.66332	[-1, -1, -3, -2, -1, -1, -2, -1, -2, -2]
-disadvantages	-1.7	0.64031	[-2, -2, -3, -1, -2, -2, -2, -1, -1, -1]
-disagree	-1.6	0.4899	[-1, -2, -1, -1, -2, -2, -2, -2, -1, -2]
-disagreeable	-1.7	0.64031	[-1, -2, -1, -1, -1, -2, -2, -2, -3, -2]
-disagreeableness	-1.7	0.64031	[-1, -1, -2, -2, -1, -2, -3, -1, -2, -2]
-disagreeablenesses	-1.9	0.9434	[-2, 0, -3, -1, -2, -3, -2, -1, -3, -2]
-disagreeably	-1.5	0.67082	[-3, -2, -1, -1, -1, -2, -1, -2, -1, -1]
-disagreed	-1.3	0.64031	[-1, -2, -1, -1, -2, 0, -1, -2, -1, -2]
-disagreeing	-1.4	0.8	[-1, 0, -1, -2, -2, -1, -3, -1, -1, -2]
-disagreement	-1.5	0.67082	[-2, -1, -1, -1, -1, -1, -1, -3, -2, -2]
-disagreements	-1.8	0.6	[-2, -3, -1, -2, -2, -1, -2, -2, -1, -2]
-disagrees	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -2, -1, -2]
-disappear	-0.9	0.7	[-2, -1, 0, 0, -2, -1, -1, -1, 0, -1]
-disappeared	-0.9	0.7	[-2, 0, -1, -1, 0, 0, -2, -1, -1, -1]
-disappears	-1.4	0.8	[-2, -2, 0, 0, -2, -1, -2, -1, -2, -2]
-disappoint	-1.7	0.64031	[-1, -1, -1, -3, -2, -2, -2, -1, -2, -2]
-disappointed	-2.1	0.83066	[-1, -3, -2, -2, -3, -1, -1, -2, -3, -3]
-disappointedly	-1.7	0.78102	[-3, -1, -3, -1, -2, -1, -1, -2, -2, -1]
-disappointing	-2.2	0.6	[-1, -2, -2, -3, -3, -2, -2, -2, -3, -2]
-disappointingly	-1.9	0.7	[-2, -1, -1, -3, -2, -3, -2, -2, -1, -2]
-disappointment	-2.3	1.00499	[-3, -1, -4, -1, -3, -1, -3, -2, -2, -3]
-disappointments	-2.0	1.09545	[-1, -2, -4, -3, -2, -2, -3, 0, -2, -1]
-disappoints	-1.6	0.4899	[-2, -1, -1, -1, -2, -1, -2, -2, -2, -2]
-disaster	-3.1	0.83066	[-2, -4, -4, -3, -3, -2, -4, -3, -2, -4]
-disasters	-2.6	0.8	[-2, -2, -3, -1, -3, -3, -2, -4, -3, -3]
-disastrous	-2.9	0.53852	[-2, -2, -3, -3, -3, -3, -4, -3, -3, -3]
-disbelieve	-1.2	0.87178	[-1, -2, -1, -2, -1, 0, 0, -1, -3, -1]
-discard	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -1, -2, -1]
-discarded	-1.4	0.91652	[-1, -1, -1, -1, 0, -1, -2, -3, -3, -1]
-discarding	-0.7	0.45826	[-1, 0, -1, -1, -1, 0, -1, 0, -1, -1]
-discards	-1.0	0.63246	[0, -1, -1, -1, -2, 0, -2, -1, -1, -1]
-discomfort	-1.8	0.6	[-2, -2, -2, -1, -1, -3, -2, -2, -1, -2]
-discomfortable	-1.6	0.8	[-1, -1, -1, -2, -3, -1, -2, -1, -3, -1]
-discomforted	-1.6	0.8	[-1, -1, -1, -2, -3, -3, -1, -1, -1, -2]
-discomforting	-1.6	1.11355	[-1, -2, -1, -1, -2, 1, -3, -2, -3, -2]
-discomforts	-1.3	0.9	[-2, -1, -2, -1, -1, -2, -2, -1, 1, -2]
-disconsolate	-2.3	0.78102	[-1, -2, -2, -3, -2, -2, -2, -4, -3, -2]
-disconsolation	-1.7	0.45826	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -2]
-discontented	-1.8	0.9798	[-1, -3, -1, -2, -4, -2, -1, -2, -1, -1]
-discord	-1.7	0.64031	[-3, -2, -2, -2, -2, -1, -1, -1, -1, -2]
-discounted	0.2	1.249	[-1, 0, 3, -1, 0, 1, 1, 1, -1, -1]
-discourage	-1.8	0.6	[-2, -2, -1, -2, -1, -1, -2, -2, -3, -2]
-discourageable	-1.2	0.9798	[-1, -2, -1, 1, -1, -1, -1, -2, -3, -1]
-discouraged	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -1, -1, -2, -2]
-discouragement	-2.0	0.89443	[-4, -1, -2, -2, -1, -1, -3, -2, -2, -2]
-discouragements	-1.8	0.6	[-2, -2, -2, -1, -1, -3, -2, -1, -2, -2]
-discourager	-1.7	0.78102	[-2, -1, -3, -2, -1, -3, -1, -2, -1, -1]
-discouragers	-1.9	0.53852	[-2, -2, -2, -2, -1, -1, -3, -2, -2, -2]
-discourages	-1.9	0.53852	[-2, -1, -2, -2, -2, -2, -1, -3, -2, -2]
-discouraging	-1.9	0.7	[-2, -2, -2, -3, -1, -1, -2, -1, -2, -3]
-discouragingly	-1.8	0.87178	[-2, -1, -3, -1, -1, -3, -2, -1, -3, -1]
-discredited	-1.9	0.53852	[-2, -2, -2, -2, -1, -3, -1, -2, -2, -2]
-disdain	-2.1	0.3	[-3, -2, -2, -2, -2, -2, -2, -2, -2, -2]
-disgrace	-2.2	0.74833	[-2, -4, -1, -2, -2, -2, -2, -3, -2, -2]
-disgraced	-2.0	0.44721	[-3, -2, -2, -2, -1, -2, -2, -2, -2, -2]
-disguise	-1.0	1.09545	[-2, -1, 0, 0, 0, 0, -3, -2, -2, 0]
-disguised	-1.1	1.04403	[-3, 0, 0, -1, -1, 0, -3, -1, -1, -1]
-disguises	-1.0	0.63246	[-2, 0, 0, -1, -1, -1, -2, -1, -1, -1]
-disguising	-1.3	0.78102	[0, -2, -1, -1, -1, -2, -1, -1, -3, -1]
-disgust	-2.9	0.7	[-3, -3, -4, -2, -3, -3, -4, -2, -3, -2]
-disgusted	-2.4	0.91652	[-4, -3, -3, -1, -3, -1, -2, -2, -2, -3]
-disgustedly	-3.0	0.89443	[-2, -3, -4, -4, -2, -4, -4, -2, -3, -2]
-disgustful	-2.6	0.4899	[-3, -3, -2, -2, -2, -2, -3, -3, -3, -3]
-disgusting	-2.4	1.11355	[-3, -2, -3, -4, -1, -3, -1, -4, -1, -2]
-disgustingly	-2.9	0.7	[-3, -3, -4, -3, -3, -2, -2, -4, -2, -3]
-disgusts	-2.1	0.53852	[-2, -2, -3, -2, -2, -2, -2, -3, -1, -2]
-dishearten	-2.0	0.63246	[-3, -1, -2, -3, -2, -2, -1, -2, -2, -2]
-disheartened	-2.2	0.74833	[-2, -2, -2, -1, -2, -2, -4, -3, -2, -2]
-disheartening	-1.8	1.32665	[-2, -2, -2, -3, -2, 2, -2, -2, -3, -2]
-dishearteningly	-2.0	0.63246	[-2, -3, -2, -1, -2, -2, -2, -3, -2, -1]
-disheartenment	-2.3	0.45826	[-3, -2, -3, -2, -2, -2, -2, -3, -2, -2]
-disheartenments	-2.2	0.87178	[-2, -3, -3, -3, -3, -1, -1, -1, -2, -3]
-disheartens	-2.2	0.4	[-3, -2, -2, -2, -3, -2, -2, -2, -2, -2]
-dishonest	-2.7	0.9	[-3, -2, -1, -4, -3, -2, -4, -3, -3, -2]
-disillusion	-1.0	1.18322	[-2, 0, -2, -1, -2, 1, -2, -1, 1, -2]
-disillusioned	-1.9	0.7	[-2, -2, -3, -2, -3, -1, -1, -1, -2, -2]
-disillusioning	-1.3	1.00499	[-2, -2, 1, -2, 0, -2, -2, -1, -1, -2]
-disillusionment	-1.7	0.78102	[-1, -3, -2, -3, -1, -2, -2, -1, -1, -1]
-disillusionments	-1.5	1.0247	[-2, 1, -3, -2, -1, -1, -2, -1, -2, -2]
-disillusions	-1.6	0.4899	[-2, -2, -2, -1, -1, -1, -2, -2, -1, -2]
-disinclined	-1.1	0.53852	[0, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-disjointed	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -2, -1, -1]
-dislike	-1.6	0.4899	[-2, -1, -1, -2, -2, -1, -2, -1, -2, -2]
-disliked	-1.7	0.64031	[-2, -3, -2, -1, -1, -1, -2, -2, -1, -2]
-dislikes	-1.7	0.78102	[-2, -2, -1, -1, -2, -1, -3, -3, -1, -1]
-disliking	-1.3	0.45826	[-1, -1, -2, -2, -2, -1, -1, -1, -1, -1]
-dismal	-3.0	1.0	[-2, -1, -4, -4, -3, -2, -3, -4, -4, -3]
-dismay	-1.8	0.87178	[-3, -1, -1, -3, -1, -1, -3, -1, -2, -2]
-dismayed	-1.9	0.9434	[-1, -2, -1, -3, -4, -1, -2, -2, -1, -2]
-dismaying	-2.2	0.9798	[-2, -3, -2, -3, -3, 0, -2, -1, -3, -3]
-dismayingly	-1.9	0.83066	[-2, -3, -2, -3, -2, -1, -2, -2, 0, -2]
-dismays	-1.8	1.07703	[-1, -1, -4, -3, -2, -1, -2, 0, -2, -2]
-disorder	-1.7	0.64031	[-2, -1, -1, -2, -2, -1, -3, -1, -2, -2]
-disorganized	-1.2	0.4	[-1, -1, -1, -1, -1, -2, -1, -2, -1, -1]
-disoriented	-1.5	0.67082	[-2, -2, -1, 0, -1, -2, -2, -1, -2, -2]
-disparage	-2.0	0.44721	[-2, -2, -2, -1, -2, -2, -2, -3, -2, -2]
-disparaged	-1.4	0.8	[-1, -2, -2, -3, -1, -1, -1, -2, 0, -1]
-disparages	-1.6	0.8	[-1, -2, -3, -2, -1, -1, -2, -2, 0, -2]
-disparaging	-2.2	0.6	[-3, -1, -2, -2, -2, -3, -3, -2, -2, -2]
-displeased	-1.9	0.7	[-3, -2, -1, -1, -3, -2, -2, -1, -2, -2]
-dispute	-1.7	0.78102	[-1, -3, -1, -1, -2, -1, -2, -2, -3, -1]
-disputed	-1.4	0.66332	[-2, -2, -2, -2, 0, -1, -1, -1, -1, -2]
-disputes	-1.1	1.64012	[-2, -2, -2, 2, -3, -1, -2, 2, -1, -2]
-disputing	-1.7	0.64031	[-2, -2, -2, -2, -1, -1, -3, -1, -1, -2]
-disqualified	-1.8	0.6	[-1, -2, -1, -2, -1, -2, -2, -3, -2, -2]
-disquiet	-1.3	0.9	[-1, -2, -2, -1, -1, -1, 1, -2, -2, -2]
-disregard	-1.1	0.53852	[-1, -1, -2, -1, -1, -2, -1, -1, 0, -1]
-disregarded	-1.6	0.4899	[-1, -1, -2, -2, -2, -2, -1, -2, -1, -2]
-disregarding	-0.9	0.53852	[-1, 0, -1, 0, -2, -1, -1, -1, -1, -1]
-disregards	-1.4	0.4899	[-1, -1, -2, -1, -2, -2, -2, -1, -1, -1]
-disrespect	-1.8	0.6	[-2, -2, -2, -1, -2, -2, -1, -3, -1, -2]
-disrespected	-2.0	0.63246	[-2, -2, -2, -2, -2, -3, -3, -1, -1, -2]
-disruption	-1.5	0.67082	[-1, -1, -1, -2, -1, -3, -2, -2, -1, -1]
-disruptions	-1.4	0.4899	[-1, -2, -1, -1, -1, -2, -2, -2, -1, -1]
-disruptive	-1.3	1.00499	[-4, 0, -1, -1, -1, -1, -1, -1, -2, -1]
-dissatisfaction	-2.2	0.74833	[-4, -2, -2, -2, -1, -3, -2, -2, -2, -2]
-dissatisfactions	-1.9	0.83066	[-1, -3, -3, -1, -2, -1, -2, -2, -1, -3]
-dissatisfactory	-2.0	0.63246	[-2, -2, -3, -1, -2, -3, -2, -2, -1, -2]
-dissatisfied	-1.6	0.66332	[-2, -3, -1, -2, -1, -1, -2, -2, -1, -1]
-dissatisfies	-1.8	0.74833	[-3, -3, -1, -1, -2, -1, -2, -2, -2, -1]
-dissatisfy	-2.2	0.6	[-2, -3, -2, -2, -2, -2, -3, -3, -1, -2]
-dissatisfying	-2.4	0.91652	[-3, -1, -4, -3, -2, -1, -2, -2, -3, -3]
-distort	-1.3	0.45826	[-2, -1, -1, -1, -2, -1, -1, -1, -1, -2]
-distorted	-1.7	0.78102	[-3, -1, -3, -1, -2, -1, -2, -2, -1, -1]
-distorting	-1.1	0.53852	[0, -1, -1, -1, -2, -1, -1, -1, -2, -1]
-distorts	-1.4	0.4899	[-2, -1, -1, -1, -2, -2, -2, -1, -1, -1]
-distract	-1.2	0.6	[-1, -1, 0, -2, -1, -1, -1, -2, -1, -2]
-distractable	-1.3	1.00499	[-2, 0, 1, -2, -2, -1, -1, -2, -2, -2]
-distracted	-1.4	0.66332	[-1, -3, -1, -2, -2, -1, -1, -1, -1, -1]
-distractedly	-0.9	0.7	[-1, -1, 0, -2, -1, 0, -1, 0, -1, -2]
-distractibility	-1.3	1.1	[-1, -1, -3, -1, 0, -3, -2, 0, -2, 0]
-distractible	-1.5	0.92195	[-1, -2, -1, -1, -4, -1, -1, -1, -2, -1]
-distracting	-1.2	0.4	[-2, -1, -1, -1, -1, -1, -2, -1, -1, -1]
-distractingly	-1.4	1.0198	[-4, 0, -1, -1, -1, -2, -1, -1, -2, -1]
-distraction	-1.6	0.66332	[-1, -2, -2, -1, -1, -3, -1, -1, -2, -2]
-distractions	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
-distractive	-1.6	0.4899	[-2, -2, -1, -1, -1, -1, -2, -2, -2, -2]
-distracts	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -2, -1, -1]
-distraught	-2.6	0.8	[-2, -3, -2, -3, -4, -2, -3, -3, -1, -3]
-distress	-2.4	0.8	[-1, -2, -2, -3, -3, -4, -3, -2, -2, -2]
-distressed	-1.8	0.6	[-2, -2, -2, -3, -2, -2, -1, -1, -2, -1]
-distresses	-1.6	0.66332	[-2, -1, -1, -2, -2, -2, -1, -1, -3, -1]
-distressful	-2.2	0.6	[-1, -3, -3, -2, -2, -3, -2, -2, -2, -2]
-distressfully	-1.7	1.1	[-1, -3, -2, 1, -3, -1, -2, -2, -2, -2]
-distressfulness	-2.4	0.66332	[-2, -3, -2, -3, -3, -3, -2, -1, -3, -2]
-distressing	-1.7	1.18743	[-3, -3, -1, -1, -2, -2, -3, -2, 1, -1]
-distressingly	-2.2	0.74833	[-3, -1, -2, -3, -3, -3, -2, -2, -2, -1]
-distrust	-1.8	0.87178	[-1, -2, -2, -2, -1, -1, -2, -4, -1, -2]
-distrusted	-2.4	0.66332	[-1, -3, -3, -3, -2, -2, -3, -2, -2, -3]
-distrustful	-2.1	0.83066	[-1, -3, -2, -2, -3, -1, -1, -3, -2, -3]
-distrustfully	-1.8	0.6	[-2, -1, -1, -2, -1, -2, -3, -2, -2, -2]
-distrustfulness	-1.6	0.66332	[-2, -1, -2, -1, -2, -1, -1, -3, -1, -2]
-distrusting	-2.1	0.83066	[-1, -2, -2, -2, -3, -3, -1, -3, -1, -3]
-distrusts	-1.3	0.45826	[-1, -1, -2, -1, -2, -1, -2, -1, -1, -1]
-disturb	-1.7	0.45826	[-2, -1, -1, -2, -2, -2, -1, -2, -2, -2]
-disturbance	-1.6	0.8	[-1, -2, -1, -2, -2, -3, -1, -2, 0, -2]
-disturbances	-1.4	0.66332	[-1, -1, -1, -2, -1, -1, -1, -1, -3, -2]
-disturbed	-1.6	0.4899	[-2, -2, -1, -1, -2, -2, -1, -2, -1, -2]
-disturber	-1.4	0.4899	[-2, -1, -1, -2, -2, -1, -1, -2, -1, -1]
-disturbers	-2.1	0.53852	[-2, -2, -2, -2, -2, -3, -3, -2, -1, -2]
-disturbing	-2.3	0.45826	[-2, -2, -3, -3, -2, -2, -3, -2, -2, -2]
-disturbingly	-2.3	0.78102	[-2, -2, -1, -3, -4, -3, -2, -2, -2, -2]
-disturbs	-1.9	0.53852	[-2, -2, -1, -2, -3, -2, -1, -2, -2, -2]
-dithering	-0.5	0.92195	[0, 0, 0, 0, 1, -1, -2, -2, -1, 0]
-divination	1.7	1.1	[2, 3, 0, 1, 2, 1, 3, 3, 2, 0]
-divinations	1.1	1.04403	[1, 0, 1, 2, 2, 0, 3, 2, 0, 0]
-divinatory	1.6	1.42829	[4, 1, 0, 0, 1, 3, 3, 0, 1, 3]
-divine	2.6	0.8	[3, 3, 3, 2, 1, 2, 3, 4, 2, 3]
-divined	0.8	1.16619	[1, 0, 3, 0, 0, 1, 0, 3, 0, 0]
-divinely	2.9	0.7	[3, 2, 3, 3, 2, 4, 3, 2, 4, 3]
-diviner	0.3	0.9	[0, 0, 3, 0, 0, 0, 0, 0, 0, 0]
-diviners	1.2	1.16619	[0, 1, 0, 2, 2, 0, 3, 1, 3, 0]
-divines	0.8	1.249	[0, 0, 3, 0, 0, 0, 3, 2, 0, 0]
-divinest	2.7	0.78102	[3, 4, 2, 4, 2, 2, 2, 3, 2, 3]
-diving	0.3	0.45826	[1, 0, 0, 0, 0, 1, 0, 1, 0, 0]
-divining	0.9	1.37477	[0, -1, 2, 0, 1, 0, 2, 4, 1, 0]
-divinise	0.5	1.36015	[0, 2, 0, 0, 0, 0, 0, -2, 2, 3]
-divinities	1.8	1.46969	[1, 3, 3, 4, 0, 0, 1, 0, 3, 3]
-divinity	2.7	1.00499	[4, 4, 2, 3, 3, 1, 2, 4, 2, 2]
-divinize	2.3	1.00499	[4, 2, 2, 3, 4, 1, 1, 2, 2, 2]
-dizzy	-0.9	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, 0, -1]
-dodging	-0.4	0.8	[-1, -1, 0, 1, 0, -1, 0, 0, -2, 0]
-dodgy	-0.9	0.9434	[-1, -1, -1, -3, -1, 1, -1, -1, -1, 0]
-dolorous	-2.2	0.6	[-2, -2, -2, -3, -3, -3, -2, -2, -1, -2]
-dominance	0.8	0.87178	[2, 0, 0, 2, 1, 0, 0, 1, 2, 0]
-dominances	-0.1	0.9434	[-1, 0, 1, 1, 0, -1, 0, 1, 0, -2]
-dominantly	0.2	1.16619	[-2, 0, 0, -1, 2, 1, 2, 0, 0, 0]
-dominants	0.2	1.16619	[0, 2, -1, 0, -1, -1, -1, 1, 1, 2]
-dominate	-0.5	0.92195	[0, -1, 1, -1, 1, -1, -2, 0, -1, -1]
-dominates	0.2	1.249	[1, 0, -2, -1, 1, -1, 2, 0, 0, 2]
-dominating	-1.2	1.98997	[-4, -1, -4, -1, -3, -1, -1, 2, 2, -1]
-domination	-0.2	0.9798	[0, 1, 0, -1, -1, -1, 0, 2, -1, -1]
-dominations	-0.3	0.45826	[0, 0, 0, 0, 0, -1, 0, -1, -1, 0]
-dominative	-0.7	1.18743	[-1, -1, -2, -2, -1, -1, -1, 2, 1, -1]
-dominators	-0.4	1.8	[-1, -2, -2, -2, 0, 2, 2, -3, 2, 0]
-dominatrices	-0.2	1.6	[-3, 0, 2, 0, -2, -2, 0, 1, 2, 0]
-dominatrix	-0.5	0.92195	[0, 0, -1, 0, 0, 1, 0, -1, -2, -2]
-dominatrixes	0.6	1.35647	[0, 4, 0, -1, 0, 2, 1, 0, 0, 0]
-doom	-1.7	1.26886	[-2, -1, -1, -4, -2, -2, 1, -3, -1, -2]
-doomed	-3.2	0.74833	[-3, -3, -4, -4, -4, -2, -4, -3, -3, -2]
-doomful	-2.1	0.7	[-3, -2, -3, -1, -2, -3, -2, -1, -2, -2]
-dooming	-2.8	0.4	[-2, -3, -2, -3, -3, -3, -3, -3, -3, -3]
-dooms	-1.1	1.57797	[1, -3, -1, -3, -2, -1, -3, 1, 1, -1]
-doomsayer	-0.7	1.41774	[2, -1, -2, -1, 1, -2, -2, -1, 1, -2]
-doomsayers	-1.7	0.78102	[-1, -2, -3, 0, -2, -2, -2, -1, -2, -2]
-doomsaying	-1.5	1.28452	[-3, -2, -2, 0, 1, 0, -3, -2, -2, -2]
-doomsayings	-1.5	0.92195	[-2, -1, -1, -2, -2, 0, 0, -2, -3, -2]
-doomsday	-2.8	1.249	[-3, -1, -3, -4, -3, -4, 0, -4, -3, -3]
-doomsdayer	-2.2	1.249	[-3, -1, -4, -3, -4, -3, -1, -1, -1, -1]
-doomsdays	-2.4	1.85472	[-3, -2, -4, 1, -4, -3, -2, -4, 1, -4]
-doomster	-2.2	0.87178	[-2, -1, -2, -3, -1, -3, -1, -3, -3, -3]
-doomsters	-1.6	0.8	[-3, -1, -2, -2, 0, -2, -2, -1, -1, -2]
-doomy	-1.1	1.37477	[2, -2, -1, -2, -2, -2, -2, 1, -1, -2]
-dork	-1.4	0.66332	[-1, -2, -2, -1, -1, -1, -3, -1, -1, -1]
-dorkier	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -2, -1, -1]
-dorkiest	-1.2	0.74833	[-1, -2, -1, -3, -1, 0, -1, -1, -1, -1]
-dorks	-0.5	0.67082	[-1, 1, -1, -1, -1, -1, 0, 0, -1, 0]
-dorky	-1.1	1.04403	[-1, 0, -1, 1, -1, -1, -3, -2, -2, -1]
-doubt	-1.5	0.5	[-1, -1, -2, -2, -1, -1, -2, -1, -2, -2]
-doubtable	-1.5	0.5	[-1, -1, -2, -1, -2, -1, -2, -2, -1, -2]
-doubted	-1.1	1.22066	[-1, -2, -2, 2, -1, -1, -2, -2, -2, 0]
-doubter	-1.6	0.91652	[-1, -3, -2, -1, -1, -1, -2, -2, -3, 0]
-doubters	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -1, -2, -2, -1]
-doubtful	-1.4	0.4899	[-1, -1, -2, -1, -2, -2, -1, -1, -2, -1]
-doubtfully	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -2]
-doubtfulness	-1.2	0.4	[-2, -1, -1, -1, -1, -1, -1, -1, -1, -2]
-doubting	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -1, -1, -2, -2]
-doubtingly	-1.4	0.4899	[-2, -2, -1, -1, -1, -1, -1, -2, -2, -1]
-doubtless	0.9	1.51327	[2, 2, 1, 2, -2, 2, -2, 1, 1, 2]
-doubtlessly	1.2	0.9798	[2, 1, 1, 2, 0, -1, 2, 1, 2, 2]
-doubtlessness	0.8	0.9798	[2, 1, 2, 0, 0, 0, 2, -1, 1, 1]
-doubts	-1.2	0.6	[-2, -1, -1, -1, -2, -2, -1, 0, -1, -1]
-douche	-1.5	1.68819	[-3, -2, -3, 1, 1, -2, -3, -2, 1, -3]
-douchebag	-3.0	0.44721	[-3, -3, -3, -3, -3, -3, -2, -3, -4, -3]
-downcast	-1.8	0.74833	[-1, -1, -1, -2, -2, -2, -1, -3, -3, -2]
-downhearted	-2.3	0.78102	[-1, -2, -2, -4, -2, -2, -2, -3, -3, -2]
-downside	-1.0	0.7746	[-1, -1, -1, -1, -1, -1, -2, 1, -2, -1]
-drag	-0.9	0.83066	[-1, -2, -1, -1, -2, -1, -1, 1, 0, -1]
-dragged	-0.2	1.07703	[-2, -1, 0, 0, -1, 0, 0, 1, 2, -1]
-drags	-0.7	0.64031	[0, -1, 0, -1, -1, -2, -1, 0, 0, -1]
-drained	-1.5	0.5	[-1, -1, -2, -2, -1, -2, -1, -2, -1, -2]
-dread	-2.0	0.63246	[-2, -3, -2, -2, -2, -2, -3, -1, -1, -2]
-dreaded	-2.7	0.64031	[-2, -3, -3, -3, -4, -3, -2, -2, -2, -3]
-dreadful	-1.9	1.86815	[-4, -2, -2, 2, -1, -4, -1, 0, -3, -4]
-dreadfully	-2.7	1.26886	[-4, -4, -3, -4, -3, -1, -2, -1, -1, -4]
-dreadfulness	-3.2	0.87178	[-3, -4, -2, -3, -4, -4, -2, -2, -4, -4]
-dreadfuls	-2.4	1.2	[-4, -3, -3, -2, -3, -2, -4, 0, -1, -2]
-dreading	-2.4	0.8	[-3, -2, -2, -2, -2, -2, -3, -4, -3, -1]
-dreadlock	-0.4	0.66332	[0, 0, 0, 0, 0, -1, -2, 0, -1, 0]
-dreadlocks	-0.2	0.9798	[0, 0, 0, 0, 0, -1, -2, 2, 0, -1]
-dreadnought	-0.6	1.35647	[-2, 0, 0, 0, -3, 0, -1, -2, 0, 2]
-dreadnoughts	-0.4	0.66332	[0, -1, -1, 0, 0, 0, 0, 0, -2, 0]
-dreads	-1.4	1.42829	[0, -1, 0, 0, -3, -3, 0, -4, -2, -1]
-dream	1.0	1.18322	[0, 1, 2, 0, 0, 3, 0, 3, 1, 0]
-dreams	1.7	1.1	[2, 2, 3, 0, 1, 1, 1, 4, 1, 2]
-dreary	-1.4	0.4899	[-1, -1, -2, -1, -1, -2, -2, -1, -2, -1]
-droopy	-0.8	0.74833	[-1, -1, 0, -1, -2, 0, 0, -1, 0, -2]
-drop	-1.1	0.53852	[0, -1, -1, -1, -2, -1, -2, -1, -1, -1]
-drown	-2.7	1.00499	[-4, -2, -2, -4, -4, -2, -3, -1, -3, -2]
-drowned	-2.9	0.7	[-2, -3, -3, -3, -2, -4, -4, -2, -3, -3]
-drowns	-2.2	1.6	[-3, -3, -3, -4, -2, -3, -1, -2, 2, -3]
-drunk	-1.4	0.91652	[-3, -1, 0, -2, 0, -1, -1, -2, -2, -2]
-dubious	-1.5	0.5	[-1, -2, -2, -1, -1, -2, -1, -1, -2, -2]
-dud	-1.0	0.89443	[-1, -1, -1, 0, -3, 0, -1, 0, -1, -2]
-dull	-1.7	0.45826	[-2, -2, -2, -1, -2, -2, -2, -1, -1, -2]
-dullard	-1.6	0.66332	[-2, -1, -1, -2, -2, -1, -1, -2, -1, -3]
-dullards	-1.8	0.87178	[-1, -3, -1, -1, -3, -1, -1, -2, -3, -2]
-dulled	-1.5	0.5	[-2, -1, -2, -1, -1, -1, -2, -2, -1, -2]
-duller	-1.7	0.64031	[-3, -1, -2, -2, -2, -1, -2, -1, -1, -2]
-dullest	-1.7	1.00499	[-1, -4, -1, -1, -2, -3, -2, -1, -1, -1]
-dulling	-1.1	0.7	[-1, -2, 0, -1, -2, -2, 0, -1, -1, -1]
-dullish	-1.1	0.53852	[-2, -1, -1, -1, -1, -1, -1, -1, 0, -2]
-dullness	-1.4	0.8	[-1, -1, -1, -1, -1, -1, -3, -1, -3, -1]
-dullnesses	-1.9	1.04403	[-3, -2, -1, -1, -3, -1, -4, -1, -2, -1]
-dulls	-1.0	0.44721	[-1, -1, -1, -1, -1, -1, 0, -1, -1, -2]
-dullsville	-2.4	0.8	[-2, -2, -4, -3, -2, -2, -3, -2, -3, -1]
-dully	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -2]
-dumb	-2.3	0.9	[-4, -2, -2, -2, -2, -2, -4, -2, -2, -1]
-dumbass	-2.6	1.0198	[-3, -3, -4, -4, -1, -2, -3, -3, -1, -2]
-dumbbell	-0.8	0.9798	[0, -1, -3, -2, 0, -1, 0, 0, -1, 0]
-dumbbells	-0.2	0.4	[0, -1, 0, 0, 0, 0, 0, -1, 0, 0]
-dumbcane	-0.3	0.45826	[0, 0, 0, 0, 0, -1, -1, 0, -1, 0]
-dumbcanes	-0.6	1.2	[0, 0, -1, -1, -1, 2, 0, -1, -3, -1]
-dumbed	-1.4	0.4899	[-2, -1, -2, -2, -2, -1, -1, -1, -1, -1]
-dumber	-1.5	0.5	[-2, -1, -2, -1, -2, -1, -1, -2, -2, -1]
-dumbest	-2.3	1.00499	[-3, -1, -3, -4, -2, -1, -2, -3, -1, -3]
-dumbfound	-0.1	1.92094	[3, -2, -1, -1, 1, 1, -3, 3, -1, -1]
-dumbfounded	-1.6	1.11355	[-2, 0, -2, 0, -2, -1, -4, -1, -2, -2]
-dumbfounder	-1.0	0.89443	[-2, 0, 0, 0, -2, -1, -2, 0, -2, -1]
-dumbfounders	-1.0	0.89443	[-1, -3, -1, 0, -2, 0, -1, 0, -1, -1]
-dumbfounding	-0.8	0.74833	[-1, -2, 0, -1, -1, 0, 0, -1, 0, -2]
-dumbfounds	-0.3	1.26886	[0, -1, -1, 0, 0, -1, -1, -2, 0, 3]
-dumbhead	-2.6	0.66332	[-3, -4, -3, -2, -2, -3, -3, -2, -2, -2]
-dumbheads	-1.9	0.83066	[-2, -2, -2, -1, -2, -1, -2, -4, -1, -2]
-dumbing	-0.5	1.0247	[-1, 2, -1, 0, -1, -2, -1, 0, 0, -1]
-dumbly	-1.3	1.00499	[-2, -1, -2, -3, 1, -2, -1, -1, -1, -1]
-dumbness	-1.9	0.53852	[-2, -2, -2, -2, -2, -3, -2, -2, -1, -1]
-dumbs	-1.5	0.67082	[-1, -1, -1, -3, -2, -1, -2, -1, -2, -1]
-dumbstruck	-1.0	1.34164	[-1, -2, 0, 0, -2, 1, -3, 1, -2, -2]
-dumbwaiter	0.2	1.07703	[0, 0, 0, 0, 2, 0, 2, 0, -2, 0]
-dumbwaiters	-0.1	0.3	[0, 0, 0, 0, 0, 0, -1, 0, 0, 0]
-dump	-1.6	0.91652	[-3, -2, -1, -2, -1, -3, -2, -1, -1, 0]
-dumpcart	-0.6	0.8	[0, -2, -1, 0, 0, 0, -1, 0, -2, 0]
-dumped	-1.7	0.78102	[-2, -3, -2, -1, -1, -1, -3, -2, -1, -1]
-dumper	-1.2	0.87178	[-2, -3, -1, -1, -1, -2, 0, -1, 0, -1]
-dumpers	-0.8	0.6	[0, 0, -2, -1, -1, 0, -1, -1, -1, -1]
-dumpier	-1.4	0.66332	[-2, -1, -2, -1, -1, -2, 0, -2, -1, -2]
-dumpiest	-1.6	1.35647	[-1, -2, -2, -3, -2, -4, 1, 0, -1, -2]
-dumpiness	-1.2	0.6	[-2, -1, 0, -1, -1, -2, -1, -2, -1, -1]
-dumping	-1.3	1.1	[-3, -2, -2, 0, -2, -1, -1, 1, -1, -2]
-dumpings	-1.1	0.83066	[-2, 0, -1, -1, 0, -1, -2, -2, 0, -2]
-dumpish	-1.8	0.6	[-2, -1, -2, -3, -2, -2, -1, -2, -2, -1]
-dumpling	0.4	0.91652	[0, 0, 1, 0, -1, 2, 2, 0, 0, 0]
-dumplings	-0.3	1.26886	[0, 0, 0, 0, 2, 0, 0, 0, -2, -3]
-dumps	-1.7	0.9	[-3, -2, -3, -1, -1, -3, -1, -1, -1, -1]
-dumpster	-0.6	0.91652	[0, -2, 0, -2, 0, 0, 0, -2, 0, 0]
-dumpsters	-1.0	0.89443	[0, -1, 0, -2, -2, -2, 0, 0, -1, -2]
-dumpy	-1.7	0.78102	[-3, -2, -3, -1, -1, -2, -2, -1, -1, -1]
-dupe	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -2, -1, -2, -1]
-duped	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -1, -2, -2]
-dwell	0.5	0.92195	[2, 1, -1, 0, -1, 1, 1, 1, 1, 0]
-dwelled	0.4	0.66332	[2, 0, 0, 0, 0, 1, 1, 0, 0, 0]
-dweller	0.3	0.64031	[2, 0, 0, 0, 0, 0, 1, 0, 0, 0]
-dwellers	-0.3	0.9	[-3, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-dwelling	0.1	0.53852	[0, 1, 0, 1, 0, 0, 0, -1, 0, 0]
-dwells	-0.1	0.53852	[0, 0, 0, 0, -1, 1, -1, 0, 0, 0]
-dynamic	1.6	0.8	[1, 1, 1, 3, 1, 1, 2, 3, 2, 1]
-dynamical	1.2	0.87178	[1, 2, 0, 1, 0, 2, 2, 2, 2, 0]
-dynamically	1.5	1.0247	[2, 0, 3, 2, 0, 0, 2, 2, 2, 2]
-dynamics	1.1	1.13578	[2, 3, 0, 0, 0, 2, 2, 0, 2, 0]
-dynamism	1.6	1.11355	[0, 2, 0, 2, 0, 2, 3, 3, 2, 2]
-dynamisms	1.2	0.9798	[2, 0, 2, 0, 0, 2, 2, 2, 0, 2]
-dynamist	1.4	1.0198	[0, 2, 0, 2, 0, 1, 3, 2, 2, 2]
-dynamistic	1.5	1.0247	[3, 1, 1, 2, 1, 3, 2, 0, 2, 0]
-dynamists	0.9	0.83066	[1, 0, 0, 0, 0, 2, 2, 1, 2, 1]
-dynamite	0.7	2.2383	[-3, 2, 3, 1, 2, 0, 2, 2, 2, -4]
-dynamited	-0.9	1.04403	[0, 0, 0, -1, -1, 0, -2, 0, -2, -3]
-dynamiter	-1.2	0.87178	[-1, 0, -1, -1, -2, 0, -1, -1, -2, -3]
-dynamiters	0.4	1.42829	[0, 0, 0, -3, 1, 0, 2, 2, 2, 0]
-dynamites	-0.3	1.73494	[0, 0, 4, -1, -1, 0, 0, 0, -2, -3]
-dynamitic	0.9	1.3	[2, 0, 1, -2, 2, 1, 1, 3, 0, 1]
-dynamiting	0.2	1.32665	[-2, 0, 0, 2, -1, -1, 0, 2, 2, 0]
-dynamometer	0.3	0.64031	[0, 0, 0, 0, 1, 0, 0, 2, 0, 0]
-dynamometers	0.3	0.45826	[0, 0, 0, 0, 0, 1, 0, 1, 1, 0]
-dynamometric	0.3	0.9	[0, 0, 0, 0, 0, 2, 0, 0, 2, -1]
-dynamometry	0.6	1.28062	[-2, 0, 0, 0, 0, 2, 2, 2, 0, 2]
-dynamos	0.3	0.64031	[1, 0, 0, 0, 0, 0, 0, 0, 2, 0]
-dynamotor	0.6	0.91652	[0, 2, 0, 0, 0, 0, 2, 0, 2, 0]
-dysfunction	-1.8	0.6	[-2, -3, -2, -1, -2, -1, -2, -1, -2, -2]
-eager	1.5	0.67082	[1, 3, 1, 2, 2, 2, 1, 1, 1, 1]
-eagerly	1.6	0.66332	[0, 1, 2, 2, 2, 2, 2, 1, 2, 2]
-eagerness	1.7	0.45826	[2, 2, 2, 2, 1, 1, 2, 2, 2, 1]
-eagers	1.6	0.66332	[2, 2, 3, 1, 2, 1, 1, 1, 2, 1]
-earnest	2.3	0.64031	[3, 2, 3, 1, 2, 2, 2, 3, 3, 2]
-ease	1.5	0.92195	[1, 1, 1, 0, 2, 1, 2, 3, 3, 1]
-eased	1.2	0.74833	[2, 0, 1, 0, 2, 2, 1, 1, 1, 2]
-easeful	1.5	1.0247	[2, 1, 1, 2, 1, 0, 3, 2, 0, 3]
-easefully	1.4	0.4899	[2, 2, 1, 1, 1, 1, 2, 2, 1, 1]
-easel	0.3	0.45826	[0, 0, 0, 0, 1, 1, 0, 0, 0, 1]
-easement	1.6	0.91652	[0, 1, 2, 3, 2, 1, 2, 1, 3, 1]
-easements	0.4	1.11355	[0, 0, 0, 1, 2, -2, 1, 0, 2, 0]
-eases	1.3	0.78102	[2, 0, 1, 0, 2, 2, 2, 1, 1, 2]
-easier	1.8	0.9798	[1, 1, 2, 2, 4, 3, 2, 1, 1, 1]
-easiest	1.8	1.07703	[2, 4, 1, 3, 2, 0, 2, 2, 1, 1]
-easily	1.4	0.4899	[2, 1, 1, 2, 1, 2, 1, 2, 1, 1]
-easiness	1.6	0.66332	[2, 1, 1, 2, 3, 2, 1, 1, 2, 1]
-easing	1.0	0.63246	[0, 0, 2, 1, 1, 2, 1, 1, 1, 1]
-easy	1.9	1.04403	[1, 4, 2, 1, 1, 3, 1, 3, 2, 1]
-easygoing	1.3	0.45826	[1, 1, 1, 1, 1, 1, 2, 2, 2, 1]
-easygoingness	1.5	0.67082	[1, 2, 1, 2, 1, 3, 1, 2, 1, 1]
-ecstacy	3.3	1.18743	[4, 4, 3, 4, 4, 0, 3, 3, 4, 4]
-ecstasies	2.3	1.34536	[3, 3, 2, 4, 3, 1, 3, -1, 2, 3]
-ecstasy	2.9	1.75784	[4, 3, 3, 4, 4, 2, -2, 3, 4, 4]
-ecstatic	2.3	1.34536	[3, 4, 3, 4, 1, 1, 1, 4, 1, 1]
-ecstatically	2.8	1.93907	[3, 4, -1, 4, 4, 4, -1, 3, 4, 4]
-ecstatics	2.9	0.83066	[1, 3, 4, 4, 3, 3, 3, 2, 3, 3]
-eerie	-1.5	0.67082	[-1, -1, -2, -2, -1, -1, -2, -1, -3, -1]
-eery	-0.9	1.04403	[-3, -1, -2, -1, -2, 0, 0, 0, 0, 0]
-effective	2.1	0.83066	[2, 2, 2, 1, 3, 4, 2, 1, 2, 2]
-effectively	1.9	0.7	[1, 2, 1, 2, 2, 1, 3, 3, 2, 2]
-efficiencies	1.6	0.4899	[2, 1, 1, 2, 2, 2, 1, 2, 2, 1]
-efficiency	1.5	0.5	[2, 1, 2, 2, 1, 2, 1, 1, 2, 1]
-efficient	1.8	0.9798	[1, 2, 1, 1, 2, 3, 3, 0, 2, 3]
-efficiently	1.7	0.78102	[1, 3, 2, 1, 3, 1, 1, 2, 2, 1]
-effin	-2.3	1.18743	[0, -3, -3, -3, -2, -1, -4, -1, -3, -3]
-egotism	-1.4	0.91652	[-2, -3, -1, -2, -2, 0, 0, -1, -2, -1]
-egotisms	-1.0	0.7746	[-1, -1, -1, -1, -1, 0, 0, -1, -3, -1]
-egotist	-2.3	0.9	[-2, -1, -2, -3, -4, -2, -3, -3, -1, -2]
-egotistic	-1.4	1.0198	[-2, -1, -1, -1, -2, 1, -3, -2, -1, -2]
-egotistical	-0.9	1.57797	[-1, -2, -2, -1, -2, 1, -3, 2, 1, -2]
-egotistically	-1.8	0.87178	[-2, -1, -1, -2, -1, -3, -3, -1, -1, -3]
-egotists	-1.7	0.78102	[-1, -2, 0, -2, -2, -2, -3, -1, -2, -2]
-elated	3.2	0.74833	[2, 4, 4, 3, 4, 3, 3, 2, 3, 4]
-elation	1.5	1.43178	[1, 2, -2, 2, 2, 3, 0, 3, 2, 2]
-elegance	2.1	0.53852	[3, 2, 2, 1, 2, 2, 3, 2, 2, 2]
-elegances	1.8	0.6	[2, 2, 1, 1, 2, 2, 2, 3, 2, 1]
-elegancies	1.6	1.0198	[2, 1, 2, 1, 1, 0, 4, 1, 2, 2]
-elegancy	2.1	0.53852	[3, 2, 2, 1, 2, 2, 3, 2, 2, 2]
-elegant	2.1	0.83066	[2, 2, 2, 1, 4, 1, 2, 3, 2, 2]
-elegantly	1.9	0.83066	[2, 1, 1, 3, 2, 2, 1, 3, 3, 1]
-embarrass	-1.2	1.66132	[-2, -2, -3, -1, -2, -2, 2, 2, -2, -2]
-embarrassable	-1.6	0.8	[-3, -2, -1, -3, -1, -1, -1, -2, -1, -1]
-embarrassed	-1.5	0.67082	[-2, -2, -1, -2, -1, -3, -1, -1, -1, -1]
-embarrassedly	-1.1	1.44568	[-2, -1, -2, -3, 1, -1, -1, -2, -2, 2]
-embarrasses	-1.7	0.78102	[-2, -3, -1, -2, -1, -3, -2, -1, -1, -1]
-embarrassing	-1.6	0.8	[-3, -1, -1, -1, -1, -2, -1, -2, -3, -1]
-embarrassingly	-1.7	0.64031	[-2, -1, -1, -2, -1, -2, -1, -3, -2, -2]
-embarrassment	-1.9	0.53852	[-2, -2, -1, -2, -2, -2, -2, -1, -3, -2]
-embarrassments	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -3]
-embittered	-0.4	1.35647	[1, -2, -1, 1, -2, 2, 0, -1, 0, -2]
-embrace	1.3	1.34536	[3, 2, 1, 3, 2, -1, 2, 1, -1, 1]
-emergency	-1.6	2.05913	[-3, -3, -3, -3, -4, 2, 1, -1, 1, -3]
-emotional	0.6	1.0198	[1, -1, 0, 0, 0, 2, 0, 2, 2, 0]
-empathetic	1.7	1.1	[-1, 3, 2, 2, 2, 1, 3, 1, 2, 2]
-emptied	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
-emptier	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
-emptiers	-0.7	0.78102	[0, 0, -1, 0, -1, -1, -2, 0, -2, 0]
-empties	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
-emptiest	-1.8	1.07703	[-1, -2, -2, -1, -1, -2, -3, 0, -4, -2]
-emptily	-1.0	1.41421	[-2, 2, -1, -1, -1, 0, -4, -1, -1, -1]
-emptiness	-1.9	0.7	[-2, -2, -3, -2, -2, -1, -1, -3, -1, -2]
-emptinesses	-1.5	1.11803	[-1, -1, -3, -1, -1, -1, -2, 0, -4, -1]
-emptins	-0.3	0.45826	[0, 0, 0, -1, 0, 0, 0, -1, -1, 0]
-empty	-0.8	0.74833	[-1, -1, -1, -1, -1, -1, -2, 0, -1, 1]
-emptying	-0.6	1.0198	[2, -1, -1, 0, -1, 0, -1, -1, -2, -1]
-enchanted	1.6	0.8	[1, 3, 1, 2, 1, 3, 1, 2, 1, 1]
-encourage	2.3	0.78102	[2, 1, 3, 2, 3, 4, 2, 2, 2, 2]
-encouraged	1.5	0.5	[1, 2, 2, 2, 2, 2, 1, 1, 1, 1]
-encouragement	1.8	0.9798	[2, 1, 2, 1, 1, 3, 1, 2, 4, 1]
-encouragements	2.1	0.7	[3, 2, 3, 2, 1, 2, 3, 2, 2, 1]
-encourager	1.5	0.5	[2, 1, 2, 1, 1, 2, 1, 1, 2, 2]
-encouragers	1.5	0.5	[2, 2, 1, 1, 2, 2, 1, 1, 2, 1]
-encourages	1.9	0.53852	[2, 2, 1, 2, 2, 1, 2, 2, 2, 3]
-encouraging	2.4	0.66332	[2, 3, 2, 3, 3, 2, 3, 2, 1, 3]
-encouragingly	2.0	0.7746	[1, 1, 1, 3, 2, 2, 2, 3, 2, 3]
-endorse	1.3	0.9	[0, 1, 0, 1, 3, 2, 2, 2, 1, 1]
-endorsed	1.0	0.89443	[1, 2, 0, 1, 1, 0, 1, 0, 3, 1]
-endorsement	1.3	0.9	[0, 1, 2, 2, 1, 2, 0, 1, 3, 1]
-endorses	1.4	0.4899	[1, 2, 1, 2, 1, 1, 1, 2, 2, 1]
-enemies	-2.2	0.6	[-2, -3, -1, -2, -2, -3, -2, -3, -2, -2]
-enemy	-2.5	0.92195	[-3, -2, -3, -3, -3, -4, -1, -3, -1, -2]
-energetic	1.9	0.53852	[2, 1, 3, 2, 2, 2, 1, 2, 2, 2]
-energetically	1.8	0.6	[2, 2, 1, 1, 2, 2, 3, 1, 2, 2]
-energetics	0.3	0.64031	[1, 0, 0, 0, 0, 0, 2, 0, 0, 0]
-energies	0.9	1.04403	[1, 0, 0, 2, 0, 1, 3, 2, 0, 0]
-energise	2.2	0.4	[2, 2, 2, 2, 2, 2, 3, 2, 3, 2]
-energised	2.1	0.53852	[2, 3, 1, 2, 2, 2, 3, 2, 2, 2]
-energises	2.2	0.6	[3, 3, 2, 2, 1, 3, 2, 2, 2, 2]
-energising	1.9	0.7	[2, 3, 1, 2, 2, 3, 2, 1, 1, 2]
-energization	1.6	0.66332	[1, 2, 1, 3, 1, 1, 2, 2, 2, 1]
-energizations	1.5	1.11803	[1, 0, 3, 1, 3, 0, 1, 1, 2, 3]
-energize	2.1	0.7	[2, 2, 2, 1, 3, 2, 3, 2, 3, 1]
-energized	2.3	0.64031	[3, 2, 3, 3, 3, 2, 2, 2, 1, 2]
-energizer	2.1	0.53852	[3, 2, 2, 2, 2, 2, 2, 3, 1, 2]
-energizers	1.7	0.9	[2, 0, 2, 3, 3, 1, 1, 2, 2, 1]
-energizes	2.1	0.53852	[3, 2, 3, 2, 2, 2, 2, 2, 1, 2]
-energizing	2.0	0.63246	[3, 3, 2, 1, 2, 2, 1, 2, 2, 2]
-energy	1.1	0.83066	[0, 2, 0, 2, 1, 1, 2, 1, 2, 0]
-engage	1.4	0.8	[1, 2, 3, 2, 1, 1, 0, 1, 2, 1]
-engaged	1.7	1.1	[1, 1, 2, 2, 1, 0, 2, 3, 4, 1]
-engagement	2.0	1.34164	[0, 0, 3, 4, 4, 2, 1, 2, 2, 2]
-engagements	0.6	0.8	[1, 0, 0, 2, 0, 2, 0, 0, 1, 0]
-engager	1.1	0.7	[1, 1, 0, 2, 1, 0, 2, 1, 2, 1]
-engagers	1.0	0.7746	[1, 1, 1, 0, 2, 1, 0, 2, 2, 0]
-engages	1.0	0.7746	[1, 1, 0, 2, 1, 0, 1, 2, 2, 0]
-engaging	1.4	0.4899	[2, 2, 1, 1, 2, 1, 1, 1, 1, 2]
-engagingly	1.5	0.67082	[1, 2, 3, 1, 1, 1, 1, 1, 2, 2]
-engrossed	0.6	1.49666	[0, 2, 0, 2, -2, 2, 3, -1, 0, 0]
-enjoy	2.2	0.6	[3, 2, 2, 2, 3, 2, 2, 3, 2, 1]
-enjoyable	1.9	0.53852	[3, 2, 2, 1, 2, 1, 2, 2, 2, 2]
-enjoyableness	1.9	1.13578	[2, 2, 2, 2, 1, 3, 3, 3, -1, 2]
-enjoyably	1.8	0.4	[2, 2, 2, 1, 2, 1, 2, 2, 2, 2]
-enjoyed	2.3	0.64031	[2, 2, 1, 3, 3, 3, 2, 2, 2, 3]
-enjoyer	2.2	0.6	[2, 2, 1, 3, 3, 2, 2, 2, 2, 3]
-enjoyers	2.2	0.74833	[2, 4, 2, 2, 2, 2, 2, 3, 2, 1]
-enjoying	2.4	0.66332	[2, 2, 2, 3, 3, 3, 1, 3, 2, 3]
-enjoyment	2.6	0.4899	[2, 3, 2, 3, 2, 3, 2, 3, 3, 3]
-enjoyments	2.0	0.7746	[3, 1, 1, 3, 2, 1, 2, 2, 2, 3]
-enjoys	2.3	0.45826	[2, 3, 2, 2, 2, 3, 2, 3, 2, 2]
-enlighten	2.3	1.1	[2, 2, 1, 3, 2, 1, 1, 4, 3, 4]
-enlightened	2.2	0.87178	[4, 2, 3, 1, 2, 2, 1, 3, 2, 2]
-enlightening	2.3	0.64031	[3, 2, 2, 2, 2, 2, 2, 4, 2, 2]
-enlightens	1.7	1.00499	[2, 1, 1, 1, 1, 2, 4, 1, 3, 1]
-ennui	-1.2	0.6	[-1, -1, -1, -2, -1, -1, -2, -1, 0, -2]
-enrage	-2.6	0.91652	[-3, -3, -3, -4, -1, -1, -3, -2, -3, -3]
-enraged	-1.7	1.79165	[-3, -3, -3, -3, 2, -1, -3, -1, 1, -3]
-enrages	-1.8	1.6	[-3, -3, -3, -3, 1, -1, -3, -1, 1, -3]
-enraging	-2.8	0.74833	[-4, -2, -3, -2, -2, -3, -3, -2, -4, -3]
-enrapture	3.0	0.63246	[2, 4, 3, 3, 4, 3, 3, 2, 3, 3]
-enslave	-3.1	0.9434	[-3, -4, -2, -4, -4, -2, -4, -2, -4, -2]
-enslaved	-1.7	2.41039	[3, -3, -3, -3, -4, -4, -4, 1, -1, 1]
-enslaves	-1.6	2.15407	[2, -2, -3, -2, -4, -4, -4, 1, -1, 1]
-ensure	1.6	0.91652	[2, 1, 3, 1, 1, 2, 3, 2, 0, 1]
-ensuring	1.1	0.9434	[0, 1, 3, 1, 1, 2, 1, 0, 2, 0]
-enterprising	2.3	0.78102	[3, 2, 1, 3, 3, 2, 1, 2, 3, 3]
-entertain	1.3	0.64031	[1, 2, 1, 1, 2, 1, 2, 0, 1, 2]
-entertained	1.7	0.64031	[1, 2, 2, 1, 2, 1, 1, 3, 2, 2]
-entertainer	1.6	1.2	[1, 4, 2, 2, 0, 0, 1, 3, 1, 2]
-entertainers	1.0	0.7746	[0, 1, 2, 2, 0, 0, 1, 1, 2, 1]
-entertaining	1.9	0.83066	[1, 2, 1, 1, 3, 2, 3, 2, 3, 1]
-entertainingly	1.9	0.53852	[2, 1, 2, 3, 2, 2, 1, 2, 2, 2]
-entertainment	1.8	0.9798	[2, 0, 4, 2, 2, 1, 2, 2, 1, 2]
-entertainments	2.3	1.18743	[3, 3, 3, 2, 1, 0, 3, 4, 1, 3]
-entertains	2.4	0.66332	[2, 2, 2, 2, 2, 3, 4, 3, 2, 2]
-enthral	0.4	1.42829	[2, 2, 0, 2, 0, -1, -2, 2, 0, -1]
-enthuse	1.6	0.66332	[1, 2, 1, 1, 3, 1, 2, 2, 2, 1]
-enthused	2.0	0.63246	[3, 3, 1, 2, 2, 2, 2, 1, 2, 2]
-enthuses	1.7	0.78102	[2, 3, 1, 2, 1, 3, 1, 1, 1, 2]
-enthusiasm	1.9	0.9434	[3, 3, 3, 2, 1, 0, 2, 1, 2, 2]
-enthusiasms	2.0	0.89443	[1, 3, 2, 2, 3, 2, 0, 2, 3, 2]
-enthusiast	1.5	0.67082	[1, 2, 2, 2, 0, 1, 1, 2, 2, 2]
-enthusiastic	2.2	0.9798	[1, 2, 3, 4, 2, 3, 2, 1, 1, 3]
-enthusiastically	2.6	0.66332	[3, 3, 3, 2, 3, 3, 3, 3, 2, 1]
-enthusiasts	1.4	0.91652	[1, 1, 0, 3, 3, 2, 1, 1, 1, 1]
-enthusing	1.9	0.7	[2, 1, 2, 1, 2, 3, 2, 1, 2, 3]
-entitled	1.1	0.83066	[2, 2, 1, 1, 2, 1, 1, -1, 1, 1]
-entrusted	0.8	1.46969	[3, 0, 2, 2, 1, 1, -1, 0, -2, 2]
-envied	-1.1	0.83066	[-1, -2, -2, 1, -2, -1, -1, -1, -1, -1]
-envier	-1.0	0.7746	[-1, -2, -2, -1, -1, 1, -1, -1, -1, -1]
-enviers	-1.1	1.13578	[-3, -1, 0, -3, -1, -1, -1, -1, 1, -1]
-envies	-0.8	0.9798	[-1, -2, -2, 1, -1, 1, -1, -1, -1, -1]
-envious	-1.1	0.83066	[-2, -1, -1, -1, -2, -1, -1, 1, -2, -1]
-envy	-1.1	0.83066	[-2, -1, -1, -2, -1, -1, -1, 1, -1, -2]
-envying	-0.8	1.32665	[-1, -1, -1, -1, -3, 2, -2, -1, 1, -1]
-envyingly	-1.3	1.55242	[-2, 3, -2, -2, -1, -3, -1, -1, -2, -2]
-erroneous	-1.8	0.6	[-2, -3, -2, -2, -2, -2, -1, -1, -1, -2]
-error	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -1, -2, -3, -2]
-errors	-1.4	0.66332	[-2, -1, -2, 0, -2, -2, -1, -1, -1, -2]
-escape	0.7	1.00499	[2, 0, 0, 1, 0, 1, 0, 3, 0, 0]
-escapes	0.5	1.36015	[4, 1, 1, 0, -1, 0, -1, 0, 1, 0]
-escaping	0.2	1.46969	[-2, 2, -1, 0, 1, 0, 2, 2, -2, 0]
-esteemed	1.9	0.83066	[3, 2, 1, 2, 3, 1, 1, 2, 3, 1]
-ethical	2.3	0.78102	[3, 3, 3, 3, 2, 2, 1, 3, 2, 1]
-euphoria	3.3	0.9	[4, 4, 3, 3, 3, 4, 4, 4, 1, 3]
-euphoric	3.2	0.87178	[3, 4, 3, 3, 3, 4, 4, 4, 1, 3]
-eviction	-2.0	0.63246	[-2, -2, -3, -2, -3, -2, -1, -2, -1, -2]
-evil	-3.4	0.91652	[-4, -4, -4, -3, -3, -4, -1, -4, -3, -4]
-evildoer	-3.1	0.7	[-2, -3, -3, -3, -4, -4, -3, -2, -3, -4]
-evildoers	-2.4	0.4899	[-3, -3, -2, -2, -2, -2, -2, -2, -3, -3]
-evildoing	-3.1	0.7	[-4, -4, -3, -3, -3, -4, -2, -3, -2, -3]
-evildoings	-2.5	1.0247	[-3, -1, -1, -3, -4, -2, -4, -2, -2, -3]
-eviler	-2.1	1.13578	[-2, -1, -3, -2, -4, -3, -1, -2, 0, -3]
-evilest	-2.5	1.0247	[-3, -4, -1, -3, -2, -3, -1, -4, -2, -2]
-eviller	-2.9	0.83066	[-3, -3, -4, -2, -2, -3, -2, -4, -2, -4]
-evillest	-3.3	0.78102	[-3, -4, -2, -3, -4, -2, -4, -4, -3, -4]
-evilly	-3.4	0.8	[-2, -4, -4, -4, -3, -4, -4, -4, -3, -2]
-evilness	-3.1	1.04403	[-3, -4, -4, -4, -4, -2, -3, -2, -1, -4]
-evils	-2.7	0.78102	[-3, -2, -2, -4, -4, -2, -3, -2, -3, -2]
-exaggerate	-0.6	0.66332	[-1, -1, -1, 0, -1, 0, 1, -1, -1, -1]
-exaggerated	-0.4	1.2	[-1, -1, -1, -1, -1, 2, 1, 1, -2, -1]
-exaggerates	-0.6	1.28062	[-1, -1, -1, -1, -1, 1, 0, 2, -3, -1]
-exaggerating	-0.7	0.9	[-1, -2, 0, -1, 0, 0, -2, -1, 1, -1]
-exasperated	-1.8	1.53623	[-4, -3, -3, -1, -1, -1, 1, -1, -4, -1]
-excel	2.0	1.0	[3, 0, 2, 3, 1, 1, 3, 3, 2, 2]
-excelled	2.2	0.87178	[1, 2, 2, 2, 3, 2, 4, 3, 2, 1]
-excellence	3.1	0.9434	[4, 3, 4, 3, 2, 3, 1, 4, 3, 4]
-excellences	2.5	0.92195	[4, 2, 2, 2, 4, 3, 2, 2, 3, 1]
-excellencies	2.4	0.4899	[3, 2, 3, 3, 2, 2, 2, 2, 3, 2]
-excellency	2.5	0.80623	[4, 2, 3, 3, 2, 3, 1, 3, 2, 2]
-excellent	2.7	0.64031	[2, 3, 3, 3, 3, 2, 3, 2, 2, 4]
-excellently	3.1	0.7	[4, 3, 3, 3, 2, 3, 3, 4, 4, 2]
-excelling	2.5	0.67082	[2, 2, 3, 3, 3, 2, 2, 4, 2, 2]
-excels	2.5	0.92195	[4, 2, 4, 2, 2, 1, 2, 3, 3, 2]
-excelsior	0.7	0.64031	[1, 0, 0, 2, 0, 1, 1, 1, 1, 0]
-excitabilities	1.5	1.0247	[2, 0, 1, 1, 3, 1, 2, 3, 2, 0]
-excitability	1.2	0.87178	[0, 1, 1, 0, 1, 2, 3, 1, 2, 1]
-excitable	1.5	0.92195	[2, 3, 1, 0, 1, 2, 2, 0, 2, 2]
-excitableness	1.0	1.09545	[0, 0, 2, 0, 2, 0, 2, 0, 1, 3]
-excitant	1.8	1.16619	[1, 0, 1, 3, 2, 0, 3, 3, 2, 3]
-excitants	1.2	0.9798	[1, 0, 1, 2, 2, 2, 1, -1, 2, 2]
-excitation	1.8	0.87178	[2, 0, 3, 1, 3, 2, 2, 2, 1, 2]
-excitations	1.8	1.16619	[3, 3, -1, 2, 2, 2, 1, 1, 3, 2]
-excitative	0.3	0.78102	[0, 1, 1, 0, 0, 0, 2, 0, -1, 0]
-excitatory	1.1	1.7	[-1, 2, 2, 1, 2, 2, 2, 3, -3, 1]
-excite	2.1	1.22066	[1, 2, 2, 1, 2, 0, 4, 4, 3, 2]
-excited	1.4	0.4899	[1, 1, 2, 1, 2, 1, 2, 1, 1, 2]
-excitedly	2.3	0.9	[3, 3, 2, 3, 1, 3, 1, 3, 1, 3]
-excitement	2.2	0.4	[2, 2, 2, 3, 3, 2, 2, 2, 2, 2]
-excitements	1.9	0.53852	[2, 1, 2, 3, 2, 2, 2, 2, 2, 1]
-exciter	1.9	0.9434	[3, 2, 3, 1, 0, 1, 2, 3, 2, 2]
-exciters	1.4	1.42829	[1, 2, 0, 1, 2, 4, 0, -1, 3, 2]
-excites	2.1	0.83066	[2, 3, 3, 2, 0, 2, 2, 3, 2, 2]
-exciting	2.2	0.87178	[3, 2, 1, 1, 1, 3, 3, 3, 2, 3]
-excitingly	1.9	0.9434	[3, 2, 3, 0, 1, 2, 1, 2, 2, 3]
-exciton	0.3	0.64031	[2, 0, 0, 0, 0, 0, 1, 0, 0, 0]
-excitonic	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
-excitons	0.8	0.6	[1, 2, 0, 1, 1, 0, 0, 1, 1, 1]
-excitor	0.5	0.67082	[2, 0, 0, 0, 1, 1, 1, 0, 0, 0]
-exclude	-0.9	1.13578	[-1, -2, -1, -3, -1, 1, -1, -1, 1, -1]
-excluded	-1.4	1.62481	[-2, -1, -3, -3, -2, -3, -2, 1, -1, 2]
-exclusion	-1.2	1.249	[-2, -2, -3, -1, -2, -1, -1, -1, 2, -1]
-exclusive	0.5	0.92195	[0, 0, 0, -1, 2, 0, 1, 2, 1, 0]
-excruciate	-2.7	0.64031	[-2, -3, -2, -3, -3, -2, -4, -3, -2, -3]
-excruciated	-1.3	1.9	[-4, -1, -4, 0, 2, -2, -1, -1, -3, 1]
-excruciates	-1.0	2.19089	[-4, 1, -4, 0, 1, -3, -1, 1, -3, 2]
-excruciating	-3.3	0.9	[-3, -4, -4, -4, -4, -4, -4, -2, -2, -2]
-excruciatingly	-2.9	1.04403	[-2, -4, -3, -2, -4, -1, -2, -3, -4, -4]
-excruciation	-3.4	0.66332	[-4, -3, -2, -4, -4, -3, -4, -3, -3, -4]
-excruciations	-1.9	1.51327	[-3, -3, -2, -4, -1, -1, 1, -4, -1, -1]
-excuse	0.3	1.73494	[0, 0, 3, -1, 0, -1, -2, 0, 4, 0]
-exempt	0.4	0.91652	[1, 0, 0, 0, 2, -1, 0, 0, 2, 0]
-exhaust	-1.2	0.87178	[0, -1, 0, -1, -1, -3, -2, -2, -1, -1]
-exhausted	-1.5	1.28452	[-2, -1, 2, -2, -3, -2, -2, -1, -2, -2]
-exhauster	-1.3	0.64031	[-1, -1, 0, -1, -2, -1, -1, -2, -2, -2]
-exhausters	-1.3	0.45826	[-2, -1, -2, -1, -1, -2, -1, -1, -1, -1]
-exhaustibility	-0.8	1.07703	[0, -2, -3, 0, 1, -1, -1, -1, 0, -1]
-exhaustible	-1.0	0.63246	[-1, -1, 0, -1, -2, -2, -1, 0, -1, -1]
-exhausting	-1.5	0.5	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -2]
-exhaustion	-1.5	0.92195	[-2, -1, 1, -2, -2, -2, -2, -1, -2, -2]
-exhaustions	-1.1	0.9434	[-1, -3, -2, -1, -1, -1, -1, 1, -1, -1]
-exhaustive	-0.5	0.67082	[-1, -1, 0, -1, -2, 0, 0, 0, 0, 0]
-exhaustively	-0.7	0.78102	[-2, 0, -1, -1, -1, -2, 0, 0, 0, 0]
-exhaustiveness	-1.1	1.3	[-2, -2, 0, -1, -1, 1, -4, -1, 0, -1]
-exhaustless	0.2	1.8868	[1, 1, 0, 2, 3, 0, -2, 2, -2, -3]
-exhaustlessness	0.9	1.75784	[2, 2, 1, 1, -4, 2, 1, 2, 0, 2]
-exhausts	-1.1	0.53852	[-2, -1, 0, -1, -1, -2, -1, -1, -1, -1]
-exhilarated	3.0	0.63246	[3, 3, 3, 3, 2, 2, 4, 4, 3, 3]
-exhilarates	2.8	1.07703	[4, 3, 3, 3, 0, 2, 3, 4, 3, 3]
-exhilarating	1.7	1.61555	[3, 4, 3, 2, -1, 1, 1, 3, -1, 2]
-exonerate	1.8	0.74833	[2, 2, 2, 2, 3, 2, 1, 0, 2, 2]
-exonerated	1.8	1.83303	[3, -2, 2, 3, 2, 4, 3, 1, -1, 3]
-exonerates	1.6	1.90788	[3, -2, 1, 2, 3, 4, 0, 3, -1, 3]
-exonerating	1.0	1.41421	[2, -2, 3, 0, 0, 2, 0, 2, 2, 1]
-expand	1.3	0.64031	[0, 2, 2, 1, 1, 1, 2, 1, 2, 1]
-expands	0.4	0.66332	[0, 1, 0, 0, 0, 0, 0, 0, 2, 1]
-expel	-1.9	1.44568	[0, -4, -3, -1, -3, -1, 0, -2, -4, -1]
-expelled	-1.0	1.94936	[-1, -2, 2, -2, -4, -3, -2, 1, 2, -1]
-expelling	-1.6	1.49666	[-2, -2, -2, -2, -2, -3, -4, -1, 1, 1]
-expels	-1.6	1.11355	[-4, -2, 0, -3, -1, -1, -1, -2, -1, -1]
-exploit	-0.4	1.62481	[-2, -1, -1, 2, -2, -2, 2, -1, 2, -1]
-exploited	-2.0	1.0	[-3, -3, -1, -1, -1, -4, -2, -2, -1, -2]
-exploiting	-1.9	1.22066	[0, -3, -3, 0, -2, -3, -1, -1, -3, -3]
-exploits	-1.4	0.8	[-2, -2, -2, -1, -1, 0, -2, 0, -2, -2]
-exploration	0.9	0.7	[2, 2, 0, 1, 1, 0, 1, 0, 1, 1]
-explorations	0.3	1.1	[1, 1, 0, 0, 1, 2, 1, -2, -1, 0]
-expose	-0.6	0.8	[-1, -1, 0, 0, -2, 1, -1, 0, -1, -1]
-exposed	-0.3	1.18743	[-2, -1, 0, 2, 0, 0, -1, 1, -2, 0]
-exposes	-0.5	0.92195	[-1, -1, 0, 2, -1, 0, -1, -1, -1, -1]
-exposing	-1.1	0.7	[-2, -2, -1, -1, 0, -2, -1, -1, 0, -1]
-extend	0.7	0.78102	[2, 0, 0, 0, 1, 2, 1, 1, 0, 0]
-extends	0.5	0.80623	[2, 0, 2, 0, 0, 0, 1, 0, 0, 0]
-exuberant	2.8	0.6	[2, 3, 2, 3, 2, 4, 3, 3, 3, 3]
-exultant	3.0	1.18322	[4, 4, 3, 0, 3, 4, 3, 3, 2, 4]
-exultantly	1.4	1.49666	[3, 2, 4, 1, 1, 2, -2, 1, 1, 1]
-fab	2.0	1.0	[2, 1, 1, 3, 1, 2, 2, 4, 3, 1]
-fabulous	2.4	0.8	[2, 2, 3, 4, 3, 3, 1, 2, 2, 2]
-fabulousness	2.8	1.07703	[4, 1, 4, 3, 1, 3, 3, 2, 4, 3]
-fad	0.9	0.83066	[2, 0, 1, 1, 1, 0, 0, 2, 2, 0]
-fag	-2.1	0.83066	[-3, -1, -2, -4, -2, -2, -2, -1, -2, -2]
-faggot	-3.4	0.8	[-2, -4, -4, -3, -2, -4, -4, -4, -3, -4]
-faggots	-3.2	0.9798	[-2, -4, -4, -4, -3, -4, -4, -3, -1, -3]
-fail	-2.5	0.67082	[-2, -3, -3, -3, -4, -2, -2, -2, -2, -2]
-failed	-2.3	0.9	[-2, -3, -1, -2, -2, -1, -3, -3, -4, -2]
-failing	-2.3	1.1	[-2, -3, -3, -3, -4, -1, -2, -2, 0, -3]
-failingly	-1.4	0.8	[-1, -3, -2, -1, 0, -1, -2, -1, -2, -1]
-failings	-2.2	1.07703	[-2, -2, -3, -4, -1, -2, -1, -1, -4, -2]
-faille	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
-fails	-1.8	0.74833	[-2, -3, -2, -3, -2, -2, -1, -1, -1, -1]
-failure	-2.3	1.00499	[-3, -1, -3, -2, -1, -2, -3, -1, -4, -3]
-failures	-2.0	0.63246	[-1, -2, -1, -2, -3, -2, -2, -3, -2, -2]
-fainthearted	-0.3	1.34536	[3, -1, -1, -1, -2, -1, 0, 1, -1, 0]
-fair	1.3	1.00499	[0, 1, 1, 2, 4, 1, 1, 1, 1, 1]
-faith	1.8	0.6	[1, 3, 2, 2, 1, 2, 2, 2, 1, 2]
-faithed	1.3	1.00499	[3, 2, 1, 2, 1, 2, -1, 1, 1, 1]
-faithful	1.9	0.83066	[1, 3, 2, 2, 1, 1, 3, 3, 2, 1]
-faithfully	1.8	1.07703	[3, 1, 2, 2, 4, 1, 0, 1, 2, 2]
-faithfulness	1.9	0.53852	[1, 2, 2, 3, 2, 2, 2, 1, 2, 2]
-faithless	-1.0	0.89443	[-1, -1, -1, -2, -2, -1, -1, 0, 1, -2]
-faithlessly	-0.9	1.51327	[-1, -2, -1, -3, -2, -1, 3, 0, -1, -1]
-faithlessness	-1.8	1.249	[-3, -2, 1, -2, -2, -1, -2, -1, -4, -2]
-faiths	1.8	0.9798	[2, 3, 1, 1, 3, 3, 0, 2, 2, 1]
-fake	-2.1	0.9434	[-2, -2, -1, -1, -1, -3, -3, -4, -2, -2]
-fakes	-1.8	1.07703	[-2, -3, -2, -2, -3, 1, -2, -2, -1, -2]
-faking	-1.8	0.87178	[-3, -1, -2, -1, -2, -2, -3, -2, 0, -2]
-fallen	-1.5	0.80623	[-1, -1, -2, -2, -1, -3, 0, -1, -2, -2]
-falling	-0.6	1.8	[-2, -2, -1, 0, -1, 3, -3, 2, 0, -2]
-falsified	-1.6	0.91652	[-4, -1, -1, -2, -1, -1, -2, -2, -1, -1]
-falsify	-2.0	0.7746	[-2, -1, -3, -3, -1, -2, -2, -2, -1, -3]
-fame	1.9	1.13578	[0, 2, 1, 2, 2, 4, 1, 3, 3, 1]
-fan	1.3	0.78102	[2, 0, 1, 1, 2, 1, 1, 3, 1, 1]
-fantastic	2.6	0.91652	[1, 3, 3, 3, 2, 4, 4, 2, 2, 2]
-fantastical	2.0	1.18322	[-1, 3, 2, 2, 2, 2, 3, 1, 3, 3]
-fantasticalities	2.1	1.04403	[2, 4, 2, 2, 1, 1, 2, 4, 1, 2]
-fantasticality	1.7	1.26886	[4, 1, 0, 2, 2, 1, 4, 1, 1, 1]
-fantasticalness	1.3	1.9	[2, 3, -3, 0, 3, 2, 2, 3, -1, 2]
-fantasticate	1.5	1.96214	[1, 2, -3, 1, 4, 1, 3, 4, 0, 2]
-fantastico	0.4	1.49666	[0, 0, 2, 0, 2, -2, 1, -1, -1, 3]
-farce	-1.7	0.45826	[-2, -2, -1, -2, -2, -1, -1, -2, -2, -2]
-fascinate	2.4	1.0198	[4, 2, 2, 3, 1, 2, 3, 4, 1, 2]
-fascinated	2.1	0.83066	[2, 2, 2, 3, 1, 2, 4, 2, 1, 2]
-fascinates	2.0	0.44721	[2, 3, 1, 2, 2, 2, 2, 2, 2, 2]
-fascination	2.2	0.74833	[2, 1, 3, 3, 2, 3, 2, 2, 1, 3]
-fascinating	2.5	0.92195	[3, 3, 3, 4, 2, 3, 2, 3, 1, 1]
-fascist	-2.6	0.8	[-3, -3, -2, -2, -2, -3, -1, -3, -4, -3]
-fascists	-0.8	1.6	[-2, -3, -1, 1, -1, 2, -3, 1, -1, -1]
-fatal	-2.5	1.62788	[-2, -3, -3, -4, -3, -3, 2, -4, -2, -3]
-fatalism	-0.6	1.8	[0, 0, -3, -4, -1, 1, 0, 2, -2, 1]
-fatalisms	-1.7	0.9	[-2, -4, -2, -2, -2, -1, -1, -1, -1, -1]
-fatalist	-0.5	1.56525	[0, 0, -1, -4, -1, 2, 0, 1, -2, 0]
-fatalistic	-1.0	1.34164	[-3, -1, -3, -1, 1, 0, 1, -2, -1, -1]
-fatalists	-1.2	0.87178	[0, -2, -1, -2, -1, 0, -1, -1, -3, -1]
-fatalities	-2.9	0.7	[-2, -3, -3, -4, -2, -2, -3, -4, -3, -3]
-fatality	-3.5	0.67082	[-2, -4, -4, -4, -3, -4, -4, -4, -3, -3]
-fatally	-3.2	0.74833	[-3, -2, -4, -2, -3, -4, -4, -3, -3, -4]
-fatigue	-1.0	0.7746	[-2, -1, -1, -1, 1, -1, -2, -1, -1, -1]
-fatigued	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -1]
-fatigues	-1.3	1.00499	[-2, -1, -1, -2, -1, 1, -3, -2, -1, -1]
-fatiguing	-1.2	0.6	[-1, -2, -2, -1, 0, -2, -1, -1, -1, -1]
-fatiguingly	-1.5	0.80623	[-1, 0, -3, -2, -1, -1, -2, -1, -2, -2]
-fault	-1.7	0.64031	[-1, -2, -2, -2, -1, -1, -2, -2, -1, -3]
-faulted	-1.4	0.4899	[-2, -2, -1, -2, -1, -1, -1, -1, -2, -1]
-faultfinder	-0.8	1.32665	[-3, -2, -2, -1, 1, 1, 1, -1, -1, -1]
-faultfinders	-1.5	0.80623	[-2, -2, -1, -3, -2, -1, 0, -1, -1, -2]
-faultfinding	-2.1	0.83066	[-3, -2, -1, -2, -1, -3, -1, -3, -2, -3]
-faultier	-2.1	0.7	[-3, -3, -3, -1, -2, -2, -2, -1, -2, -2]
-faultiest	-2.1	0.53852	[-3, -1, -2, -2, -2, -2, -2, -2, -3, -2]
-faultily	-2.0	0.89443	[-2, -2, -2, -3, -2, -1, 0, -3, -2, -3]
-faultiness	-1.5	0.92195	[-1, -1, -3, -1, 0, -2, -3, -1, -2, -1]
-faulting	-1.4	0.4899	[-1, -2, -1, -1, -2, -1, -1, -2, -1, -2]
-faultless	2.0	1.41421	[3, 2, 0, 1, 3, 1, 4, 0, 2, 4]
-faultlessly	2.0	1.09545	[3, 3, 2, 2, 0, 3, 2, 3, 2, 0]
-faultlessness	1.1	2.02237	[3, 2, 4, 2, 1, -1, -2, 1, -2, 3]
-faults	-2.1	0.3	[-2, -2, -2, -2, -2, -2, -3, -2, -2, -2]
-faulty	-1.3	0.45826	[-1, -1, -1, -1, -2, -2, -2, -1, -1, -1]
-fav	2.0	0.63246	[2, 1, 2, 2, 2, 1, 3, 2, 3, 2]
-fave	1.9	1.51327	[1, 3, -2, 3, 2, 3, 1, 3, 2, 3]
-favor	1.7	0.64031	[2, 2, 2, 2, 2, 2, 0, 1, 2, 2]
-favorable	2.1	0.7	[2, 1, 2, 3, 1, 2, 2, 3, 3, 2]
-favorableness	2.2	0.87178	[1, 2, 1, 3, 2, 2, 2, 4, 2, 3]
-favorably	1.6	0.66332	[2, 1, 1, 1, 1, 2, 2, 2, 3, 1]
-favored	1.8	0.6	[2, 2, 1, 1, 3, 1, 2, 2, 2, 2]
-favorer	1.3	1.18743	[2, 2, 1, 1, -2, 1, 2, 2, 2, 2]
-favorers	1.4	0.4899	[2, 2, 1, 2, 1, 2, 1, 1, 1, 1]
-favoring	1.8	0.6	[2, 1, 1, 3, 2, 2, 1, 2, 2, 2]
-favorite	2.0	0.63246	[2, 1, 3, 1, 2, 2, 2, 3, 2, 2]
-favorited	1.7	0.45826	[1, 2, 2, 1, 2, 2, 2, 1, 2, 2]
-favorites	1.8	0.6	[1, 2, 1, 3, 2, 2, 1, 2, 2, 2]
-favoritism	0.7	1.79165	[-1, 3, -1, -1, 2, -2, 2, 2, 3, 0]
-favoritisms	0.7	0.9	[0, 2, -1, 1, 0, 0, 1, 1, 2, 1]
-favors	1.0	0.7746	[2, 1, 1, 1, 2, 1, -1, 1, 1, 1]
-favour	1.9	0.53852	[2, 1, 2, 3, 2, 2, 2, 1, 2, 2]
-favoured	1.8	0.4	[1, 2, 2, 2, 1, 2, 2, 2, 2, 2]
-favourer	1.6	0.4899	[1, 2, 2, 1, 1, 2, 2, 2, 1, 2]
-favourers	1.6	0.66332	[2, 2, 1, 0, 2, 2, 1, 2, 2, 2]
-favouring	1.3	0.45826	[1, 2, 1, 1, 2, 1, 1, 1, 1, 2]
-favours	1.8	0.6	[3, 2, 1, 2, 1, 2, 2, 1, 2, 2]
-fear	-2.2	0.6	[-2, -3, -2, -3, -2, -1, -2, -3, -2, -2]
-feared	-2.2	0.6	[-2, -3, -2, -1, -3, -2, -3, -2, -2, -2]
-fearful	-2.2	0.87178	[-2, -2, -3, -1, -2, -3, -2, -2, -4, -1]
-fearfuller	-2.2	0.87178	[-1, -4, -2, -2, -1, -2, -3, -2, -3, -2]
-fearfullest	-2.5	1.0247	[-3, -3, -4, -4, -3, -2, -1, -2, -2, -1]
-fearfully	-2.2	0.87178	[-2, -2, -2, -1, -1, -3, -4, -2, -3, -2]
-fearfulness	-1.8	0.87178	[-1, -1, -1, -2, -2, -1, -4, -2, -2, -2]
-fearing	-2.7	0.9	[-3, -3, -3, -2, -4, -2, -1, -3, -2, -4]
-fearless	1.9	0.83066	[3, 3, 3, 2, 2, 2, 1, 1, 1, 1]
-fearlessly	1.1	1.22066	[2, -2, 1, 1, 2, 1, 3, 1, 1, 1]
-fearlessness	1.1	1.13578	[3, 2, -1, 2, 0, 2, 1, 1, 1, 0]
-fears	-1.8	0.6	[-2, -2, -3, -2, -2, -1, -1, -2, -1, -2]
-fearsome	-1.7	0.64031	[-3, -1, -1, -2, -1, -2, -2, -2, -1, -2]
-fed up	-1.8	1.249	[-2, -2, -3, -4, -2, -2, -1, -2, -1, 1]
-feeble	-1.2	1.249	[-2, -2, -3, -1, -1, -2, -1, -1, 2, -1]
-feeling	0.5	1.0247	[0, 0, 0, 3, 0, 2, 0, 0, 0, 0]
-felonies	-2.5	0.5	[-3, -3, -3, -2, -2, -2, -2, -3, -2, -3]
-felony	-2.5	1.36015	[-4, -3, -4, -2, -3, -3, -2, -3, -2, 1]
-ferocious	-0.4	1.56205	[1, 1, -2, -3, -1, 2, 1, -2, -1, 0]
-ferociously	-1.1	1.86815	[-3, -4, 2, -2, 0, -2, -1, -1, 2, -2]
-ferociousness	-1.0	1.89737	[2, -4, -2, 0, -2, -3, -1, 0, 2, -2]
-ferocities	-1.0	1.54919	[1, 0, -2, 0, 0, -3, 0, 0, -2, -4]
-ferocity	-0.7	1.67631	[-2, -1, -4, 0, 0, -3, 1, 1, 0, 1]
-fervent	1.1	1.44568	[3, 0, 0, 1, -2, 2, 2, 3, 1, 1]
-fervid	0.5	2.20227	[4, -2, 1, -2, 4, 0, -1, 2, 1, -2]
-festival	2.2	0.6	[2, 2, 3, 2, 3, 2, 2, 2, 3, 1]
-festivalgoer	1.3	1.1	[1, 3, 2, 3, 0, 0, 1, 2, 0, 1]
-festivalgoers	1.2	0.9798	[2, 2, 0, 0, 0, 2, 2, 0, 2, 2]
-festivals	1.5	1.11803	[2, 0, 2, 3, 0, 3, 2, 1, 2, 0]
-festive	2.0	0.63246	[2, 3, 2, 3, 1, 2, 2, 2, 1, 2]
-festively	2.2	0.6	[2, 2, 3, 1, 3, 2, 3, 2, 2, 2]
-festiveness	2.4	0.8	[1, 3, 2, 1, 3, 3, 3, 3, 2, 3]
-festivities	2.1	0.7	[1, 2, 1, 2, 3, 2, 3, 3, 2, 2]
-festivity	2.2	1.07703	[3, 3, 3, 0, 2, 1, 3, 3, 1, 3]
-feud	-1.4	0.66332	[-3, -2, -1, -2, -1, -1, -1, -1, -1, -1]
-feudal	-0.8	0.87178	[-1, -2, -2, 0, 0, 0, -2, -1, 0, 0]
-feudalism	-0.9	1.37477	[-2, -3, -2, -3, 0, 0, 1, 0, 0, 0]
-feudalisms	-0.2	0.74833	[0, 0, 0, 0, 0, 0, -1, 0, -2, 1]
-feudalist	-0.9	1.13578	[-2, -2, -2, -2, 0, 0, 1, 0, 0, -2]
-feudalistic	-1.1	0.7	[0, -1, -1, 0, -2, -1, -2, -1, -2, -1]
-feudalities	-0.4	1.0198	[-1, 0, -1, -2, -1, 0, -1, 0, 0, 2]
-feudality	-0.5	1.28452	[1, -1, 0, -1, 1, 0, -3, -2, 1, -1]
-feudalization	-0.3	1.18743	[-2, -2, 0, 0, 2, 0, -1, -1, 1, 0]
-feudalize	-0.5	0.92195	[-1, 0, -1, 0, -2, 0, 1, 0, 0, -2]
-feudalized	-0.8	1.07703	[-1, -1, -3, 0, 0, 0, 1, -1, -2, -1]
-feudalizes	-0.1	0.53852	[0, 0, -1, 0, -1, 0, 0, 0, 1, 0]
-feudalizing	-0.7	1.34536	[2, -2, -1, 0, 0, -2, -1, -2, 1, -2]
-feudally	-0.6	0.66332	[0, 0, -1, -1, 0, -1, 0, -1, -2, 0]
-feudaries	-0.3	0.9	[0, 0, 0, -2, -2, 0, 0, 0, 0, 1]
-feudary	-0.8	0.74833	[0, 0, -1, -1, -2, 0, -1, 0, -2, -1]
-feudatories	-0.5	0.92195	[-3, 0, -1, 0, 0, 0, 0, -1, 0, 0]
-feudatory	-0.1	0.83066	[-2, 0, 0, 0, 1, 0, 1, -1, 0, 0]
-feuded	-2.2	0.6	[-2, -2, -2, -1, -3, -3, -2, -3, -2, -2]
-feuding	-1.6	0.66332	[-2, -1, -2, -2, -1, -1, -3, -1, -2, -1]
-feudist	-1.1	0.83066	[-2, 0, -3, -1, -1, -1, 0, -1, -1, -1]
-feudists	-0.7	0.9	[0, 0, -1, 0, 0, -2, -2, 0, -2, 0]
-feuds	-1.4	1.0198	[-2, -2, -2, -1, -1, -1, -3, -2, 1, -1]
-fiasco	-2.3	0.64031	[-2, -2, -3, -3, -2, -3, -1, -3, -2, -2]
-fidgety	-1.4	0.66332	[-1, -2, -2, 0, -1, -1, -2, -1, -2, -2]
-fiery	-1.4	0.91652	[0, -1, -1, -2, -2, 0, -3, -1, -2, -2]
-fiesta	2.1	0.7	[3, 2, 1, 2, 2, 1, 3, 3, 2, 2]
-fiestas	1.5	1.0247	[3, 0, 3, 1, 0, 2, 2, 1, 2, 1]
-fight	-1.6	1.56205	[-1, -2, -3, -3, -1, 2, -4, -1, -2, -1]
-fighter	0.6	1.11355	[3, 0, 0, -1, 1, 0, 1, 0, 2, 0]
-fighters	-0.2	1.46969	[-1, 2, -2, 0, 2, 0, -2, -2, 0, 1]
-fighting	-1.5	1.11803	[-1, -2, -3, -2, -2, -2, 0, -3, 0, 0]
-fightings	-1.9	0.53852	[-2, -3, -1, -2, -2, -2, -2, -1, -2, -2]
-fights	-1.7	0.64031	[-2, -2, -1, -2, -2, -1, -3, -1, -1, -2]
-fine	0.8	0.6	[1, 0, 1, 2, 1, 1, 1, 1, 0, 0]
-fire	-1.4	1.49666	[-2, 0, -4, 0, -2, -1, -1, 0, -4, 0]
-fired	-2.6	0.91652	[-2, -3, -4, -3, -3, -1, -3, -3, -1, -3]
-firing	-1.4	0.8	[0, -1, -1, -1, -1, -2, -2, -3, -2, -1]
-fit	1.5	1.0247	[2, 1, 2, 0, 4, 2, 1, 1, 1, 1]
-fitness	1.1	0.9434	[0, 2, 1, 0, 1, 3, 2, 1, 0, 1]
-flagship	0.4	0.91652	[0, 0, 0, 0, 0, 0, 0, 1, 3, 0]
-flatter	0.4	1.42829	[-2, -2, 1, 2, 1, -1, 1, 2, 1, 1]
-flattered	1.6	2.00998	[2, 3, 3, 1, 2, 3, 3, 1, 2, -4]
-flatterer	-0.3	1.9	[-4, 2, -1, 1, 2, 2, -2, -1, -1, -1]
-flatterers	0.3	1.84662	[2, 1, -2, 1, 0, -4, 2, 1, 2, 0]
-flatteries	1.2	1.16619	[2, 2, 3, 1, -1, 0, 0, 1, 2, 2]
-flattering	1.3	2.19317	[3, 2, 2, 3, -4, 4, -1, 2, 1, 1]
-flatteringly	1.0	1.61245	[2, 2, 1, 2, 1, -3, -1, 2, 2, 2]
-flatters	0.6	2.10713	[1, 1, 2, 2, 3, -1, -2, 2, -4, 2]
-flattery	0.4	1.49666	[1, -1, -2, 1, 3, -2, 1, 1, 1, 1]
-flawless	2.3	2.14709	[4, 3, 4, 4, 1, 2, 4, 4, -2, -1]
-flawlessly	0.8	1.83303	[-2, 2, 3, 1, 0, -2, 2, 2, -1, 3]
-flees	-0.7	1.18743	[-3, 0, -2, 0, -1, -1, -1, 1, -1, 1]
-flexibilities	1.0	1.09545	[1, 3, 1, 0, 1, -1, 2, 0, 2, 1]
-flexibility	1.4	0.8	[2, 2, 0, 2, 1, 2, 1, 0, 2, 2]
-flexible	0.9	0.83066	[2, 1, 0, 0, 1, 2, 0, 1, 2, 0]
-flexibly	1.3	0.78102	[2, 1, 0, 0, 1, 2, 2, 1, 2, 2]
-flirtation	1.7	0.64031	[3, 1, 1, 2, 2, 1, 2, 1, 2, 2]
-flirtations	-0.1	1.64012	[0, -4, 1, 0, 0, -2, 1, 1, 2, 0]
-flirtatious	0.5	2.5	[-4, 1, 2, 1, 2, -3, 3, 4, -2, 1]
-flirtatiously	-0.1	1.86815	[2, -1, 1, 2, 1, 1, -3, -3, -2, 1]
-flirtatiousness	0.6	1.85472	[1, 0, 2, 1, 1, 2, 1, -4, -1, 3]
-flirted	-0.2	1.98997	[1, 2, -1, 1, 1, 1, -3, -3, -3, 2]
-flirter	-0.4	1.85472	[1, 2, -1, 0, 1, 1, -3, -3, -3, 1]
-flirters	0.6	2.10713	[1, 4, 0, 1, 2, 1, -4, 2, 1, -2]
-flirtier	-0.1	1.37477	[-2, 1, 1, 1, 1, -2, 1, -1, -2, 1]
-flirtiest	0.4	1.74356	[3, 1, 2, 1, 1, -1, -3, -2, 1, 1]
-flirting	0.8	1.83303	[1, 2, 2, 2, 2, -1, 1, 2, -4, 1]
-flirts	0.7	1.18743	[2, -1, 2, 1, 1, -2, 1, 1, 1, 1]
-flirty	0.6	1.35647	[2, -2, 2, 1, 1, -2, 1, 1, 1, 1]
-flop	-1.4	0.4899	[-1, -1, -2, -1, -2, -1, -2, -1, -2, -1]
-flops	-1.4	0.8	[-2, -2, -2, 0, -2, -1, -2, -1, 0, -2]
-flu	-1.6	0.8	[0, -2, -1, -2, -1, -2, -3, -1, -2, -2]
-flunk	-1.3	0.78102	[-2, -1, -1, -3, -1, -1, 0, -2, -1, -1]
-flunked	-2.1	0.9434	[-4, -1, -3, -2, -1, -1, -3, -2, -2, -2]
-flunker	-1.9	1.04403	[-4, -1, -3, -2, -1, -1, -3, -2, -1, -1]
-flunkers	-1.6	0.8	[-2, -1, -3, -2, 0, -1, -1, -2, -2, -2]
-flunkey	-1.8	0.9798	[-4, -1, -3, -2, -1, -1, -2, -2, -1, -1]
-flunkeys	-0.6	1.2	[-2, -1, -1, 2, -1, 0, -1, -2, 1, -1]
-flunkies	-1.4	1.11355	[-2, -2, 0, -3, 1, -2, -1, -2, -1, -2]
-flunking	-1.5	0.92195	[-2, -1, -1, -3, -1, -1, 0, -2, -3, -1]
-flunks	-1.8	1.32665	[0, -2, -3, -3, -2, -3, -2, -1, 1, -3]
-flunky	-1.8	1.4	[-2, -3, -3, -3, -2, -1, -2, -2, 2, -2]
-flustered	-1.0	1.18322	[-1, -1, -1, -1, -3, -2, 2, -1, -1, -1]
-focused	1.6	0.91652	[2, 2, 1, 3, 0, 1, 1, 2, 3, 1]
-foe	-1.9	1.22066	[-1, -3, -2, -2, -2, -2, -4, 1, -2, -2]
-foehns	0.2	0.4	[1, 0, 0, 0, 0, 0, 0, 0, 1, 0]
-foeman	-1.8	0.6	[-2, -3, -1, -2, -2, -2, -2, -1, -1, -2]
-foemen	-0.3	1.18743	[0, 0, -1, 0, 0, -2, -2, -1, 2, 1]
-foes	-2.0	0.89443	[-2, -1, -2, -2, -4, -3, -2, -1, -1, -2]
-foetal	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
-foetid	-2.3	1.41774	[-1, -3, 0, -2, -3, 0, -3, -3, -4, -4]
-foetor	-3.0	0.89443	[-3, -4, -2, -3, -3, -1, -4, -4, -3, -3]
-foetors	-2.1	1.04403	[-2, -3, -1, -3, -2, -2, 0, -4, -2, -2]
-foetus	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
-foetuses	0.2	0.6	[2, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-fond	1.9	0.83066	[2, 3, 2, 3, 1, 1, 3, 2, 1, 1]
-fondly	1.9	0.7	[1, 2, 3, 2, 2, 3, 2, 1, 1, 2]
-fondness	2.5	0.67082	[3, 2, 2, 2, 2, 3, 4, 3, 2, 2]
-fool	-1.9	0.53852	[-2, -2, -2, -2, -1, -2, -2, -3, -1, -2]
-fooled	-1.6	0.4899	[-2, -1, -1, -2, -2, -1, -2, -1, -2, -2]
-fooleries	-1.8	1.07703	[-1, -2, 0, -2, -1, -2, -4, -2, -3, -1]
-foolery	-1.8	0.87178	[-2, -2, -3, 0, -3, -1, -2, -2, -2, -1]
-foolfish	-0.8	0.87178	[-1, 0, -1, -2, 0, 0, 0, -2, 0, -2]
-foolfishes	-0.4	0.4899	[-1, -1, -1, 0, 0, 0, 0, 0, 0, -1]
-foolhardier	-1.5	0.67082	[-2, -1, -2, -1, -2, -1, -2, -2, 0, -2]
-foolhardiest	-1.3	0.64031	[0, -2, -1, -1, -1, -1, -2, -1, -2, -2]
-foolhardily	-1.0	1.41421	[-1, -1, -2, -2, -2, -2, -1, -1, 3, -1]
-foolhardiness	-1.6	0.66332	[-3, -1, -1, -1, -2, -1, -2, -2, -2, -1]
-foolhardy	-1.4	0.4899	[-2, -2, -1, -1, -1, -2, -1, -1, -2, -1]
-fooling	-1.7	0.64031	[-2, -2, -1, -2, -2, -2, -1, -3, -1, -1]
-foolish	-1.1	0.83066	[-1, -1, -1, -2, -2, -1, -1, -2, 1, -1]
-foolisher	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -2, -3, -2, -1]
-foolishest	-1.4	1.28062	[-2, 1, -2, -3, -2, -2, -1, 1, -2, -2]
-foolishly	-1.8	0.6	[-2, -1, -2, -2, -3, -1, -1, -2, -2, -2]
-foolishness	-1.8	0.6	[-1, -1, -2, -2, -2, -1, -3, -2, -2, -2]
-foolishnesses	-2.0	0.89443	[-1, -1, -1, -2, -3, -1, -3, -3, -2, -3]
-foolproof	1.6	0.91652	[2, 1, 3, 1, 1, 0, 1, 2, 2, 3]
-fools	-2.2	0.74833	[-2, -4, -2, -2, -1, -2, -2, -2, -2, -3]
-foolscaps	-0.8	0.6	[0, -1, -1, -1, 0, -1, -2, 0, -1, -1]
-forbid	-1.3	0.78102	[-2, -2, -1, -1, -1, -1, 0, -1, -1, -3]
-forbiddance	-1.4	1.35647	[-3, -1, -2, -3, -1, 2, -1, -2, -2, -1]
-forbiddances	-1.0	2.0	[-2, 3, 1, -2, -4, -2, -3, -1, -1, 1]
-forbidden	-1.8	0.74833	[-1, -2, -2, -2, -1, -1, -3, -3, -2, -1]
-forbidder	-1.6	0.66332	[-1, -2, -2, -2, -2, 0, -2, -2, -2, -1]
-forbidders	-1.5	0.80623	[-1, -2, -1, -3, -2, -2, 0, -2, -1, -1]
-forbidding	-1.9	0.7	[-3, -1, -1, -2, -2, -1, -3, -2, -2, -2]
-forbiddingly	-1.9	0.53852	[-2, -1, -2, -2, -2, -2, -3, -2, -1, -2]
-forbids	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -2, -1, -1]
-forced	-2.0	0.63246	[-1, -2, -3, -3, -1, -2, -2, -2, -2, -2]
-foreclosure	-0.5	1.43178	[-1, -2, -3, 2, -1, 1, -1, 0, 1, -1]
-foreclosures	-2.4	0.66332	[-3, -2, -3, -2, -3, -3, -1, -2, -2, -3]
-forgave	1.4	0.91652	[2, 2, 1, 2, 1, -1, 1, 2, 2, 2]
-forget	-0.9	0.53852	[-1, -1, -1, -1, 0, -1, -1, 0, -2, -1]
-forgetful	-1.1	1.3	[-3, -1, -2, 1, 0, -2, 1, -1, -2, -2]
-forgivable	1.7	0.64031	[2, 1, 2, 1, 2, 2, 1, 2, 3, 1]
-forgivably	1.6	0.66332	[1, 1, 2, 1, 2, 2, 1, 2, 3, 1]
-forgive	1.1	1.22066	[2, 1, 1, 3, 1, 1, 1, 2, -2, 1]
-forgiven	1.6	0.66332	[2, 1, 1, 3, 2, 2, 1, 2, 1, 1]
-forgiveness	1.1	1.22066	[2, 1, 1, 1, 3, 2, -2, 1, 1, 1]
-forgiver	1.7	0.78102	[3, 1, 1, 3, 1, 2, 1, 2, 2, 1]
-forgivers	1.2	0.6	[2, 1, 2, 1, 0, 1, 1, 2, 1, 1]
-forgives	1.7	0.78102	[2, 1, 3, 1, 1, 3, 2, 1, 1, 2]
-forgiving	1.9	0.7	[2, 3, 2, 1, 2, 3, 1, 1, 2, 2]
-forgivingly	1.4	0.4899	[2, 1, 2, 1, 1, 1, 2, 1, 2, 1]
-forgivingness	1.8	0.6	[3, 1, 2, 1, 2, 2, 2, 2, 2, 1]
-forgotten	-0.9	0.53852	[-1, 0, -1, 0, -1, -1, -1, -1, -2, -1]
-fortunate	1.9	0.53852	[2, 2, 1, 1, 2, 2, 2, 3, 2, 2]
-fought	-1.3	0.78102	[-2, -1, -2, -1, 0, -1, -1, -1, -1, -3]
-foughten	-1.9	1.3	[-1, -3, 0, -2, -4, -3, -2, 0, -1, -3]
-frantic	-1.9	0.7	[-3, -2, -2, -1, -2, -1, -2, -3, -1, -2]
-frantically	-1.4	0.4899	[-2, -1, -2, -1, -1, -1, -1, -1, -2, -2]
-franticness	-0.7	1.18743	[-1, -2, 2, -1, -1, -1, 1, -2, -1, -1]
-fraud	-2.8	0.6	[-3, -3, -2, -3, -2, -3, -3, -2, -4, -3]
-frauds	-2.3	0.45826	[-2, -2, -2, -3, -3, -2, -3, -2, -2, -2]
-fraudster	-2.5	0.92195	[-4, -1, -2, -2, -4, -2, -3, -2, -3, -2]
-fraudsters	-2.4	0.91652	[-4, -3, -3, -3, -1, -2, -2, -2, -1, -3]
-fraudulence	-2.3	0.78102	[-3, -2, -2, -3, -2, -1, -2, -4, -2, -2]
-fraudulent	-2.2	0.6	[-2, -3, -2, -2, -2, -1, -3, -3, -2, -2]
-freak	-1.9	0.9434	[-3, -2, -1, -2, -4, -1, -2, -1, -2, -1]
-freaked	-1.2	1.32665	[-2, -2, 1, 0, -1, -2, -3, 1, -2, -2]
-freakier	-1.3	1.1	[-3, -2, -2, 1, -2, -2, -1, 0, -1, -1]
-freakiest	-1.6	1.0198	[-2, -3, -3, -3, -1, -1, -1, 0, -1, -1]
-freakiness	-1.4	0.8	[-1, -1, -1, -2, -3, 0, -2, -1, -2, -1]
-freaking	-1.8	1.16619	[0, -4, -3, -2, -3, -1, -1, -1, -2, -1]
-freakish	-2.1	1.37477	[-1, -3, -2, -1, -2, -3, -4, -3, 1, -3]
-freakishly	-0.8	1.249	[-2, -2, 1, -2, -1, 1, -1, 1, -1, -2]
-freakishness	-1.4	1.68523	[-2, -4, -1, 0, -1, -2, 1, 1, -4, -2]
-freakout	-1.8	1.6	[-3, 1, -3, -2, -3, -1, -4, 1, -2, -2]
-freakouts	-1.5	0.92195	[-2, -2, -1, -1, -2, -2, -2, 1, -2, -2]
-freaks	-0.4	1.35647	[2, 0, -2, -1, 0, 1, -2, 1, -1, -2]
-freaky	-1.5	1.20416	[-2, -2, -2, -2, -1, -2, 2, -2, -2, -2]
-free	2.3	0.9	[2, 4, 3, 3, 2, 1, 2, 3, 1, 2]
-freebase	-0.1	1.44568	[2, 0, -2, 1, -3, 0, -1, 0, 1, 1]
-freebased	0.8	1.16619	[2, 0, -1, 0, 3, 0, 1, 2, 1, 0]
-freebases	0.8	1.249	[2, 0, -1, 0, 2, 0, 0, 3, 2, 0]
-freebasing	-0.4	1.56205	[-4, -2, 0, 0, 1, 2, 0, -1, 0, 0]
-freebee	1.3	0.78102	[1, 2, 1, 1, 1, 0, 3, 2, 1, 1]
-freebees	1.3	1.26886	[2, 2, -2, 2, 2, 2, 0, 2, 1, 2]
-freebie	1.8	0.9798	[2, 1, 3, 2, 2, 4, 1, 1, 1, 1]
-freebies	1.8	0.9798	[2, 3, 1, 1, 2, 4, 1, 1, 2, 1]
-freeboard	0.3	0.64031	[0, 0, 0, 0, 0, 1, 0, 0, 0, 2]
-freeboards	0.7	0.9	[0, 0, 0, 1, 0, 0, 2, 2, 2, 0]
-freeboot	-0.7	1.67631	[1, -2, -3, -2, -1, -2, -1, 2, -1, 2]
-freebooter	-1.7	1.00499	[-2, -2, -3, -3, -2, -2, 0, -1, 0, -2]
-freebooters	-0.2	1.32665	[-1, -3, 1, 0, -2, 1, 0, 1, 0, 1]
-freebooting	-0.8	1.249	[-2, -2, -1, 2, -1, -1, -1, 1, -2, -1]
-freeborn	1.2	0.74833	[1, 0, 3, 1, 1, 1, 1, 1, 2, 1]
-freed	1.7	1.34536	[-2, 2, 3, 2, 2, 2, 3, 1, 2, 2]
-freedman	1.1	0.9434	[1, 2, 0, 1, 2, 1, 3, 0, 0, 1]
-freedmen	0.7	0.78102	[1, 2, 1, 2, 0, 1, 0, 0, 0, 0]
-freedom	3.2	0.9798	[4, 4, 1, 3, 2, 4, 4, 3, 3, 4]
-freedoms	1.2	1.07703	[2, 1, 1, 3, 2, 1, 2, 1, -1, 0]
-freedwoman	1.6	1.74356	[3, 2, 0, 4, 4, 3, 1, -1, 0, 0]
-freedwomen	1.3	0.78102	[2, 0, 2, 0, 2, 1, 1, 1, 2, 2]
-freeform	0.9	0.83066	[0, 0, 0, 2, 1, 2, 1, 1, 2, 0]
-freehand	0.5	0.80623	[0, 0, 0, 1, 0, 2, 0, 2, 0, 0]
-freehanded	1.4	0.91652	[3, 0, 0, 2, 1, 2, 2, 1, 2, 1]
-freehearted	1.5	0.67082	[2, 0, 1, 2, 2, 2, 2, 1, 1, 2]
-freehold	0.7	0.78102	[1, 1, 0, 0, 2, 0, 2, 0, 1, 0]
-freeholder	0.5	0.5	[1, 1, 0, 0, 0, 1, 1, 0, 1, 0]
-freeholders	0.1	0.83066	[0, 0, 1, 0, 0, 1, 0, -2, 0, 1]
-freeholds	1.0	0.63246	[1, 0, 2, 0, 1, 2, 1, 1, 1, 1]
-freeing	2.1	1.04403	[2, 1, 1, 1, 4, 2, 2, 4, 2, 2]
-freelance	1.2	1.66132	[3, 0, 0, 0, 0, 1, 4, 0, 4, 0]
-freelanced	0.7	1.00499	[3, 0, 0, 0, 0, 2, 1, 0, 1, 0]
-freelancer	1.1	1.04403	[2, 0, 3, 2, 1, 0, 0, 0, 2, 1]
-freelancers	0.4	0.66332	[0, 0, 0, 2, 0, 0, 0, 1, 1, 0]
-freelances	0.7	0.9	[1, 0, 0, 0, 0, 2, 2, 0, 2, 0]
-freelancing	0.4	0.66332	[2, 0, 0, 0, 1, 0, 0, 0, 1, 0]
-freeload	-1.9	1.04403	[-2, -3, -1, -2, -1, 0, -1, -3, -3, -3]
-freeloaded	-1.6	0.8	[-2, 0, -3, -1, -1, -2, -2, -2, -2, -1]
-freeloader	-0.7	1.00499	[-2, 0, -1, -2, -1, 1, -1, 1, -1, -1]
-freeloaders	-0.1	1.57797	[-2, -2, -1, 0, 0, 2, -2, 0, 2, 2]
-freeloading	-1.3	2.0025	[1, -2, -4, -2, -3, -3, 1, 2, 0, -3]
-freeloads	-1.3	0.9	[-1, -1, -2, -2, -2, 0, 0, -1, -1, -3]
-freely	1.9	0.53852	[2, 1, 2, 2, 2, 3, 2, 2, 1, 2]
-freeman	1.7	0.78102	[2, 2, 2, 1, 2, 0, 3, 1, 2, 2]
-freemartin	-0.5	0.92195	[0, 0, 0, -1, 0, -1, 0, 0, -3, 0]
-freemasonries	0.7	0.78102	[0, 1, 0, 0, 0, 1, 1, 0, 2, 2]
-freemasonry	0.3	0.64031	[1, 0, 2, 0, 0, 0, 0, 0, 0, 0]
-freemen	1.5	0.67082	[1, 1, 0, 2, 2, 2, 2, 2, 1, 2]
-freeness	1.6	0.66332	[1, 2, 3, 2, 2, 1, 1, 1, 2, 1]
-freenesses	1.7	0.78102	[1, 2, 1, 2, 2, 2, 3, 2, 2, 0]
-freer	1.1	0.7	[2, 2, 0, 2, 1, 1, 1, 0, 1, 1]
-freers	1.0	0.89443	[0, 1, 1, 2, 3, 1, 0, 1, 0, 1]
-frees	1.2	0.6	[1, 2, 0, 1, 1, 1, 2, 1, 1, 2]
-freesia	0.4	0.91652	[0, 0, 3, 0, 1, 0, 0, 0, 0, 0]
-freesias	0.4	0.66332	[0, 0, 0, 1, 1, 2, 0, 0, 0, 0]
-freest	1.6	1.28062	[3, 4, 0, 3, 0, 1, 1, 2, 1, 1]
-freestanding	1.1	0.83066	[2, 1, 1, 2, 0, 0, 0, 2, 1, 2]
-freestyle	0.7	0.9	[2, 0, 1, 0, 2, 0, 0, 2, 0, 0]
-freestyler	0.4	0.91652	[0, 0, 0, 0, 1, 0, 0, 0, 0, 3]
-freestylers	0.8	0.87178	[2, 1, 0, 0, 0, 1, 0, 2, 2, 0]
-freestyles	0.3	0.64031	[0, 0, 0, 0, 1, 0, 0, 0, 0, 2]
-freethinker	1.0	0.63246	[1, 2, 1, 1, 2, 1, 0, 0, 1, 1]
-freethinkers	1.0	0.7746	[1, 0, 0, 1, 2, 2, 1, 2, 0, 1]
-freethinking	1.1	0.7	[1, 0, 1, 1, 2, 2, 0, 2, 1, 1]
-freeware	0.7	1.48661	[1, 0, 0, 2, 4, 0, 1, -2, 1, 0]
-freeway	0.2	0.6	[0, 0, 0, 0, 0, 0, 2, 0, 0, 0]
-freewheel	0.5	1.11803	[2, 0, 1, 2, 0, -2, 0, 0, 1, 1]
-freewheeled	0.3	0.78102	[1, 0, 0, 0, 0, 1, 2, -1, 0, 0]
-freewheeler	0.2	0.87178	[-2, 1, 0, 0, 0, 1, 1, 1, 0, 0]
-freewheelers	-0.3	1.00499	[-2, 0, 0, 0, 2, -1, -1, 0, -1, 0]
-freewheeling	0.5	1.11803	[-1, 2, 0, -1, 1, 2, 2, 0, 0, 0]
-freewheelingly	0.8	0.87178	[1, 2, 0, 0, 1, 2, 1, -1, 1, 1]
-freewheels	0.6	0.91652	[0, 3, 1, 1, 1, 0, 0, 0, 0, 0]
-freewill	1.0	0.7746	[1, 1, 1, -1, 1, 1, 1, 2, 2, 1]
-freewriting	0.8	1.07703	[0, 2, 0, 0, 1, 0, 3, 0, 2, 0]
-freeze	0.2	0.9798	[-1, 0, 1, 1, -1, 0, 0, -1, 2, 1]
-freezers	-0.1	0.3	[0, 0, 0, -1, 0, 0, 0, 0, 0, 0]
-freezes	-0.1	1.13578	[0, -2, -2, 1, 0, 0, 0, 0, 2, 0]
-freezing	-0.4	1.28062	[-2, -1, -2, -2, 0, 0, 0, 1, 2, 0]
-freezingly	-1.6	0.4899	[-1, -2, -2, -1, -2, -2, -2, -2, -1, -1]
-frenzy	-1.3	1.48661	[-1, -1, -2, -2, 2, -4, -1, -2, 0, -2]
-fresh	1.3	0.45826	[2, 2, 1, 1, 1, 1, 2, 1, 1, 1]
-friend	2.2	0.6	[2, 2, 3, 2, 3, 3, 1, 2, 2, 2]
-friended	1.7	0.78102	[2, 2, 1, 3, 1, 1, 2, 3, 1, 1]
-friending	1.8	1.07703	[1, 4, 2, 0, 1, 3, 2, 2, 1, 2]
-friendless	-1.5	0.67082	[-1, -2, -2, -1, 0, -2, -1, -2, -2, -2]
-friendlessness	-0.3	2.05183	[-2, -2, 2, 1, -4, -1, 2, 1, -2, 2]
-friendlier	2.0	0.63246	[3, 2, 2, 1, 2, 2, 2, 1, 3, 2]
-friendlies	2.2	0.74833	[3, 2, 2, 3, 2, 2, 1, 3, 1, 3]
-friendliest	2.6	0.91652	[3, 3, 1, 3, 2, 1, 3, 3, 4, 3]
-friendlily	1.8	0.74833	[1, 2, 2, 1, 3, 1, 1, 2, 3, 2]
-friendliness	2.0	0.7746	[3, 1, 3, 2, 2, 3, 2, 1, 2, 1]
-friendly	2.2	0.6	[2, 1, 3, 3, 2, 2, 3, 2, 2, 2]
-friends	2.1	0.53852	[3, 3, 2, 2, 2, 1, 2, 2, 2, 2]
-friendship	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
-friendships	1.6	0.91652	[2, 1, 1, 0, 3, 2, 2, 3, 1, 1]
-fright	-1.6	1.35647	[-2, -1, 0, -3, -2, -4, 1, -1, -2, -2]
-frighted	-1.4	0.91652	[0, -1, -1, -1, -2, -1, -3, -1, -1, -3]
-frighten	-1.4	0.8	[0, -1, -1, -1, -2, -1, -3, -2, -1, -2]
-frightened	-1.9	0.7	[-2, -3, -1, -1, -2, -2, -3, -1, -2, -2]
-frightening	-2.2	0.9798	[-1, -1, -4, -3, -3, -3, -2, -2, -1, -2]
-frighteningly	-2.1	0.7	[-2, -2, -2, -2, -4, -2, -1, -2, -2, -2]
-frightens	-1.7	0.78102	[-2, -1, -2, -1, -1, -1, -2, -3, -3, -1]
-frightful	-2.3	0.78102	[-2, -2, -2, -2, -3, -2, -3, -1, -4, -2]
-frightfully	-1.7	0.78102	[-1, -1, -1, -2, -2, -1, -2, -3, -1, -3]
-frightfulness	-1.9	0.7	[-1, -1, -2, -3, -3, -2, -1, -2, -2, -2]
-frighting	-1.5	0.67082	[-1, -2, -2, -3, -1, -1, -1, -1, -2, -1]
-frights	-1.1	0.83066	[-2, 0, -2, 0, -2, -1, 0, -1, -1, -2]
-frisky	1.0	1.48324	[1, -2, 1, 1, 1, 3, 3, 2, -1, 1]
-frowning	-1.4	1.42829	[-1, -1, -1, -3, -3, 1, -2, -3, 1, -2]
-frustrate	-2.0	0.63246	[-2, -3, -2, -1, -3, -2, -2, -1, -2, -2]
-frustrated	-2.4	0.66332	[-2, -1, -3, -3, -2, -2, -3, -2, -3, -3]
-frustrates	-1.9	0.7	[-1, -1, -3, -2, -1, -2, -2, -2, -3, -2]
-frustrating	-1.9	0.83066	[-2, -2, -1, -1, -1, -2, -2, -2, -4, -2]
-frustratingly	-2.0	0.63246	[-1, -3, -2, -2, -2, -2, -2, -3, -2, -1]
-frustration	-2.1	0.7	[-3, -2, -3, -2, -1, -2, -3, -2, -1, -2]
-frustrations	-2.0	0.7746	[-2, -1, -1, -3, -2, -2, -3, -3, -2, -1]
-fuck	-2.5	1.20416	[0, -3, -4, -3, -2, -3, -4, -1, -2, -3]
-fucked	-3.4	0.66332	[-2, -3, -4, -3, -4, -4, -3, -4, -3, -4]
-fucker	-3.3	0.78102	[-3, -4, -4, -2, -3, -4, -4, -2, -4, -3]
-fuckers	-2.9	0.9434	[-3, -3, -4, -3, -4, -4, -2, -1, -2, -3]
-fuckface	-3.2	1.07703	[-4, -2, -4, -1, -4, -4, -2, -4, -3, -4]
-fuckhead	-3.1	1.04403	[-1, -4, -2, -4, -3, -3, -2, -4, -4, -4]
-fucks	-2.1	1.13578	[-3, -2, -1, -1, -1, -2, -4, -2, -4, -1]
-fucktard	-3.1	0.9434	[-4, -4, -4, -3, -4, -2, -4, -2, -2, -2]
-fud	-1.1	1.37477	[-1, -3, -1, -1, -3, -2, 2, 0, -1, -1]
-fuked	-2.5	0.92195	[-2, -3, -3, -3, -3, -3, 0, -3, -3, -2]
-fuking	-3.2	0.9798	[-4, -1, -3, -4, -3, -2, -4, -3, -4, -4]
-fulfill	1.9	1.04403	[1, 1, 2, 4, 1, 1, 2, 1, 3, 3]
-fulfilled	1.8	0.87178	[1, 2, 1, 0, 2, 2, 3, 2, 2, 3]
-fulfills	1.0	1.09545	[2, 1, 1, 1, 1, -2, 2, 2, 1, 1]
-fume	-1.2	1.16619	[0, 0, 0, -2, -3, -2, -1, -3, -1, 0]
-fumed	-1.8	0.87178	[-3, -2, -3, -2, -2, 0, -2, -1, -1, -2]
-fumeless	0.3	0.64031	[0, 0, 0, 1, 0, 0, 0, 2, 0, 0]
-fumelike	-0.7	1.18743	[0, 0, -3, 0, 0, -2, -1, -2, 1, 0]
-fumer	0.7	0.9	[2, 1, 0, 1, 0, 2, 0, -1, 1, 1]
-fumers	-0.8	0.6	[0, -1, -1, -2, -1, 0, 0, -1, -1, -1]
-fumes	-0.1	1.13578	[0, -2, 0, 0, -1, 1, -1, -1, 1, 2]
-fumet	0.4	1.0198	[2, 0, 0, -1, 0, 1, -1, 0, 2, 1]
-fumets	-0.4	0.66332	[0, -1, 0, -1, 0, 0, -2, 0, 0, 0]
-fumette	-0.6	1.11355	[-2, -2, 0, -1, -1, 2, 0, 0, -1, -1]
-fuming	-2.7	0.64031	[-2, -3, -3, -2, -3, -4, -3, -2, -2, -3]
-fun	2.3	0.45826	[2, 3, 2, 3, 2, 2, 3, 2, 2, 2]
-funeral	-1.5	1.74642	[-2, -3, -2, -1, -3, -1, -4, 1, 2, -2]
-funerals	-1.6	2.2891	[-3, -4, -1, -4, 2, -3, -3, 2, 1, -3]
-funky	-0.4	1.62481	[0, -1, 2, -1, 2, 0, -4, -1, 0, -1]
-funned	2.3	0.9	[2, 3, 3, 4, 1, 2, 2, 2, 3, 1]
-funnel	0.1	0.53852	[1, 0, 0, 0, 0, -1, 0, 0, 1, 0]
-funneled	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
-funnelform	0.5	0.80623	[0, 0, 1, 0, 0, 0, 0, 2, 2, 0]
-funneling	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
-funnelled	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
-funnelling	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
-funnels	0.4	0.66332	[0, 0, 0, 1, 0, 0, 0, 0, 2, 1]
-funner	2.2	0.74833	[2, 2, 3, 4, 1, 2, 2, 2, 2, 2]
-funnest	2.9	0.7	[4, 3, 4, 3, 2, 3, 2, 3, 2, 3]
-funnier	1.7	1.00499	[2, 2, -1, 2, 2, 2, 3, 1, 2, 2]
-funnies	1.3	1.00499	[2, 1, -1, 2, 1, 2, 3, 1, 1, 1]
-funniest	2.6	0.8	[3, 3, 3, 3, 2, 2, 1, 2, 4, 3]
-funnily	1.9	0.53852	[2, 3, 1, 2, 2, 2, 2, 1, 2, 2]
-funniness	1.8	0.9798	[3, 2, 3, 2, 2, 1, 3, 0, 1, 1]
-funninesses	1.6	0.91652	[1, 3, 0, 3, 1, 2, 1, 2, 2, 1]
-funning	1.8	0.9798	[2, 2, 1, 2, 1, 4, 0, 2, 2, 2]
-funny	1.9	0.53852	[3, 2, 2, 1, 2, 2, 1, 2, 2, 2]
-funnyman	1.4	0.4899	[2, 2, 1, 2, 1, 1, 1, 1, 2, 1]
-funnymen	1.3	1.1	[2, 1, 1, 0, 0, 3, 3, 1, 2, 0]
-furious	-2.7	1.41774	[-3, -3, -3, -4, -4, -4, 1, -2, -3, -2]
-furiously	-1.9	1.04403	[-2, -2, -4, -2, -1, -2, -1, -3, 0, -2]
-fury	-2.7	0.78102	[-4, -3, -2, -2, -2, -3, -4, -2, -3, -2]
-futile	-1.9	0.83066	[0, -3, -2, -2, -2, -2, -3, -1, -2, -2]
-gag	-1.4	1.0198	[-2, -2, -1, -2, 0, -2, -3, 0, 0, -2]
-gagged	-1.3	1.55242	[-2, -2, -1, -2, 2, -3, -1, -3, 1, -2]
-gain	2.4	0.4899	[2, 3, 2, 2, 3, 2, 3, 2, 3, 2]
-gained	1.6	0.66332	[2, 1, 2, 1, 1, 3, 2, 1, 2, 1]
-gaining	1.8	0.4	[1, 2, 2, 2, 1, 2, 2, 2, 2, 2]
-gains	1.4	0.4899	[1, 2, 1, 2, 2, 2, 1, 1, 1, 1]
-gallant	1.7	1.1	[4, 0, 3, 1, 1, 2, 2, 2, 1, 1]
-gallantly	1.9	0.53852	[2, 2, 3, 2, 2, 2, 2, 1, 2, 1]
-gallantry	2.6	0.8	[3, 3, 1, 2, 2, 3, 4, 2, 3, 3]
-geek	-0.8	0.9798	[0, 0, 0, -2, -3, -1, -1, 0, 0, -1]
-geekier	0.2	1.4	[0, 3, -1, -1, -1, 1, 2, 1, -1, -1]
-geekiest	-0.1	0.9434	[1, -1, -1, -1, -1, 1, 1, 1, 0, -1]
-geeks	-0.4	0.91652	[0, 0, -1, 0, 0, 0, 0, 0, -3, 0]
-geeky	-0.6	0.91652	[0, 0, -1, 0, -1, 0, -1, 0, -3, 0]
-generosities	2.6	0.4899	[3, 3, 2, 3, 2, 3, 2, 3, 2, 3]
-generosity	2.3	0.64031	[3, 1, 2, 2, 3, 2, 3, 3, 2, 2]
-generous	2.3	0.78102	[3, 2, 4, 2, 2, 1, 2, 3, 2, 2]
-generously	1.8	0.74833	[3, 3, 2, 1, 2, 1, 1, 2, 1, 2]
-generousness	2.4	0.91652	[3, 2, 3, 1, 3, 4, 3, 2, 2, 1]
-genial	1.8	0.6	[3, 1, 2, 1, 2, 2, 1, 2, 2, 2]
-gentle	1.9	0.53852	[2, 2, 2, 1, 2, 3, 2, 2, 1, 2]
-gentler	1.4	0.4899	[2, 1, 1, 1, 1, 2, 2, 1, 2, 1]
-gentlest	1.8	0.4	[2, 1, 2, 2, 2, 1, 2, 2, 2, 2]
-gently	2.0	0.7746	[2, 2, 2, 1, 1, 3, 3, 2, 1, 3]
-ghost	-1.3	1.34536	[-2, 0, 0, 0, 0, -3, -2, -3, 0, -3]
-giddy	-0.6	1.62481	[-2, -2, 3, -1, -1, -1, -1, -2, 2, -1]
-gift	1.9	0.53852	[2, 1, 2, 2, 2, 1, 2, 3, 2, 2]
-giggle	1.8	0.9798	[2, 2, 2, 2, 2, 3, 2, -1, 2, 2]
-giggled	1.5	1.20416	[1, 3, 1, 3, 3, 1, 1, -1, 2, 1]
-giggler	0.6	0.8	[1, 1, 1, 1, -1, 1, 1, 1, -1, 1]
-gigglers	1.4	0.4899	[1, 2, 2, 1, 2, 1, 1, 1, 1, 2]
-giggles	0.8	1.249	[1, 2, 2, 1, -1, 1, 1, 2, -2, 1]
-gigglier	1.0	1.09545	[2, 1, 1, 2, 2, 1, -1, 2, 1, -1]
-giggliest	1.7	1.26886	[4, 2, 1, 2, 1, 3, 2, 2, -1, 1]
-giggling	1.5	0.5	[2, 2, 1, 2, 2, 1, 1, 1, 1, 2]
-gigglingly	1.1	1.37477	[1, 2, 1, 1, -1, 2, 1, -1, 4, 1]
-giggly	1.0	1.41421	[1, 2, -2, 1, 2, 3, 1, -1, 2, 1]
-giver	1.4	0.66332	[1, 2, 2, 0, 1, 2, 1, 2, 1, 2]
-givers	1.7	1.34536	[2, -1, 3, 3, 3, 1, 1, 2, 0, 3]
-giving	1.4	1.0198	[1, 1, 3, 1, 1, 2, 3, 0, 2, 0]
-glad	2.0	0.63246	[3, 2, 1, 2, 2, 2, 1, 3, 2, 2]
-gladly	1.4	0.4899	[2, 2, 1, 2, 1, 1, 2, 1, 1, 1]
-glamor	2.1	0.9434	[1, 2, 2, 2, 1, 3, 2, 4, 3, 1]
-glamorise	1.3	1.1	[0, 1, 4, 1, 0, 2, 1, 2, 1, 1]
-glamorised	1.8	0.74833	[1, 2, 2, 2, 2, 2, 0, 2, 3, 2]
-glamorises	2.1	1.04403	[1, 3, 2, 4, 2, 2, 0, 2, 3, 2]
-glamorising	1.2	1.16619	[3, 2, 0, 3, 1, 2, 0, 1, 0, 0]
-glamorization	1.6	0.91652	[2, 2, 3, 0, 3, 1, 2, 1, 1, 1]
-glamorize	1.7	1.1	[1, 2, 1, 4, 2, 0, 3, 1, 2, 1]
-glamorized	2.1	1.04403	[3, 2, 1, 2, 4, 2, 2, 0, 3, 2]
-glamorizer	2.4	1.0198	[3, 2, 2, 3, 4, 3, 2, 0, 3, 2]
-glamorizers	1.6	1.11355	[4, 1, 1, 1, 1, 2, 0, 2, 3, 1]
-glamorizes	2.4	1.2	[3, 2, 2, 4, 4, 1, 2, 0, 3, 3]
-glamorizing	1.8	1.16619	[3, 0, 1, 2, 3, 2, 1, 0, 3, 3]
-glamorous	2.3	0.78102	[3, 2, 4, 2, 2, 2, 3, 2, 2, 1]
-glamorously	2.1	1.04403	[1, 3, 2, 1, 2, 1, 4, 1, 3, 3]
-glamors	1.4	0.66332	[1, 1, 2, 2, 2, 1, 2, 2, 0, 1]
-glamour	2.4	0.91652	[2, 4, 2, 1, 3, 2, 2, 2, 2, 4]
-glamourize	0.8	1.32665	[2, 1, 0, 1, 0, 4, 0, 0, -1, 1]
-glamourless	-1.6	1.49666	[-4, -1, -1, -2, -2, -3, -2, -1, 2, -2]
-glamourous	2.0	0.7746	[1, 3, 3, 2, 1, 2, 2, 2, 3, 1]
-glamours	1.9	0.83066	[1, 3, 2, 2, 3, 2, 1, 1, 3, 1]
-glee	3.2	0.4	[3, 4, 3, 3, 4, 3, 3, 3, 3, 3]
-gleeful	2.9	0.53852	[3, 3, 3, 3, 3, 4, 2, 2, 3, 3]
-gloom	-2.6	0.66332	[-4, -2, -3, -3, -2, -3, -2, -2, -2, -3]
-gloomed	-1.9	0.7	[-1, -2, -3, -1, -2, -2, -1, -2, -3, -2]
-gloomful	-2.1	0.9434	[-3, -1, -4, -2, -1, -1, -2, -3, -2, -2]
-gloomier	-1.5	1.20416	[-3, -2, -2, -3, -1, -2, 0, 1, -1, -2]
-gloomiest	-1.8	2.03961	[-2, -2, 2, -4, -2, -3, -4, -3, 2, -2]
-gloominess	-1.8	0.6	[-2, -1, -2, -3, -2, -1, -2, -2, -2, -1]
-gloominesses	-1.0	1.09545	[-1, -2, -2, -1, -1, -2, 2, -1, -1, -1]
-glooming	-1.8	0.74833	[-1, -2, -2, -1, -2, -1, -3, -1, -3, -2]
-glooms	-0.9	1.57797	[3, -2, -1, -2, -2, -2, 1, -2, -1, -1]
-gloomy	-0.6	1.56205	[2, -1, -2, -2, -2, -1, 1, -2, 2, -1]
-gloried	2.4	1.0198	[2, 3, 3, 4, 4, 1, 1, 2, 2, 2]
-glories	2.1	1.3	[4, 1, 4, 1, 1, 4, 2, 2, 1, 1]
-glorification	2.0	0.89443	[3, 1, 3, 2, 3, 1, 1, 3, 2, 1]
-glorified	2.3	0.9	[1, 4, 2, 2, 4, 2, 2, 2, 2, 2]
-glorifier	2.3	1.00499	[1, 4, 1, 2, 4, 2, 3, 2, 2, 2]
-glorifiers	1.6	1.0198	[2, 1, 2, -1, 2, 2, 2, 1, 2, 3]
-glorifies	2.2	0.9798	[1, 4, 2, 2, 4, 2, 1, 2, 2, 2]
-glorify	2.7	0.78102	[3, 3, 4, 3, 1, 3, 2, 3, 2, 3]
-glorifying	2.4	1.28062	[3, 4, 2, 2, 4, 4, 0, 1, 2, 2]
-gloriole	1.5	1.36015	[2, 4, 1, 2, 0, -1, 1, 3, 2, 1]
-glorioles	1.2	0.87178	[0, 2, 0, 2, 0, 1, 2, 2, 1, 2]
-glorious	3.2	0.6	[4, 3, 3, 2, 3, 3, 3, 4, 3, 4]
-gloriously	2.9	0.83066	[3, 4, 3, 2, 4, 2, 2, 2, 4, 3]
-gloriousness	2.6	1.0198	[3, 2, 3, 4, 3, 2, 1, 4, 3, 1]
-glory	2.5	0.80623	[1, 3, 3, 1, 3, 3, 3, 2, 3, 3]
-glum	-2.1	0.7	[-2, -1, -3, -3, -1, -2, -2, -3, -2, -2]
-gn8	0.6	0.66332	[1, 1, 0, 0, 0, 0, 2, 1, 0, 1]
-god	1.1	1.51327	[0, 0, 0, 1, 0, 3, 0, 3, 0, 4]
-goddam	-2.5	1.28452	[0, -3, -3, -4, -3, -1, -4, -1, -3, -3]
-goddammed	-2.4	0.91652	[-2, -3, -1, -1, -2, -2, -4, -3, -3, -3]
-goddamn	-2.1	1.75784	[-3, -3, -2, -4, -4, -3, -3, -1, 1, 1]
-goddamned	-1.8	2.03961	[-3, -3, -3, -4, -1, 2, -2, -3, 2, -3]
-goddamns	-2.1	1.51327	[-3, -2, -4, 2, -2, -3, -3, -2, -2, -2]
-goddams	-1.9	1.92094	[-3, -3, -2, -4, -4, -2, -3, -1, 2, 1]
-godsend	2.8	0.87178	[2, 3, 3, 2, 4, 3, 3, 1, 4, 3]
-good	1.9	0.9434	[2, 1, 1, 3, 2, 4, 2, 2, 1, 1]
-goodness	2.0	1.54919	[2, 2, 2, 3, 1, 2, -2, 4, 3, 3]
-gorgeous	3.0	0.63246	[3, 3, 2, 3, 3, 3, 4, 4, 3, 2]
-gorgeously	2.3	0.78102	[2, 2, 2, 3, 1, 2, 4, 3, 2, 2]
-gorgeousness	2.9	0.9434	[3, 4, 3, 1, 4, 4, 2, 2, 3, 3]
-gorgeousnesses	2.1	0.7	[3, 2, 1, 3, 2, 2, 1, 2, 3, 2]
-gossip	-0.7	0.45826	[-1, -1, -1, 0, 0, -1, -1, 0, -1, -1]
-gossiped	-1.1	0.53852	[-1, -1, -1, -1, -1, -1, 0, -1, -2, -2]
-gossiper	-1.1	0.7	[-1, -1, -1, 0, -2, -1, -1, -2, 0, -2]
-gossipers	-1.1	0.53852	[-1, 0, -1, -1, -1, -1, -1, -1, -2, -2]
-gossiping	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -1, -2, -2]
-gossipmonger	-1.0	1.41421	[-1, -2, 1, -3, -2, 1, -1, -2, -2, 1]
-gossipmongers	-1.4	0.66332	[-2, -1, -1, -1, -2, -2, -1, 0, -2, -2]
-gossipped	-1.3	0.9	[-2, -2, -1, -2, -1, -1, -2, -1, 1, -2]
-gossipping	-1.8	0.6	[-2, -1, -2, -2, -1, -2, -2, -1, -3, -2]
-gossipries	-0.8	0.6	[-1, -1, -1, 0, -1, 0, -1, 0, -2, -1]
-gossipry	-1.2	1.16619	[1, 0, -1, -2, -1, -1, -1, -3, -3, -1]
-gossips	-1.3	0.64031	[-1, -2, -1, -1, -2, -1, 0, -1, -2, -2]
-gossipy	-1.3	0.78102	[-1, -2, -2, -1, -2, -1, 0, 0, -2, -2]
-grace	1.8	0.4	[2, 1, 2, 2, 1, 2, 2, 2, 2, 2]
-graced	0.9	1.04403	[1, 1, 2, -2, 1, 1, 1, 2, 1, 1]
-graceful	2.0	0.63246	[2, 1, 2, 2, 2, 3, 3, 2, 2, 1]
-gracefuller	2.2	0.74833	[2, 3, 2, 2, 1, 2, 3, 1, 3, 3]
-gracefullest	2.8	0.74833	[3, 3, 3, 3, 1, 3, 3, 3, 4, 2]
-gracefully	2.4	0.66332	[3, 3, 2, 1, 3, 2, 2, 2, 3, 3]
-gracefulness	2.2	0.6	[3, 2, 1, 2, 2, 2, 3, 2, 2, 3]
-graces	1.6	0.4899	[2, 2, 2, 1, 1, 2, 1, 2, 1, 2]
-gracile	1.7	0.78102	[1, 3, 2, 1, 2, 3, 2, 1, 1, 1]
-graciles	0.6	0.8	[0, 0, 0, 0, 0, 0, 2, 1, 2, 1]
-gracilis	0.4	0.66332	[0, 0, 0, 0, 0, 1, 0, 1, 0, 2]
-gracility	1.2	0.87178	[1, 1, 0, 1, 1, 3, 2, 2, 0, 1]
-gracing	1.3	0.9	[1, 0, 3, 2, 1, 2, 0, 1, 2, 1]
-gracioso	1.0	0.63246	[2, 2, 1, 1, 1, 1, 0, 1, 0, 1]
-gracious	2.6	0.8	[2, 2, 3, 3, 3, 3, 2, 4, 1, 3]
-graciously	2.3	0.9	[2, 4, 1, 3, 3, 2, 1, 2, 3, 2]
-graciousness	2.4	0.66332	[2, 2, 2, 2, 2, 3, 4, 3, 2, 2]
-grand	2.0	0.63246	[2, 2, 3, 1, 2, 2, 2, 2, 3, 1]
-grandee	1.1	0.83066	[0, 1, 1, 0, 1, 1, 2, 1, 3, 1]
-grandees	1.2	0.87178	[0, 2, 2, 1, 0, 1, 0, 2, 2, 2]
-grander	1.7	0.9	[3, 1, 1, 2, 2, 2, 0, 2, 3, 1]
-grandest	2.4	1.2	[3, 3, 1, 2, 2, 0, 4, 2, 4, 3]
-grandeur	2.4	1.11355	[3, 2, 3, 2, 4, 1, 1, 4, 1, 3]
-grandeurs	2.1	1.3	[2, 2, 1, 0, 0, 4, 3, 3, 3, 3]
-grant	1.5	0.80623	[2, 2, 1, 0, 3, 1, 1, 1, 2, 2]
-granted	1.0	1.09545	[3, 0, 0, 0, 0, 1, 2, 2, 2, 0]
-granting	1.3	0.45826	[2, 1, 1, 2, 1, 2, 1, 1, 1, 1]
-grants	0.9	0.7	[2, 1, 2, 1, 0, 1, 0, 0, 1, 1]
-grateful	2.0	0.63246	[2, 3, 1, 2, 2, 2, 3, 1, 2, 2]
-gratefuller	1.8	0.87178	[2, 3, 0, 3, 2, 1, 1, 2, 2, 2]
-gratefully	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 3, 1, 2]
-gratefulness	2.2	0.6	[2, 3, 2, 1, 2, 2, 3, 2, 3, 2]
-graticule	0.1	0.3	[0, 0, 0, 1, 0, 0, 0, 0, 0, 0]
-graticules	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
-gratification	1.6	0.8	[1, 2, 3, 2, 2, 1, 2, 0, 2, 1]
-gratifications	1.8	0.4	[2, 2, 1, 2, 2, 1, 2, 2, 2, 2]
-gratified	1.6	0.91652	[3, 1, 1, 1, 3, 1, 1, 1, 1, 3]
-gratifies	1.5	0.80623	[3, 1, 1, 1, 2, 1, 1, 1, 1, 3]
-gratify	1.3	1.00499	[2, -1, 1, 3, 1, 1, 1, 1, 2, 2]
-gratifying	2.3	0.45826	[2, 3, 2, 2, 2, 2, 3, 2, 2, 3]
-gratifyingly	2.0	0.63246	[2, 2, 2, 1, 3, 2, 1, 3, 2, 2]
-gratin	0.4	0.91652	[0, 1, 0, 0, 0, 0, 2, 0, -1, 2]
-grating	-0.4	0.4899	[-1, -1, -1, 0, 0, -1, 0, 0, 0, 0]
-gratingly	-0.2	1.6	[1, -3, -2, -2, 0, 2, 1, -1, 1, 1]
-gratings	-0.8	0.9798	[0, -2, -1, -1, 0, 0, -3, 0, 0, -1]
-gratins	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
-gratis	0.2	0.9798	[-2, 1, 1, 0, 0, 0, -1, 1, 1, 1]
-gratitude	2.3	0.64031	[2, 2, 3, 1, 2, 3, 2, 3, 3, 2]
-gratz	2.0	0.89443	[2, 3, 2, 1, 1, 1, 2, 2, 4, 2]
-grave	-1.6	1.62481	[-2, -2, 0, -2, -3, 2, -3, -1, -1, -4]
-graved	-0.9	1.13578	[0, 0, -1, 0, -1, -1, -1, -1, -4, 0]
-gravel	-0.5	0.5	[0, -1, 0, -1, -1, -1, -1, 0, 0, 0]
-graveled	-0.5	0.80623	[0, 0, 0, 0, -1, -2, 0, 0, -2, 0]
-graveless	-1.3	1.34536	[-2, -2, 0, -1, 0, -2, -4, 1, -1, -2]
-graveling	-0.4	1.28062	[-3, 0, -2, 0, 2, -1, 0, 0, 0, 0]
-gravelled	-0.9	0.53852	[0, -1, -1, -2, 0, -1, -1, -1, -1, -1]
-gravelling	-0.4	1.11355	[0, -1, -2, -2, 0, -1, 0, 0, 2, 0]
-gravelly	-0.9	0.7	[0, -2, -1, -1, 0, -1, -1, 0, -1, -2]
-gravels	-0.5	0.80623	[0, -1, 0, 0, 0, -2, 0, 0, 0, -2]
-gravely	-1.5	1.0247	[0, -3, -1, 0, -3, -2, -1, -1, -2, -2]
-graven	-0.9	1.22066	[0, 0, -1, 0, -2, -1, -1, 0, -4, 0]
-graveness	-1.5	0.67082	[-1, -2, -2, -3, -2, -1, -1, -1, -1, -1]
-graver	-1.1	1.22066	[0, -2, -1, 0, 0, -2, -1, 0, -4, -1]
-gravers	-1.2	1.6	[-4, 0, -2, 0, -2, -2, -2, 0, 2, -2]
-graves	-1.2	1.07703	[0, 0, -1, -1, -2, -1, -1, -1, -4, -1]
-graveside	-0.8	0.6	[-1, -1, -1, 0, 0, 0, -1, -2, -1, -1]
-gravesides	-1.6	1.2	[-2, -1, 0, -3, -1, 0, -1, -2, -2, -4]
-gravest	-1.3	1.9	[-3, -1, -2, -2, 1, 1, -2, 2, -3, -4]
-gravestone	-0.7	0.78102	[0, -1, 0, -1, -1, -2, 0, 0, -2, 0]
-gravestones	-0.5	0.5	[-1, -1, 0, -1, -1, -1, 0, 0, 0, 0]
-graveyard	-1.2	0.87178	[0, 0, -1, -2, -1, -1, -2, -1, -3, -1]
-graveyards	-1.2	0.87178	[0, -1, -3, -1, -1, -2, 0, -1, -2, -1]
-great	3.1	0.7	[2, 4, 4, 4, 3, 3, 3, 3, 2, 3]
-greater	1.5	0.67082	[2, 1, 2, 1, 2, 2, 2, 1, 0, 2]
-greatest	3.2	0.74833	[3, 4, 3, 3, 3, 4, 4, 2, 2, 4]
-greed	-1.7	1.61555	[-2, -1, -2, -1, -2, -4, -1, 2, -4, -2]
-greedier	-2.0	0.63246	[-2, -2, -2, -2, -2, -3, -2, -1, -1, -3]
-greediest	-2.8	0.87178	[-3, -4, -3, -2, -2, -4, -4, -2, -2, -2]
-greedily	-1.9	1.22066	[-2, -1, -3, -3, -3, -2, -1, -2, 1, -3]
-greediness	-1.7	1.00499	[-2, -1, -2, -1, -2, -4, -1, 0, -2, -2]
-greeds	-1.0	1.18322	[-1, -2, -2, -2, -2, -2, 1, 0, -1, 1]
-greedy	-1.3	1.48661	[-2, -2, -2, -2, -3, -2, 2, -1, -2, 1]
-greenwash	-1.8	1.4	[-1, 0, -2, -2, -3, -4, 0, 0, -3, -3]
-greenwashing	-0.4	0.91652	[-1, 0, 0, 1, 1, -2, -1, -1, 0, -1]
-greet	1.3	0.64031	[1, 1, 1, 1, 0, 2, 2, 2, 2, 1]
-greeted	1.1	0.9434	[2, 0, 0, 1, 1, 1, 0, 2, 1, 3]
-greeting	1.6	0.4899	[2, 1, 2, 2, 1, 2, 2, 1, 1, 2]
-greetings	1.8	1.07703	[1, 2, 3, 3, 1, 1, 1, 4, 1, 1]
-greets	0.6	0.66332	[0, 0, 2, 0, 1, 1, 0, 1, 1, 0]
-grey	0.2	0.4	[0, 0, 1, 0, 0, 0, 1, 0, 0, 0]
-grief	-2.2	0.6	[-2, -1, -3, -2, -3, -3, -2, -2, -2, -2]
-grievance	-2.1	0.53852	[-2, -2, -3, -2, -2, -3, -2, -1, -2, -2]
-grievances	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -2, -1]
-grievant	-0.8	1.249	[-2, 1, -1, -2, -1, 2, -2, -1, -1, -1]
-grievants	-1.1	0.83066	[-1, -1, -1, -1, -1, -1, 0, -2, 0, -3]
-grieve	-1.6	1.49666	[-2, -3, -1, -3, 1, -3, -1, -2, 1, -3]
-grieved	-2.0	0.89443	[-3, -3, -3, -2, -2, -3, -1, -1, -1, -1]
-griever	-1.9	0.83066	[-2, -2, -3, -2, -3, -3, -1, -1, -1, -1]
-grievers	-0.3	1.55242	[-1, 2, -2, -1, 1, -2, 2, -2, 1, -1]
-grieves	-2.1	0.9434	[-3, -3, -3, -2, -3, -3, -1, -1, -1, -1]
-grieving	-2.3	1.1	[-2, -4, -2, -3, -3, 0, -3, -2, -1, -3]
-grievous	-2.0	1.84391	[-3, -4, -2, -3, -1, 3, -2, -3, -2, -3]
-grievously	-1.7	1.55242	[-3, -1, -4, -2, -2, 1, -3, 1, -2, -2]
-grievousness	-2.7	0.78102	[-3, -3, -3, -2, -3, -4, -2, -1, -3, -3]
-grim	-2.7	0.64031	[-2, -4, -3, -3, -2, -2, -3, -3, -2, -3]
-grimace	-1.0	2.14476	[-4, -3, -2, -2, 2, -1, -1, -3, 2, 2]
-grimaced	-2.0	0.63246	[-2, -3, -2, -2, -2, -2, -1, -3, -1, -2]
-grimaces	-1.8	0.74833	[-1, -2, -1, -2, -2, -1, -3, -3, -1, -2]
-grimacing	-1.4	1.56205	[-3, -2, -3, -3, -1, -1, 1, 0, 1, -3]
-grimalkin	-0.9	1.04403	[-1, -2, -1, 1, -2, -2, -1, -1, 1, -1]
-grimalkins	-0.9	0.9434	[0, 0, 0, -2, -1, -1, -1, 0, -3, -1]
-grime	-1.5	0.92195	[-1, -2, -1, -1, -1, -3, 0, -2, -1, -3]
-grimed	-1.2	0.74833	[-2, -2, 0, -2, -1, -1, -1, -2, -1, 0]
-grimes	-1.0	0.7746	[-2, -2, 0, 0, -1, -1, -1, -2, -1, 0]
-grimier	-1.6	1.0198	[-1, -2, -2, -2, -1, 0, -4, -1, -1, -2]
-grimiest	-0.7	2.05183	[-2, -3, 1, -3, 2, -2, -2, -2, 2, 2]
-grimily	-0.7	1.61555	[-2, -1, -1, -2, -2, 2, -2, 2, 1, -2]
-griminess	-1.6	0.4899	[-1, -2, -2, -2, -1, -2, -2, -1, -1, -2]
-griming	-0.7	1.55242	[-3, -1, -1, -2, 0, 2, -1, -2, -1, 2]
-grimly	-1.3	1.55242	[-2, -1, 2, -2, -2, -1, -3, -3, 1, -2]
-grimmer	-1.5	1.36015	[1, -2, -3, 1, -2, -1, -2, -2, -3, -2]
-grimmest	-0.8	1.72047	[-2, -1, -3, 0, -2, -1, 0, 2, 2, -3]
-grimness	-0.8	1.98997	[2, -2, -3, -2, -3, 2, -1, 1, 1, -3]
-grimy	-1.8	0.87178	[-2, -2, -2, -1, -1, -3, 0, -2, -2, -3]
-grin	2.1	0.83066	[2, 4, 2, 2, 2, 1, 2, 3, 1, 2]
-grinned	1.1	0.9434	[1, 1, 2, 1, 3, 1, -1, 1, 1, 1]
-grinner	1.1	0.83066	[1, 1, 2, 2, 2, 1, -1, 1, 1, 1]
-grinners	1.6	0.8	[2, 2, 2, 3, 1, 0, 2, 2, 1, 1]
-grinning	1.5	1.0247	[3, 2, 2, 1, 1, -1, 1, 2, 2, 2]
-grins	0.9	1.92094	[1, 4, -3, 1, 2, 1, 2, -2, 2, 1]
-gross	-2.1	1.51327	[-1, -3, -2, -3, -3, -3, -3, 2, -2, -3]
-grossed	-0.4	1.11355	[-1, -2, -1, -2, 0, 0, 1, 1, 1, -1]
-grosser	-0.3	1.41774	[1, -2, -1, -2, 0, -1, 1, 2, 1, -2]
-grosses	-0.8	1.77764	[-2, -2, 3, -2, -3, -1, 1, -1, 1, -2]
-grossest	-2.1	0.83066	[-2, -1, -2, -3, -3, -1, -3, -3, -1, -2]
-grossing	-0.3	1.79165	[-1, -3, -1, 1, 0, -1, -3, 1, 1, 3]
-grossly	-0.9	1.44568	[1, -2, 0, -3, -1, -2, 1, 1, -2, -2]
-grossness	-1.8	0.6	[-2, -2, -1, -1, -1, -3, -2, -2, -2, -2]
-grossular	-0.3	1.34536	[0, -2, 0, -1, -2, -1, 0, 0, 0, 3]
-grossularite	-0.1	1.13578	[2, 0, 0, 0, 0, -3, 0, 0, 0, 0]
-grossularites	-0.7	1.26886	[0, -4, -1, -2, 0, 0, 0, 0, 0, 0]
-grossulars	-0.3	0.45826	[0, 0, 0, 0, -1, -1, 0, 0, 0, -1]
-grouch	-2.2	0.87178	[-2, -3, -3, -3, -2, -1, -3, -1, -1, -3]
-grouched	-0.8	0.9798	[-2, -1, -2, -2, 1, -1, 0, 0, 0, -1]
-grouches	-0.9	1.13578	[-2, -1, -2, -1, -1, -1, -1, 2, 0, -2]
-grouchier	-2.0	0.63246	[-2, -3, -3, -2, -2, -2, -2, -1, -2, -1]
-grouchiest	-2.3	0.78102	[-3, -3, -2, -2, -1, -3, -1, -3, -3, -2]
-grouchily	-1.4	1.56205	[-2, -1, -2, -3, -3, 2, -2, -2, 1, -2]
-grouchiness	-2.0	0.7746	[-2, -2, -3, -2, -3, -2, -2, 0, -2, -2]
-grouching	-1.7	1.1	[-1, -3, -2, 1, -2, -3, -2, -1, -2, -2]
-grouchy	-1.9	0.7	[-1, -3, -2, -2, -1, -3, -1, -2, -2, -2]
-growing	0.7	0.64031	[0, 1, 1, 2, 1, 0, 0, 1, 1, 0]
-growth	1.6	1.0198	[2, 0, 3, 0, 2, 3, 1, 1, 2, 2]
-guarantee	1.0	1.0	[2, 3, 1, 0, 2, 0, 1, 0, 0, 1]
-guilt	-1.1	1.22066	[-1, -3, 2, -1, -1, -2, -1, -2, -1, -1]
-guiltier	-2.0	0.63246	[-2, -1, -3, -1, -3, -2, -2, -2, -2, -2]
-guiltiest	-1.7	1.79165	[-3, -2, -2, -4, -1, -2, 3, -1, -3, -2]
-guiltily	-1.1	1.57797	[-3, -1, -1, -2, 0, -2, 3, -2, -1, -2]
-guiltiness	-1.8	0.6	[-2, -2, -1, -2, -1, -1, -2, -2, -3, -2]
-guiltless	0.8	1.53623	[3, 2, 1, 2, -2, 1, 1, -2, 1, 1]
-guiltlessly	0.7	1.18743	[-1, 1, -2, 2, 1, 1, 1, 1, 2, 1]
-guiltlessness	0.6	1.42829	[1, 1, -1, -1, -1, 1, 2, 3, -1, 2]
-guilts	-1.4	0.66332	[-1, -2, -1, -1, -3, -1, -1, -2, -1, -1]
-guilty	-1.8	0.6	[-1, -2, -2, -3, -2, -2, -1, -2, -2, -1]
-gullibility	-1.6	0.66332	[-1, -1, -2, -2, -1, -2, -1, -2, -1, -3]
-gullible	-1.5	0.67082	[-1, -2, -2, -1, -1, -3, -2, -1, -1, -1]
-gun	-1.4	1.49666	[0, -4, 0, -3, 0, -3, -2, 0, -2, 0]
-h8	-2.7	1.00499	[-4, -3, -4, -1, -1, -3, -3, -3, -2, -3]
-ha	1.4	0.8	[1, 0, 1, 1, 3, 2, 2, 1, 2, 1]
-hacked	-1.7	1.00499	[-2, -1, -2, -4, 0, -2, -2, -1, -1, -2]
-haha	2.0	0.89443	[1, 1, 2, 3, 2, 1, 4, 2, 2, 2]
-hahaha	2.6	1.0198	[2, 4, 2, 4, 1, 2, 3, 4, 2, 2]
-hahas	1.8	0.9798	[1, 2, 2, 4, 3, 2, 1, 1, 1, 1]
-hail	0.3	0.9	[0, 0, 0, 2, 0, 0, 2, 0, -1, 0]
-hailed	0.9	0.83066	[1, 2, 1, 1, 0, 0, 0, 2, 2, 0]
-hallelujah	3.0	0.7746	[3, 4, 3, 1, 3, 3, 3, 3, 3, 4]
-handsome	2.2	0.74833	[2, 2, 2, 2, 2, 3, 4, 1, 2, 2]
-handsomely	1.9	0.7	[1, 3, 1, 1, 2, 2, 2, 2, 2, 3]
-handsomeness	2.4	1.28062	[2, 4, 1, 4, 0, 2, 4, 3, 2, 2]
-handsomer	2.0	0.63246	[2, 3, 2, 2, 2, 2, 1, 3, 1, 2]
-handsomest	2.6	0.91652	[3, 2, 1, 2, 3, 4, 4, 3, 2, 2]
-hapless	-1.4	1.11355	[-3, -1, -1, -1, -2, -1, 1, -2, -3, -1]
-haplessness	-1.4	1.0198	[-1, -2, 0, -1, -1, -1, -1, -2, -1, -4]
-happier	2.4	0.66332	[3, 1, 2, 3, 2, 2, 3, 3, 3, 2]
-happiest	3.2	0.74833	[4, 3, 2, 4, 4, 3, 3, 3, 2, 4]
-happily	2.6	0.91652	[4, 1, 2, 4, 2, 3, 2, 2, 3, 3]
-happiness	2.6	0.4899	[2, 3, 3, 3, 3, 2, 2, 3, 2, 3]
-happing	1.1	0.83066	[1, 1, 1, 0, 2, 2, 0, 2, 0, 2]
-happy	2.7	0.9	[2, 2, 2, 4, 2, 4, 3, 4, 2, 2]
-harass	-2.2	0.6	[-2, -3, -2, -2, -2, -3, -2, -3, -1, -2]
-harassed	-2.5	0.80623	[-4, -2, -3, -3, -2, -2, -3, -2, -3, -1]
-harasser	-2.4	0.8	[-3, -2, -2, -3, -2, -2, -4, -2, -3, -1]
-harassers	-2.8	0.6	[-3, -3, -2, -2, -3, -3, -3, -4, -2, -3]
-harasses	-2.5	0.80623	[-3, -3, -2, -3, -2, -2, -4, -2, -3, -1]
-harassing	-2.5	1.62788	[-2, -4, -3, -4, -3, -3, 2, -2, -3, -3]
-harassment	-2.5	0.67082	[-2, -3, -2, -2, -3, -2, -4, -3, -2, -2]
-harassments	-2.6	0.4899	[-3, -3, -2, -3, -2, -3, -3, -2, -2, -3]
-hard	-0.4	1.2	[0, -1, 0, -1, 0, 1, -2, -1, -2, 2]
-hardier	-0.6	1.68523	[-3, -2, -2, 1, 1, 2, 1, 0, -2, -2]
-hardship	-1.3	1.84662	[-2, 2, -4, -1, -2, -3, -1, -2, 2, -2]
-hardy	1.7	1.00499	[1, 2, 1, 0, 2, 2, 4, 1, 2, 2]
-harm	-2.5	0.80623	[-2, -2, -2, -3, -2, -1, -3, -3, -3, -4]
-harmed	-2.1	0.83066	[-1, -4, -2, -2, -2, -2, -1, -2, -3, -2]
-harmfully	-2.6	0.91652	[-3, -4, -3, -1, -3, -3, -3, -3, -1, -2]
-harmfulness	-2.6	0.8	[-3, -1, -3, -3, -3, -2, -4, -2, -2, -3]
-harming	-2.6	0.66332	[-3, -3, -2, -2, -3, -3, -2, -2, -2, -4]
-harmless	1.0	0.7746	[2, 1, 1, 1, 1, 0, 0, 2, 0, 2]
-harmlessly	1.4	1.2	[4, 0, 1, 0, 1, 1, 1, 2, 3, 1]
-harmlessness	0.8	1.16619	[1, 2, 0, 1, 0, 1, 2, 1, 2, -2]
-harmonic	1.8	0.87178	[2, 1, 2, 3, 0, 1, 3, 2, 2, 2]
-harmonica	0.6	0.8	[0, 1, 0, 0, 0, 2, 1, 0, 2, 0]
-harmonically	2.1	1.13578	[3, 3, 4, 1, 0, 1, 2, 2, 2, 3]
-harmonicas	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
-harmonicist	0.5	0.92195	[0, 0, 0, 0, 1, 0, 0, 0, 1, 3]
-harmonicists	0.9	1.3	[2, 1, 0, 0, 2, 0, 0, 0, 4, 0]
-harmonics	1.5	1.0247	[2, 2, 2, 0, 0, 2, 3, 2, 0, 2]
-harmonies	1.3	0.9	[2, 0, 2, 1, 2, 2, 0, 2, 0, 2]
-harmonious	2.0	1.09545	[3, 4, 2, 2, 2, 0, 2, 3, 1, 1]
-harmoniously	1.9	0.9434	[4, 2, 2, 1, 2, 1, 1, 3, 2, 1]
-harmoniousness	1.8	0.6	[1, 2, 2, 2, 2, 1, 2, 3, 2, 1]
-harmonise	1.8	0.74833	[1, 1, 2, 3, 2, 1, 1, 3, 2, 2]
-harmonised	1.3	0.9	[2, 3, 2, 0, 2, 1, 1, 1, 1, 0]
-harmonising	1.4	0.66332	[1, 2, 1, 1, 2, 1, 1, 1, 1, 3]
-harmonium	0.9	1.22066	[0, 3, 0, 2, 3, 0, 0, 0, 0, 1]
-harmoniums	0.8	0.9798	[0, 0, 0, 2, 0, 2, 0, 2, 2, 0]
-harmonization	1.9	0.83066	[3, 1, 2, 2, 2, 2, 3, 0, 2, 2]
-harmonizations	0.9	0.9434	[0, 0, 2, 0, 2, 2, 0, 2, 1, 0]
-harmonize	1.7	0.78102	[3, 2, 2, 1, 2, 2, 0, 1, 2, 2]
-harmonized	1.6	0.91652	[1, 2, 1, 1, 2, 2, 3, 3, 0, 1]
-harmonizer	1.6	0.8	[1, 2, 1, 1, 2, 2, 2, 3, 0, 2]
-harmonizers	1.6	1.11355	[2, 2, 2, 1, 2, 0, 4, 0, 2, 1]
-harmonizes	1.5	0.92195	[0, 2, 2, 2, 0, 1, 1, 2, 3, 2]
-harmonizing	1.4	0.66332	[0, 1, 1, 2, 2, 1, 2, 2, 1, 2]
-harmony	1.7	0.45826	[2, 2, 2, 2, 1, 2, 2, 2, 1, 1]
-harms	-2.2	1.6	[2, -3, -2, -2, -3, -2, -4, -4, -2, -2]
-harried	-1.4	0.4899	[-1, -1, -2, -1, -2, -2, -1, -1, -1, -2]
-harsh	-1.9	0.7	[-1, -1, -2, -2, -1, -3, -3, -2, -2, -2]
-harsher	-2.2	0.6	[-2, -3, -2, -3, -2, -2, -1, -3, -2, -2]
-harshest	-2.9	0.83066	[-4, -2, -2, -2, -2, -3, -3, -4, -4, -3]
-hate	-2.7	1.00499	[-4, -3, -4, -4, -2, -2, -2, -2, -1, -3]
-hated	-3.2	0.6	[-3, -3, -4, -3, -2, -3, -3, -4, -4, -3]
-hateful	-2.2	1.249	[-3, 1, -3, -3, -1, -2, -2, -3, -3, -3]
-hatefully	-2.3	0.78102	[-1, -3, -3, -3, -1, -2, -2, -2, -3, -3]
-hatefulness	-3.6	0.4899	[-4, -4, -3, -3, -3, -4, -4, -4, -4, -3]
-hater	-1.8	0.6	[-2, -1, -2, -2, -2, -1, -1, -2, -2, -3]
-haters	-2.2	0.6	[-2, -1, -3, -2, -3, -2, -3, -2, -2, -2]
-hates	-1.9	0.7	[-2, -1, -2, -2, -3, -1, -1, -2, -2, -3]
-hating	-2.3	1.1	[-4, -3, -4, -1, -2, -2, -1, -2, -1, -3]
-hatred	-3.2	0.9798	[-1, -3, -2, -4, -3, -3, -4, -4, -4, -4]
-haunt	-1.7	1.00499	[-1, -1, -3, -1, -2, -2, -1, -4, -1, -1]
-haunted	-2.1	0.7	[-2, -2, -1, -3, -3, -2, -2, -3, -1, -2]
-haunting	-1.1	0.83066	[-3, 0, -2, -1, 0, -1, -1, -1, -1, -1]
-haunts	-1.0	1.41421	[0, -2, -2, -2, -2, -1, 2, -2, 1, -2]
-havoc	-2.9	0.7	[-2, -4, -4, -3, -2, -3, -3, -3, -2, -3]
-healthy	1.7	0.9	[1, 3, 1, 1, 3, 3, 1, 2, 1, 1]
-heartbreak	-2.7	0.78102	[-1, -3, -3, -3, -2, -4, -2, -3, -3, -3]
-heartbreaker	-2.2	1.07703	[-2, -3, 0, -3, -2, -1, -4, -3, -2, -2]
-heartbreakers	-2.1	0.9434	[-3, -2, -3, -2, -1, -1, -4, -1, -2, -2]
-heartbreaking	-2.0	1.73205	[-3, -1, -3, -3, -4, 2, -3, -2, 0, -3]
-heartbreakingly	-1.8	2.08806	[-3, 3, 1, -3, -3, -2, -3, -3, -4, -1]
-heartbreaks	-1.8	1.77764	[-2, 1, -3, -2, -3, -2, -3, 2, -4, -2]
-heartbroken	-3.3	0.45826	[-4, -3, -3, -4, -3, -3, -4, -3, -3, -3]
-heartfelt	2.5	0.5	[3, 3, 2, 3, 2, 2, 3, 2, 2, 3]
-heartless	-2.2	0.74833	[-2, -2, -2, -4, -2, -1, -2, -3, -2, -2]
-heartlessly	-2.8	0.6	[-3, -2, -3, -3, -2, -3, -4, -2, -3, -3]
-heartlessness	-2.8	0.87178	[-3, -3, -2, -3, -4, -4, -1, -3, -2, -3]
-heartwarming	2.1	1.22066	[3, 2, 3, 3, 2, 2, 3, 3, -1, 1]
-heaven	2.3	1.18743	[1, 1, 2, 4, 3, 3, 3, 4, 1, 1]
-heavenlier	3.0	0.63246	[3, 2, 3, 3, 4, 3, 3, 4, 2, 3]
-heavenliest	2.7	1.1	[3, 2, 3, 4, 2, 4, 3, 0, 3, 3]
-heavenliness	2.7	0.9	[3, 2, 1, 4, 3, 2, 3, 4, 3, 2]
-heavenlinesses	2.3	2.2383	[4, 4, 4, 3, -2, 3, 3, 4, -2, 2]
-heavenly	3.0	0.63246	[3, 3, 3, 3, 2, 3, 3, 4, 2, 4]
-heavens	1.7	1.18743	[4, 0, 1, 2, 0, 3, 2, 2, 2, 1]
-heavenward	1.4	1.35647	[0, 3, 0, 4, 1, 2, 2, 0, 2, 0]
-heavenwards	1.2	1.32665	[1, 4, 0, 0, 2, 1, 1, 0, 3, 0]
-heavyhearted	-2.1	0.83066	[-2, -3, -3, -2, -3, -1, -1, -1, -2, -3]
-heh	-0.6	1.28062	[0, 1, -1, 1, -1, -2, -1, -3, 1, -1]
-hell	-3.6	0.66332	[-4, -4, -4, -4, -4, -2, -3, -4, -3, -4]
-hellish	-3.2	0.74833	[-3, -3, -2, -2, -4, -3, -4, -4, -3, -4]
-help	1.7	0.78102	[3, 2, 1, 2, 1, 2, 3, 1, 1, 1]
-helper	1.4	0.8	[1, 1, 0, 1, 1, 2, 1, 2, 3, 2]
-helpers	1.1	0.83066	[1, 1, 0, 2, 1, 1, 1, 1, 3, 0]
-helpful	1.8	0.87178	[2, 1, 3, 1, 1, 3, 1, 2, 3, 1]
-helpfully	2.3	0.9	[1, 2, 2, 3, 2, 3, 3, 2, 4, 1]
-helpfulness	1.9	1.13578	[1, 4, 1, 2, 2, 1, 1, 2, 4, 1]
-helping	1.2	0.6	[2, 1, 1, 2, 0, 1, 1, 1, 2, 1]
-helpless	-2.0	0.63246	[-2, -3, -2, -2, -2, -3, -1, -2, -1, -2]
-helplessly	-1.4	0.4899	[-1, -1, -2, -2, -1, -1, -1, -2, -2, -1]
-helplessness	-2.1	0.9434	[-2, -4, -1, -2, -1, -3, -3, -2, -1, -2]
-helplessnesses	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -3, -2, -1, -2]
-helps	1.6	0.4899	[1, 1, 1, 2, 2, 2, 1, 2, 2, 2]
-hero	2.6	0.8	[2, 3, 2, 2, 4, 4, 2, 3, 2, 2]
-heroes	2.3	0.9	[3, 4, 3, 1, 3, 2, 1, 2, 2, 2]
-heroic	2.6	0.8	[3, 3, 1, 4, 2, 3, 2, 3, 2, 3]
-heroical	2.9	1.04403	[4, 4, 2, 4, 2, 3, 1, 4, 2, 3]
-heroically	2.4	0.8	[2, 2, 2, 3, 3, 3, 4, 1, 2, 2]
-heroicomic	1.0	1.0	[1, 0, 1, 0, 2, 0, 3, 1, 2, 0]
-heroicomical	1.1	0.83066	[2, 0, 0, 2, 1, 2, 1, 2, 1, 0]
-heroics	2.4	0.8	[2, 1, 2, 2, 2, 3, 3, 3, 4, 2]
-heroin	-2.2	1.83303	[0, -2, -4, 2, -4, -2, -2, -3, -3, -4]
-heroine	2.7	1.1	[0, 2, 4, 4, 3, 3, 3, 3, 2, 3]
-heroines	1.8	1.32665	[2, 1, 1, 4, 3, 1, 0, 3, 3, 0]
-heroinism	-2.0	2.0	[-3, -4, 2, -2, -4, -3, -2, -1, 1, -4]
-heroism	2.8	0.6	[3, 3, 4, 3, 2, 2, 3, 3, 2, 3]
-heroisms	2.2	0.87178	[3, 1, 2, 4, 3, 2, 2, 2, 1, 2]
-heroize	2.1	0.7	[3, 2, 3, 1, 2, 2, 2, 3, 1, 2]
-heroized	2.0	1.18322	[1, 0, 3, 3, 2, 0, 3, 3, 2, 3]
-heroizes	2.2	0.9798	[1, 3, 2, 3, 4, 3, 2, 1, 2, 1]
-heroizing	1.9	1.64012	[2, 3, -2, 2, 4, 3, 2, 2, 3, 0]
-heron	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
-heronries	0.7	1.1	[2, 0, 0, 0, 2, 0, 3, 0, 0, 0]
-heronry	0.1	0.9434	[0, 0, 0, 0, 0, 2, 0, 1, -2, 0]
-herons	0.5	1.0247	[0, 0, 0, 3, 0, 2, 0, 0, 0, 0]
-heros	1.3	1.18743	[3, 0, 0, 2, 0, 2, 2, 3, 1, 0]
-hesitance	-0.9	0.3	[-1, -1, 0, -1, -1, -1, -1, -1, -1, -1]
-hesitancies	-1.0	0.63246	[-1, -1, -1, -2, -1, -1, -2, 0, 0, -1]
-hesitancy	-0.9	0.53852	[0, -1, 0, -2, -1, -1, -1, -1, -1, -1]
-hesitant	-1.0	0.7746	[0, -1, 0, -1, -2, 0, -1, -2, -1, -2]
-hesitantly	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -2, -1, -1]
-hesitate	-1.1	0.53852	[-2, -1, -1, -1, -2, -1, -1, 0, -1, -1]
-hesitated	-1.3	0.9	[-1, -2, -1, -2, -2, -2, -1, 1, -1, -2]
-hesitater	-1.4	0.66332	[-1, -1, -1, -1, -1, -2, -1, -3, -2, -1]
-hesitaters	-1.4	0.4899	[-1, -2, -1, -1, -1, -1, -2, -2, -2, -1]
-hesitates	-1.4	0.4899	[-1, -1, -1, -2, -1, -2, -1, -2, -2, -1]
-hesitating	-1.4	0.66332	[-1, -1, -2, -1, -1, -3, -2, -1, -1, -1]
-hesitatingly	-1.5	0.80623	[-1, -1, -1, -1, -3, -2, -3, -1, -1, -1]
-hesitation	-1.1	0.53852	[-2, 0, -1, -1, -1, -1, -1, -2, -1, -1]
-hesitations	-1.1	0.53852	[-1, -1, -1, 0, -2, -1, -1, -2, -1, -1]
-hid	-0.4	0.4899	[0, -1, 0, 0, -1, -1, -1, 0, 0, 0]
-hide	-0.7	0.64031	[0, -1, -1, -1, -1, 0, 0, -2, -1, 0]
-hides	-0.7	0.9	[-1, -2, -1, 0, -1, 0, 0, -2, 1, -1]
-hiding	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -1, -2, -1]
-highlight	1.4	0.91652	[3, 0, 1, 1, 2, 1, 0, 2, 2, 2]
-hilarious	1.7	1.41774	[2, 2, 2, 3, 3, 1, -2, 2, 3, 1]
-hindrance	-1.7	0.78102	[-2, -3, -2, -1, -1, -1, -3, -1, -2, -1]
-hoax	-1.1	1.04403	[-3, -1, -2, -1, 1, -2, -1, -1, -1, 0]
-holiday	1.7	1.18743	[1, 3, 2, 2, 0, 0, 1, 2, 4, 2]
-holidays	1.6	1.0198	[2, 0, 1, 2, 3, 0, 1, 2, 3, 2]
-homesick	-0.7	1.67631	[-2, -1, -1, -2, -1, -2, 2, -1, 3, -2]
-homesickness	-1.8	1.249	[-3, -2, -1, -1, -3, -2, -1, 1, -3, -3]
-homesicknesses	-1.8	0.6	[-1, -2, -2, -2, -1, -2, -1, -2, -3, -2]
-honest	2.3	0.9	[3, 2, 1, 2, 3, 1, 2, 3, 2, 4]
-honester	1.9	0.7	[2, 3, 2, 2, 1, 3, 1, 1, 2, 2]
-honestest	3.0	0.7746	[1, 3, 3, 3, 3, 3, 4, 4, 3, 3]
-honesties	1.8	1.07703	[4, 3, 1, 1, 1, 1, 3, 2, 1, 1]
-honestly	2.0	0.63246	[2, 3, 2, 2, 1, 2, 2, 1, 3, 2]
-honesty	2.2	0.6	[2, 3, 2, 2, 1, 2, 3, 2, 3, 2]
-honor	2.2	1.16619	[3, 2, 1, 2, 0, 4, 3, 1, 3, 3]
-honorability	2.2	0.4	[3, 3, 2, 2, 2, 2, 2, 2, 2, 2]
-honorable	2.5	0.67082	[2, 2, 3, 2, 4, 3, 2, 2, 2, 3]
-honorableness	2.2	0.87178	[2, 4, 1, 3, 3, 2, 1, 2, 2, 2]
-honorably	2.4	0.66332	[2, 2, 3, 2, 3, 3, 3, 1, 2, 3]
-honoraria	0.6	0.8	[1, 0, 1, 0, 0, 0, 2, 0, 2, 0]
-honoraries	1.5	1.5	[2, 2, 1, 3, 3, 1, -2, 2, 3, 0]
-honorarily	1.9	0.7	[2, 2, 3, 1, 2, 1, 2, 1, 3, 2]
-honorarium	0.7	1.48661	[3, 2, -1, 2, 1, -2, 1, 1, -1, 1]
-honorariums	1.0	1.0	[0, 0, 0, 0, 1, 2, 1, 3, 2, 1]
-honorary	1.4	0.91652	[2, 2, 2, 3, 1, 1, 0, 1, 2, 0]
-honored	2.8	0.87178	[3, 4, 4, 3, 1, 2, 2, 3, 3, 3]
-honoree	2.1	0.7	[3, 2, 3, 3, 1, 2, 1, 2, 2, 2]
-honorees	2.3	0.78102	[1, 3, 3, 4, 2, 2, 2, 2, 2, 2]
-honorer	1.7	0.78102	[2, 1, 3, 3, 1, 2, 1, 2, 1, 1]
-honorers	1.3	0.45826	[1, 1, 2, 2, 1, 1, 2, 1, 1, 1]
-honorific	1.4	1.2	[2, 2, 2, 2, 2, 1, 2, 1, 2, -2]
-honorifically	2.2	0.74833	[3, 4, 1, 2, 2, 2, 2, 2, 2, 2]
-honorifics	1.7	0.78102	[1, 2, 0, 1, 2, 2, 2, 3, 2, 2]
-honoring	2.3	0.64031	[3, 3, 1, 2, 2, 3, 3, 2, 2, 2]
-honors	2.3	0.64031	[3, 2, 2, 2, 1, 3, 3, 2, 3, 2]
-honour	2.7	0.78102	[2, 3, 2, 2, 2, 3, 4, 4, 3, 2]
-honourable	2.1	0.53852	[2, 3, 2, 2, 2, 1, 3, 2, 2, 2]
-honoured	2.2	1.249	[3, 3, 4, 3, -1, 2, 2, 2, 2, 2]
-honourer	1.8	0.87178	[2, 3, 2, 1, 2, 3, 1, 0, 2, 2]
-honourers	1.6	1.0198	[0, 2, 2, 1, 2, 2, 1, 3, 0, 3]
-honouring	2.1	0.3	[2, 2, 2, 3, 2, 2, 2, 2, 2, 2]
-honours	2.2	0.87178	[4, 3, 2, 2, 3, 2, 2, 1, 2, 1]
-hooligan	-1.5	0.5	[-1, -2, -1, -2, -2, -2, -1, -1, -2, -1]
-hooliganism	-2.1	0.83066	[-3, -2, -3, -3, -2, -2, -2, -2, 0, -2]
-hooligans	-1.1	1.22066	[-2, -1, -1, 2, -1, -1, -1, -3, -2, -1]
-hooray	2.3	0.9	[3, 2, 3, 2, 1, 3, 1, 2, 2, 4]
-hope	1.9	0.53852	[3, 2, 2, 1, 2, 2, 1, 2, 2, 2]
-hoped	1.6	0.4899	[1, 2, 1, 1, 2, 2, 1, 2, 2, 2]
-hopeful	2.3	0.78102	[2, 1, 1, 3, 3, 3, 2, 3, 2, 3]
-hopefully	1.7	0.78102	[1, 3, 1, 3, 1, 2, 1, 1, 2, 2]
-hopefulness	1.6	1.35647	[2, 1, -2, 2, 3, 2, 1, 3, 2, 2]
-hopeless	-2.0	1.78885	[-3, -3, -3, -3, 3, -1, -3, -3, -2, -2]
-hopelessly	-2.2	0.74833	[-3, -4, -2, -2, -1, -2, -2, -2, -2, -2]
-hopelessness	-3.1	0.7	[-3, -4, -4, -3, -3, -3, -4, -3, -2, -2]
-hopes	1.8	0.6	[1, 3, 1, 2, 2, 2, 1, 2, 2, 2]
-hoping	1.8	0.4	[2, 2, 2, 1, 2, 2, 2, 2, 2, 1]
-horrendous	-2.8	0.87178	[-3, -3, -4, -4, -3, -3, -2, -2, -1, -3]
-horrendously	-1.9	1.92094	[-3, -2, -4, -4, 2, -1, -3, -2, 1, -3]
-horrent	-0.9	1.04403	[0, -1, -2, 0, 0, -3, -1, 0, -2, 0]
-horrible	-2.5	0.67082	[-2, -2, -3, -2, -2, -4, -3, -3, -2, -2]
-horribleness	-2.4	0.4899	[-3, -3, -2, -2, -3, -2, -2, -3, -2, -2]
-horribles	-2.1	0.7	[-2, -4, -2, -2, -1, -2, -2, -2, -2, -2]
-horribly	-2.4	0.66332	[-2, -2, -2, -2, -2, -4, -3, -3, -2, -2]
-horrid	-2.5	1.0247	[-2, -3, -3, -4, -4, -1, -2, -2, -3, -1]
-horridly	-1.4	1.49666	[-2, 0, -3, -2, 0, -3, 2, -2, -2, -2]
-horridness	-2.3	1.26886	[-3, -3, -2, 1, -3, -3, -3, -3, -1, -3]
-horridnesses	-3.0	1.09545	[-2, -3, -4, -4, -4, -4, -2, -2, -1, -4]
-horrific	-3.4	0.91652	[-2, -4, -4, -4, -2, -4, -2, -4, -4, -4]
-horrifically	-2.9	0.7	[-2, -3, -2, -4, -2, -4, -3, -3, -3, -3]
-horrified	-2.5	0.92195	[-2, -3, -2, -2, -1, -4, -2, -2, -3, -4]
-horrifies	-2.9	1.22066	[-1, -3, -2, -1, -4, -4, -4, -4, -2, -4]
-horrify	-2.5	0.67082	[-2, -2, -3, -2, -2, -2, -4, -2, -3, -3]
-horrifying	-2.7	0.9	[-3, -4, -3, -2, -3, -3, -4, -2, -2, -1]
-horrifyingly	-3.3	0.9	[-3, -3, -4, -4, -1, -4, -3, -3, -4, -4]
-horror	-2.7	1.1	[-3, -1, -4, -4, -4, -3, -1, -2, -3, -2]
-horrors	-2.7	0.64031	[-3, -3, -4, -3, -2, -2, -2, -3, -2, -3]
-hostile	-1.6	1.74356	[-4, -3, -3, -1, 1, -2, 2, -2, -2, -2]
-hostilely	-2.2	0.6	[-1, -3, -3, -2, -2, -2, -2, -2, -2, -3]
-hostiles	-1.3	1.9	[-3, -3, -3, -3, -1, 2, -3, -1, 1, 1]
-hostilities	-2.1	0.53852	[-2, -3, -2, -2, -2, -2, -1, -2, -3, -2]
-hostility	-2.5	0.80623	[-2, -2, -3, -3, -3, -2, -4, -2, -3, -1]
-huckster	-0.9	0.7	[-1, 0, -1, 0, -1, -2, -2, 0, -1, -1]
-hug	2.1	1.04403	[1, 3, 2, 1, 1, 2, 3, 3, 1, 4]
-huge	1.3	0.9	[0, 2, 2, 0, 0, 2, 2, 2, 1, 2]
-huggable	1.6	0.66332	[2, 2, 1, 1, 1, 3, 1, 2, 2, 1]
-hugged	1.7	0.78102	[2, 2, 2, 2, 3, 1, 1, 2, 0, 2]
-hugger	1.6	0.91652	[3, 2, 2, 2, 3, 1, 1, 1, 0, 1]
-huggers	1.8	0.6	[1, 3, 1, 2, 1, 2, 2, 2, 2, 2]
-hugging	1.8	0.74833	[2, 1, 1, 3, 3, 2, 2, 1, 2, 1]
-hugs	2.2	0.74833	[3, 2, 1, 2, 2, 2, 3, 1, 3, 3]
-humerous	1.4	1.11355	[-1, 2, 2, 3, 1, 1, 2, 0, 2, 2]
-humiliate	-2.5	1.28452	[-3, -3, -3, -3, -2, -2, -4, -3, 1, -3]
-humiliated	-1.4	2.498	[3, -3, -4, -3, -3, -4, -3, 0, 1, 2]
-humiliates	-1.0	2.09762	[1, -2, -3, -3, -3, -2, -3, 1, 2, 2]
-humiliating	-1.2	1.8868	[-4, -1, -3, -1, 2, -1, 2, -3, -2, -1]
-humiliatingly	-2.6	0.4899	[-3, -3, -2, -2, -3, -3, -3, -3, -2, -2]
-humiliation	-2.7	0.78102	[-2, -3, -4, -2, -2, -2, -3, -2, -4, -3]
-humiliations	-2.4	0.66332	[-3, -2, -2, -2, -2, -2, -2, -3, -2, -4]
-humor	1.1	0.53852	[1, 0, 2, 2, 1, 1, 1, 1, 1, 1]
-humoral	0.6	1.0198	[2, 0, 0, 0, 0, 0, 3, 1, 0, 0]
-humored	1.2	0.87178	[1, 1, 2, 2, 1, 1, 2, 1, 2, -1]
-humoresque	1.2	0.6	[1, 1, 1, 2, 1, 2, 2, 1, 1, 0]
-humoresques	0.9	1.04403	[1, 0, 2, 0, 0, 1, 2, 0, 3, 0]
-humoring	2.1	0.7	[3, 2, 2, 2, 1, 2, 2, 1, 3, 3]
-humorist	1.2	0.74833	[1, 2, 1, 1, 2, 1, 2, 0, 0, 2]
-humoristic	1.5	0.80623	[3, 0, 2, 1, 2, 1, 2, 2, 1, 1]
-humorists	1.3	0.78102	[2, 1, 1, 1, 0, 1, 2, 3, 1, 1]
-humorless	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -2]
-humorlessness	-1.4	1.11355	[1, -3, -3, -1, -1, -2, -1, -1, -2, -1]
-humorous	1.6	0.4899	[1, 2, 1, 2, 2, 1, 2, 2, 1, 2]
-humorously	2.3	0.78102	[3, 3, 2, 2, 1, 3, 3, 1, 2, 3]
-humorousness	2.4	0.66332	[1, 2, 3, 2, 3, 2, 3, 3, 2, 3]
-humors	1.6	0.4899	[2, 1, 2, 2, 2, 2, 1, 2, 1, 1]
-humour	2.1	0.9434	[1, 2, 2, 4, 2, 1, 1, 3, 3, 2]
-humoured	1.1	0.53852	[1, 0, 1, 2, 2, 1, 1, 1, 1, 1]
-humouring	1.7	0.78102	[2, 3, 1, 2, 1, 0, 2, 2, 2, 2]
-humourous	2.0	0.7746	[1, 2, 3, 2, 2, 3, 3, 2, 1, 1]
-hunger	-1.0	1.67332	[-4, 0, 2, -2, -1, -2, 1, -2, 0, -2]
-hurrah	2.6	0.8	[3, 2, 3, 3, 1, 3, 4, 2, 2, 3]
-hurrahed	1.9	0.53852	[2, 2, 1, 1, 2, 2, 3, 2, 2, 2]
-hurrahing	2.4	0.4899	[3, 2, 2, 2, 3, 2, 3, 3, 2, 2]
-hurrahs	2.1	1.44568	[2, 3, 0, 3, 2, 3, -1, 2, 3, 4]
-hurray	2.7	0.78102	[3, 2, 3, 3, 1, 3, 4, 2, 3, 3]
-hurrayed	1.8	1.32665	[3, 3, 2, 3, 3, 3, 0, 0, 1, 0]
-hurraying	1.2	1.66132	[2, -3, 2, 3, 0, 2, 2, 2, 0, 2]
-hurrays	2.4	1.11355	[2, 3, 2, 4, 0, 3, 2, 2, 2, 4]
-hurt	-2.4	0.8	[-3, -3, -2, -2, -4, -3, -2, -1, -2, -2]
-hurter	-2.3	0.78102	[-2, -4, -1, -2, -3, -3, -2, -2, -2, -2]
-hurters	-1.9	1.04403	[-2, -3, -1, -2, -1, 0, -3, -3, -3, -1]
-hurtful	-2.4	1.0198	[-2, -4, -2, -2, -1, -3, -2, -3, -1, -4]
-hurtfully	-2.6	0.66332	[-3, -2, -3, -2, -2, -3, -4, -3, -2, -2]
-hurtfulness	-1.9	1.51327	[2, -2, -2, -2, -3, -1, -2, -3, -4, -2]
-hurting	-1.7	0.78102	[-3, -1, -1, -2, -1, -1, -3, -2, -2, -1]
-hurtle	-0.3	1.1	[-2, 1, 0, -1, -1, -1, 0, 2, 0, -1]
-hurtled	-0.6	0.8	[0, -2, 0, 0, 0, 0, -1, -1, -2, 0]
-hurtles	-1.0	0.63246	[-1, -2, 0, 0, -1, -1, -1, -1, -2, -1]
-hurtless	0.3	1.55242	[-1, -3, 2, 1, 2, 1, 0, 0, -1, 2]
-hurtling	-1.4	0.8	[-3, -2, -1, -1, -1, -1, -1, -2, 0, -2]
-hurts	-2.1	0.83066	[-4, -2, -2, -2, -3, -1, -2, -2, -2, -1]
-hypocritical	-2.0	0.89443	[-4, -2, -1, -3, -2, -1, -2, -1, -2, -2]
-hysteria	-1.9	0.7	[-1, -3, -1, -2, -2, -2, -2, -2, -1, -3]
-hysterical	-0.1	1.97231	[2, 0, 0, 3, -2, -2, 3, -1, -2, -2]
-hysterics	-1.8	1.77764	[-3, -3, -3, -1, -3, -1, -2, 3, -3, -2]
-ideal	2.4	1.2	[4, 3, 4, 4, 2, 2, 1, 2, 1, 1]
-idealess	-1.9	1.3	[-4, -2, -3, -2, -1, 0, -4, -1, -1, -1]
-idealise	1.4	0.91652	[2, 2, 1, 0, 1, 3, 2, 0, 1, 2]
-idealised	2.1	0.83066	[1, 4, 1, 3, 2, 2, 2, 2, 2, 2]
-idealises	2.0	0.89443	[1, 4, 1, 2, 2, 2, 2, 3, 1, 2]
-idealising	0.6	0.4899	[0, 1, 1, 1, 1, 1, 1, 0, 0, 0]
-idealism	1.7	1.1	[1, 2, 0, 3, 3, 2, 1, 2, 3, 0]
-idealisms	0.8	0.9798	[0, 2, 3, 1, 0, 0, 1, 0, 0, 1]
-idealist	1.6	1.56205	[2, 3, -2, 1, 3, 3, 1, 0, 2, 3]
-idealistic	1.8	0.9798	[2, 1, 0, 2, 4, 2, 2, 2, 1, 2]
-idealistically	1.7	1.1	[0, 3, 3, 1, 2, 3, 0, 2, 1, 2]
-idealists	0.7	1.1	[0, -2, 1, 2, 1, 1, 2, 0, 1, 1]
-idealities	1.5	0.67082	[2, 1, 1, 2, 1, 0, 2, 2, 2, 2]
-ideality	1.9	0.9434	[0, 1, 2, 3, 2, 1, 2, 3, 3, 2]
-idealization	1.8	0.9798	[2, 2, 2, 1, 4, 2, 2, 0, 1, 2]
-idealizations	1.4	0.66332	[2, 1, 1, 2, 1, 2, 1, 0, 2, 2]
-idealize	1.2	0.9798	[1, 2, 2, 0, 0, 1, 3, 0, 2, 1]
-idealized	1.8	0.74833	[2, 3, 1, 1, 2, 1, 3, 1, 2, 2]
-idealizer	1.3	0.9	[1, 1, 1, 1, 1, 3, 0, 1, 3, 1]
-idealizers	1.9	1.37477	[1, 4, 1, 2, 0, 2, 3, 2, 4, 0]
-idealizes	2.0	1.0	[3, 2, 2, 1, 4, 2, 2, 0, 2, 2]
-idealizing	1.4	1.0198	[1, 1, 2, 3, 0, 1, 3, 0, 2, 1]
-idealless	-1.7	1.00499	[-2, -2, -2, -2, -4, -1, 0, -1, -2, -1]
-ideally	1.8	1.16619	[1, 0, 2, 2, 3, 2, 4, 0, 2, 2]
-idealogues	0.5	0.92195	[1, 0, -1, 2, 0, 0, 2, 0, 1, 0]
-idealogy	0.8	1.16619	[0, 3, 1, 0, 2, 0, 0, 1, 2, -1]
-ideals	0.8	0.6	[0, 1, 0, 2, 1, 1, 1, 0, 1, 1]
-idiot	-2.3	0.64031	[-2, -3, -1, -3, -2, -3, -3, -2, -2, -2]
-idiotic	-2.6	0.91652	[-3, -4, -2, -3, -2, -2, -4, -1, -3, -2]
-ignorable	-1.0	0.63246	[-1, -1, -1, -2, 0, -1, 0, -1, -2, -1]
-ignorami	-1.9	0.83066	[-2, -2, -3, -2, 0, -1, -2, -2, -3, -2]
-ignoramus	-1.9	0.83066	[-1, -2, -1, -3, -1, -3, -1, -3, -2, -2]
-ignoramuses	-2.3	1.1	[-2, -2, -3, -4, 0, -1, -3, -2, -3, -3]
-ignorance	-1.5	1.20416	[-2, -2, -3, -2, 0, -2, -1, -3, -1, 1]
-ignorances	-1.2	0.9798	[0, -1, -2, -1, -2, -2, -1, 1, -2, -2]
-ignorant	-1.1	0.83066	[-1, -1, -1, -2, 1, -2, -1, -2, -1, -1]
-ignorantly	-1.6	0.91652	[-1, -2, -2, -2, -2, -2, -2, 1, -2, -2]
-ignorantness	-1.1	1.44568	[3, -1, -2, -1, -1, -2, -2, -2, -1, -2]
-ignore	-1.5	0.67082	[-1, -2, -1, -1, -1, -1, -2, -3, -2, -1]
-ignored	-1.3	0.45826	[-2, -1, -2, -1, -1, -2, -1, -1, -1, -1]
-ignorer	-1.3	0.45826	[-1, -1, -2, -1, -2, -1, -1, -1, -2, -1]
-ignorers	-0.7	1.00499	[-1, -2, -1, -1, -1, 1, 0, -2, 1, -1]
-ignores	-1.1	0.3	[-1, -1, -2, -1, -1, -1, -1, -1, -1, -1]
-ignoring	-1.7	0.64031	[-1, -1, -1, -2, -2, -3, -2, -1, -2, -2]
-ill	-1.8	0.9798	[-2, 0, -2, -1, -4, -2, -2, -2, -1, -2]
-illegal	-2.6	0.8	[-3, -4, -3, -2, -1, -2, -3, -3, -2, -3]
-illiteracy	-1.9	0.7	[-2, -1, -2, -2, -3, -2, -1, -2, -1, -3]
-illness	-1.7	0.64031	[-2, -1, -2, -2, -3, -2, -1, -2, -1, -1]
-illnesses	-2.2	0.74833	[-2, -2, -2, -4, -2, -3, -2, -1, -2, -2]
-imbecile	-2.2	0.9798	[-3, -2, -3, -3, -3, -1, -3, 0, -2, -2]
-immobilized	-1.2	0.87178	[-1, -3, 0, -1, -1, 0, -2, -1, -2, -1]
-immoral	-2.0	1.09545	[-4, -1, -1, -3, -2, -3, -3, -1, -1, -1]
-immoralism	-1.6	0.91652	[-2, -2, -2, -2, 1, -2, -2, -2, -1, -2]
-immoralist	-2.1	0.3	[-2, -2, -3, -2, -2, -2, -2, -2, -2, -2]
-immoralists	-1.7	0.78102	[-2, -2, -2, -3, -1, -1, -1, -1, -3, -1]
-immoralities	-1.1	1.51327	[-2, -1, -4, -3, 1, 1, -1, 0, -1, -1]
-immorality	-0.6	2.2891	[3, -3, 1, 2, 2, -2, -4, -1, -2, -2]
-immorally	-2.1	0.7	[-1, -1, -2, -2, -3, -2, -3, -2, -2, -3]
-immortal	1.0	1.73205	[3, 3, 2, 2, -2, -2, 2, 1, 1, 0]
-immune	1.2	0.74833	[2, 2, 0, 1, 2, 1, 2, 1, 1, 0]
-impatience	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -1, -2, -2]
-impatiens	-0.2	0.6	[0, 0, -1, 0, 0, 0, 1, -1, -1, 0]
-impatient	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -2]
-impatiently	-1.7	0.64031	[-1, -1, -2, -3, -1, -2, -1, -2, -2, -2]
-imperfect	-1.3	0.64031	[-1, -1, -1, -1, -1, -2, -3, -1, -1, -1]
-impersonal	-1.3	0.45826	[-2, -2, -1, -1, -2, -1, -1, -1, -1, -1]
-impolite	-1.6	0.66332	[-2, -1, -3, -1, -1, -1, -1, -2, -2, -2]
-impolitely	-1.8	0.6	[-2, -2, -1, -1, -2, -1, -2, -2, -3, -2]
-impoliteness	-1.8	0.87178	[-1, -3, -2, -3, -2, -3, -1, -1, -1, -1]
-impolitenesses	-2.3	0.78102	[-3, -2, -2, -1, -1, -3, -3, -2, -3, -3]
-importance	1.5	0.80623	[2, 1, 2, 3, 1, 2, 1, 0, 2, 1]
-importancies	0.4	1.42829	[0, 0, 1, 2, 0, 0, 2, 2, 0, -3]
-importancy	1.4	0.66332	[2, 1, 2, 2, 1, 2, 1, 0, 2, 1]
-important	0.8	1.07703	[0, 0, 0, 2, 1, 0, 0, 3, 2, 0]
-importantly	1.3	0.78102	[2, 1, 2, 1, 2, 2, 0, 0, 1, 2]
-impose	-1.2	0.4	[-1, -1, -1, -1, -2, -1, -2, -1, -1, -1]
-imposed	-0.3	1.41774	[2, -1, -1, -1, 1, 0, -2, 2, -2, -1]
-imposes	-0.4	1.42829	[-2, -1, 1, -2, -1, -1, -2, 1, 2, 1]
-imposing	-0.4	1.0198	[1, -1, -2, -1, 1, 1, 0, -1, -1, -1]
-impotent	-1.1	0.3	[-1, -1, -1, -2, -1, -1, -1, -1, -1, -1]
-impress	1.9	0.53852	[2, 2, 1, 2, 2, 2, 2, 1, 2, 3]
-impressed	2.1	0.3	[2, 2, 2, 2, 2, 2, 3, 2, 2, 2]
-impresses	2.1	0.3	[2, 2, 2, 2, 2, 2, 3, 2, 2, 2]
-impressibility	1.2	1.249	[-1, 2, 0, 2, 0, 2, 2, 3, 2, 0]
-impressible	0.8	1.16619	[2, -1, 1, 0, -1, 2, 1, 0, 2, 2]
-impressing	2.5	0.92195	[3, 4, 1, 2, 3, 2, 3, 1, 3, 3]
-impression	0.9	0.9434	[0, 1, 0, 0, 2, 2, 0, 2, 0, 2]
-impressionable	0.2	1.07703	[0, 0, -1, 1, -1, -1, 0, 2, 0, 2]
-impressionism	0.8	1.07703	[0, 2, 3, 0, 0, 2, 0, 0, 1, 0]
-impressionisms	0.5	0.80623	[0, 0, 0, 0, 0, 2, 0, 1, 0, 2]
-impressionist	1.0	1.09545	[0, 2, 3, 0, 0, 2, 2, 0, 1, 0]
-impressionistic	1.5	1.20416	[2, 2, 0, 0, 1, 0, 2, 2, 4, 2]
-impressionistically	1.6	0.8	[2, 0, 1, 1, 2, 2, 3, 2, 2, 1]
-impressionists	0.5	1.43178	[2, 0, 0, 1, 1, 2, -2, 2, 1, -2]
-impressions	0.9	1.13578	[2, 0, 0, 3, 0, 2, 0, 2, 0, 0]
-impressive	2.3	0.78102	[1, 2, 3, 2, 3, 2, 3, 3, 3, 1]
-impressively	2.0	0.89443	[3, 1, 1, 2, 2, 2, 2, 4, 2, 1]
-impressiveness	1.7	0.64031	[2, 1, 2, 3, 1, 2, 2, 2, 1, 1]
-impressment	-0.4	1.85472	[-2, 1, 3, -2, -1, -3, 0, 0, 2, -2]
-impressments	0.5	1.20416	[2, 0, 0, 1, 2, 2, 0, -2, 0, 0]
-impressure	0.6	1.0198	[-1, 0, 0, 0, 0, 2, 0, 2, 1, 2]
-imprisoned	-2.0	1.0	[-4, -2, -3, -1, -3, -2, -1, -2, -1, -1]
-improve	1.9	0.7	[2, 3, 3, 2, 1, 1, 2, 2, 1, 2]
-improved	2.1	0.7	[3, 1, 2, 3, 2, 3, 1, 2, 2, 2]
-improvement	2.0	0.63246	[2, 3, 3, 2, 1, 1, 2, 2, 2, 2]
-improvements	1.3	0.64031	[0, 2, 2, 1, 2, 2, 1, 1, 1, 1]
-improver	1.8	0.6	[2, 1, 2, 1, 2, 3, 1, 2, 2, 2]
-improvers	1.3	0.78102	[1, 2, 2, 1, 2, 2, 0, 0, 1, 2]
-improves	1.8	1.07703	[3, -1, 2, 2, 2, 3, 1, 2, 2, 2]
-improving	1.8	0.4	[2, 2, 1, 1, 2, 2, 2, 2, 2, 2]
-inability	-1.7	0.9	[-2, -2, -3, 0, -2, -3, -2, -1, -1, -1]
-inaction	-1.0	0.63246	[-2, -1, 0, -1, -1, 0, -1, -2, -1, -1]
-inadequacies	-1.7	0.64031	[-1, -3, -2, -1, -2, -1, -2, -2, -1, -2]
-inadequacy	-1.7	0.78102	[-1, -3, -1, -1, -3, -2, -2, -1, -2, -1]
-inadequate	-1.7	0.64031	[-2, -1, -1, -3, -1, -1, -2, -2, -2, -2]
-inadequately	-1.0	1.26491	[-3, -1, -1, -2, 2, -1, -2, -1, 0, -1]
-inadequateness	-1.7	0.45826	[-2, -2, -1, -1, -1, -2, -2, -2, -2, -2]
-inadequatenesses	-1.6	0.91652	[-1, -1, -2, -1, -2, -4, -2, -1, -1, -1]
-incapable	-1.6	0.4899	[-1, -2, -1, -1, -2, -1, -2, -2, -2, -2]
-incapacitated	-1.9	0.9434	[-2, -2, -1, -1, -2, -4, -1, -1, -2, -3]
-incensed	-2.0	1.0	[-2, -1, -4, 0, -2, -2, -2, -3, -2, -2]
-incentive	1.5	1.0247	[1, 2, 1, 2, 1, 0, 4, 2, 1, 1]
-incentives	1.3	1.34536	[2, 2, 1, 1, 3, 1, -2, 3, 1, 1]
-incompetence	-2.3	0.45826	[-3, -2, -2, -3, -2, -3, -2, -2, -2, -2]
-incompetent	-2.1	0.83066	[-1, -1, -2, -2, -3, -3, -2, -3, -1, -3]
-inconsiderate	-1.9	0.7	[-2, -1, -1, -1, -2, -2, -2, -3, -3, -2]
-inconvenience	-1.5	0.5	[-1, -2, -1, -1, -1, -2, -2, -1, -2, -2]
-inconvenient	-1.4	0.4899	[-2, -2, -1, -2, -1, -2, -1, -1, -1, -1]
-increase	1.3	0.64031	[1, 2, 2, 1, 2, 0, 1, 1, 2, 1]
-increased	1.1	1.04403	[2, 0, 3, 2, 2, 1, 0, 1, 0, 0]
-indecision	-0.8	0.6	[-1, 0, -1, 0, -1, -1, -2, 0, -1, -1]
-indecisions	-1.1	0.53852	[-1, -1, -1, -1, -2, -1, -2, -1, 0, -1]
-indecisive	-1.0	0.44721	[0, -1, -1, -1, -1, -2, -1, -1, -1, -1]
-indecisively	-0.7	1.18743	[-2, -1, -1, -1, -1, -1, -2, 2, 1, -1]
-indecisiveness	-1.3	0.64031	[-1, -3, -1, -2, -1, -1, -1, -1, -1, -1]
-indecisivenesses	-0.9	0.53852	[-1, -1, 0, -1, -1, 0, -1, -2, -1, -1]
-indestructible	0.6	1.85472	[3, 4, -1, -2, 1, 1, 2, 0, -1, -1]
-indifference	-0.2	0.74833	[0, -1, 0, 0, 0, 1, -2, 0, 0, 0]
-indifferent	-0.8	0.6	[-1, 0, 0, -1, -2, -1, -1, 0, -1, -1]
-indignant	-1.8	0.74833	[-1, -3, -2, -2, -2, -1, -1, -1, -3, -2]
-indignation	-2.4	0.8	[-2, -1, -2, -3, -3, -3, -1, -3, -3, -3]
-indoctrinate	-1.4	0.91652	[-1, -3, -1, 0, -2, -1, -2, -2, 0, -2]
-indoctrinated	-0.4	1.35647	[1, -2, -3, 1, -1, 1, 1, -1, -1, 0]
-indoctrinates	-0.6	1.2	[1, -1, -3, 1, -1, 1, -1, -1, -1, -1]
-indoctrinating	-0.7	1.41774	[-1, 0, -3, -1, -2, -1, 2, -2, 0, 1]
-ineffective	-0.5	1.74642	[-2, -1, -1, -1, -2, 2, -2, 1, 3, -2]
-ineffectively	-1.3	0.9	[-2, -2, -2, 1, -1, -1, -1, -2, -1, -2]
-ineffectiveness	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -1, -2, -1]
-ineffectual	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-ineffectuality	-1.6	0.66332	[-2, -1, -1, -1, -2, -1, -3, -2, -2, -1]
-ineffectually	-1.1	0.9434	[-1, -2, -2, -1, 0, -1, -2, -1, 1, -2]
-ineffectualness	-1.3	0.45826	[-2, -1, -1, -1, -1, -2, -1, -1, -2, -1]
-infatuated	0.2	1.72047	[3, 2, 0, 3, -1, -1, -2, 0, -1, -1]
-infatuation	0.6	1.74356	[1, -1, -1, 2, -1, 1, 4, 2, 1, -2]
-infected	-2.2	0.6	[-3, -2, -2, -2, -2, -2, -3, -1, -2, -3]
-inferior	-1.7	0.78102	[-1, -2, -2, -1, -1, -3, -2, -1, -1, -3]
-inferiorities	-1.9	0.7	[-2, -3, -1, -2, -2, -3, -1, -1, -2, -2]
-inferiority	-1.1	1.7	[-2, -3, -2, -2, -2, -3, 2, 1, -1, 1]
-inferiorly	-2.0	0.63246	[-3, -2, -2, -2, -2, -3, -1, -2, -1, -2]
-inferiors	-0.5	1.43178	[-1, -1, -1, -2, -1, 0, 3, -1, 1, -2]
-inflamed	-1.4	1.28062	[-2, -2, -1, -2, -2, -1, 2, -3, -2, -1]
-influential	1.9	1.04403	[3, 1, 2, 3, 4, 1, 1, 2, 1, 1]
-infringement	-2.1	0.83066	[-3, -1, -2, -1, -2, -1, -3, -3, -2, -3]
-infuriate	-2.2	0.87178	[-2, -1, -3, -3, -2, -3, -3, -1, -1, -3]
-infuriated	-3.0	0.7746	[-1, -4, -3, -3, -3, -3, -3, -3, -3, -4]
-infuriates	-2.6	0.8	[-4, -2, -1, -3, -3, -3, -2, -3, -3, -2]
-infuriating	-2.4	1.42829	[-1, -3, -3, -3, -3, -4, 0, 0, -4, -3]
-inhibin	-0.2	0.4	[-1, 0, 0, 0, 0, 0, 0, 0, -1, 0]
-inhibit	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -2]
-inhibited	-0.4	0.4899	[0, 0, -1, 0, -1, -1, 0, -1, 0, 0]
-inhibiting	-0.4	1.42829	[1, -1, -1, -1, -2, -1, 2, -2, 2, -1]
-inhibition	-1.5	0.67082	[-1, -1, -1, -1, -2, -1, -1, -2, -2, -3]
-inhibitions	-0.8	0.74833	[-2, -1, -2, 0, 0, 0, 0, -1, -1, -1]
-inhibitive	-1.4	0.4899	[-2, -2, -1, -1, -2, -1, -2, -1, -1, -1]
-inhibitor	-0.3	1.00499	[-2, 1, 1, -1, 1, 0, -1, -1, 0, -1]
-inhibitors	-1.0	0.7746	[-1, 0, -2, -1, -2, -2, 0, 0, -1, -1]
-inhibitory	-1.0	0.7746	[0, -1, -2, -2, -1, -2, 0, 0, -1, -1]
-inhibits	-0.9	0.53852	[-1, -1, -2, -1, -1, 0, -1, -1, -1, 0]
-injured	-1.7	0.64031	[-2, -1, -1, -1, -2, -1, -2, -2, -3, -2]
-injury	-1.8	0.6	[-2, -2, -1, -2, -1, -1, -2, -3, -2, -2]
-injustice	-2.7	0.64031	[-3, -2, -3, -4, -3, -3, -2, -2, -3, -2]
-innocence	1.6	0.91652	[3, 1, 1, 1, 2, 2, 0, 3, 2, 1]
-innocency	1.9	0.83066	[3, 1, 2, 0, 2, 2, 2, 3, 2, 2]
-innocent	1.4	1.2	[1, -1, 2, 2, 2, 0, 1, 3, 3, 1]
-innocenter	0.9	1.37477	[1, 1, 1, 2, 2, 1, 1, -3, 1, 2]
-innocently	1.4	0.8	[0, 2, 1, 1, 1, 1, 3, 2, 2, 1]
-innocents	1.1	1.04403	[0, 0, 2, 2, 2, -1, 1, 1, 2, 2]
-innovate	2.2	0.74833	[2, 4, 3, 2, 2, 1, 2, 2, 2, 2]
-innovates	2.0	0.89443	[2, 2, 2, 0, 1, 3, 3, 2, 3, 2]
-innovation	1.6	0.91652	[1, 0, 3, 2, 1, 2, 3, 2, 1, 1]
-innovative	1.9	0.83066	[1, 1, 2, 1, 2, 4, 2, 2, 2, 2]
-inquisition	-1.2	1.249	[-2, 1, -1, 0, 0, -3, -1, -3, -2, -1]
-inquisitive	0.7	1.18743	[2, 1, 1, 2, -2, -1, 1, 1, 1, 1]
-insane	-1.7	0.78102	[-2, 0, -2, -1, -2, -3, -2, -2, -1, -2]
-insanity	-2.7	1.00499	[-2, -4, -1, -1, -3, -4, -3, -3, -3, -3]
-insecure	-1.8	0.74833	[-1, -2, -2, -1, -3, -2, -3, -2, -1, -1]
-insecurely	-1.4	0.66332	[-3, -1, -1, -1, -2, -1, -2, -1, -1, -1]
-insecureness	-1.8	0.87178	[-1, -1, -1, -3, -3, -3, -2, -2, -1, -1]
-insecurities	-1.8	0.6	[-3, -2, -2, -2, -1, -2, -1, -1, -2, -2]
-insecurity	-1.8	0.74833	[-2, -2, -2, -1, -3, -3, -2, -1, -1, -1]
-insensitive	-0.9	1.81384	[2, -3, -2, -1, 2, -3, -2, 1, -1, -2]
-insensitivity	-1.8	0.6	[-2, -2, -1, -3, -2, -2, -1, -2, -1, -2]
-insignificant	-1.4	0.8	[-3, -2, -1, -2, -1, -2, 0, -1, -1, -1]
-insincere	-1.8	0.6	[-2, -1, -2, -1, -2, -2, -2, -2, -1, -3]
-insincerely	-1.9	0.7	[-2, -1, -2, -2, -1, -3, -2, -3, -1, -2]
-insincerity	-1.4	1.35647	[-1, -1, -3, -2, -1, 2, -2, -1, -2, -3]
-insipid	-2.0	0.7746	[-1, -2, -2, -1, -3, -3, -3, -2, -2, -1]
-inspiration	2.4	0.8	[3, 3, 3, 3, 1, 3, 1, 3, 2, 2]
-inspirational	2.3	0.64031	[2, 3, 2, 3, 2, 3, 2, 3, 1, 2]
-inspirationally	2.3	0.64031	[3, 2, 2, 3, 3, 1, 2, 2, 3, 2]
-inspirations	2.1	0.53852	[2, 2, 2, 2, 1, 2, 2, 3, 3, 2]
-inspirator	1.9	1.22066	[2, 2, 3, 0, 3, 4, 0, 2, 1, 2]
-inspirators	1.2	0.74833	[3, 1, 1, 2, 1, 1, 1, 1, 0, 1]
-inspiratory	1.5	0.67082	[2, 2, 3, 1, 1, 1, 1, 1, 2, 1]
-inspire	2.7	0.78102	[2, 3, 3, 3, 3, 3, 3, 1, 4, 2]
-inspired	2.2	0.87178	[3, 2, 1, 3, 1, 1, 3, 2, 3, 3]
-inspirer	2.2	1.07703	[3, 2, 2, 4, 0, 2, 3, 1, 3, 2]
-inspirers	2.0	0.63246	[2, 2, 3, 2, 3, 2, 1, 2, 1, 2]
-inspires	1.9	1.04403	[2, 2, 2, 4, 0, 2, 3, 1, 1, 2]
-inspiring	1.8	1.07703	[2, 2, 2, -1, 2, 3, 2, 2, 1, 3]
-inspiringly	2.6	0.4899	[2, 3, 3, 2, 3, 3, 2, 3, 2, 3]
-inspirit	1.9	0.7	[1, 3, 2, 1, 2, 1, 3, 2, 2, 2]
-inspirited	1.3	1.18743	[2, 2, 0, 0, 3, 0, 2, 0, 3, 1]
-inspiriting	1.8	0.4	[1, 2, 1, 2, 2, 2, 2, 2, 2, 2]
-inspiritingly	2.1	1.44568	[3, 2, 2, 2, 4, 1, -1, 3, 4, 1]
-inspirits	0.8	1.46969	[3, 0, 3, -2, 0, 1, 1, 0, 2, 0]
-insult	-2.3	1.00499	[-2, -1, -2, -3, -4, -1, -3, -1, -3, -3]
-insulted	-2.3	0.45826	[-2, -2, -2, -2, -3, -2, -2, -2, -3, -3]
-insulter	-2.0	0.63246	[-2, -1, -2, -2, -1, -3, -3, -2, -2, -2]
-insulters	-2.0	0.44721	[-2, -3, -2, -2, -2, -2, -2, -1, -2, -2]
-insulting	-2.2	0.74833	[-3, -2, -3, -3, -2, -3, -1, -2, -2, -1]
-insultingly	-2.3	0.78102	[-3, -3, -1, -2, -2, -3, -2, -1, -3, -3]
-insults	-1.8	0.6	[-2, -3, -2, -2, -1, -1, -1, -2, -2, -2]
-intact	0.8	0.6	[1, 1, 0, 0, 1, 1, 0, 1, 1, 2]
-integrity	1.6	0.66332	[2, 1, 1, 1, 2, 1, 3, 1, 2, 2]
-intellect	2.0	1.09545	[2, 1, 4, 2, 1, 3, 2, 3, 0, 2]
-intellection	0.6	1.0198	[0, 0, 0, 1, 0, 0, 0, 0, 2, 3]
-intellections	0.8	0.87178	[1, 0, 1, 0, 1, 1, 1, 0, 0, 3]
-intellective	1.7	0.78102	[3, 2, 1, 2, 2, 1, 0, 2, 2, 2]
-intellectively	0.8	0.9798	[0, 0, 1, 1, 0, 3, 0, 1, 2, 0]
-intellects	1.8	0.87178	[1, 0, 2, 1, 3, 2, 2, 2, 3, 2]
-intellectual	2.3	0.9	[3, 3, 1, 2, 3, 4, 2, 2, 1, 2]
-intellectualism	2.2	1.07703	[4, 0, 3, 1, 3, 2, 2, 3, 2, 2]
-intellectualist	2.0	1.0	[4, 0, 2, 1, 3, 2, 2, 2, 2, 2]
-intellectualistic	1.3	1.73494	[1, 4, 0, 3, -2, 0, 2, 3, 0, 2]
-intellectualists	0.8	0.74833	[0, 1, 1, 1, 0, 2, 0, 1, 2, 0]
-intellectualities	1.7	1.34536	[3, 3, 0, 2, 1, 0, 0, 4, 2, 2]
-intellectuality	1.7	1.1	[3, 2, 2, 1, 2, 1, 0, 3, 0, 3]
-intellectualization	1.5	1.11803	[2, 1, 2, 1, 4, 2, 0, 0, 2, 1]
-intellectualize	1.5	0.92195	[1, 2, 1, 1, 3, 2, 3, 0, 1, 1]
-intellectualized	1.2	0.74833	[1, 0, 1, 1, 2, 0, 1, 2, 2, 2]
-intellectualizes	1.8	0.87178	[2, 3, 2, 0, 2, 3, 2, 2, 1, 1]
-intellectualizing	0.8	1.77764	[0, 1, 2, 1, 0, 2, 2, -4, 2, 2]
-intellectually	1.4	0.8	[2, 0, 0, 1, 2, 2, 2, 2, 2, 1]
-intellectualness	1.5	0.80623	[2, 2, 2, 2, 0, 0, 1, 2, 2, 2]
-intellectuals	1.6	0.8	[0, 1, 2, 1, 3, 2, 1, 2, 2, 2]
-intelligence	2.1	0.9434	[3, 2, 2, 1, 3, 3, 3, 2, 2, 0]
-intelligencer	1.5	0.80623	[2, 0, 0, 2, 2, 2, 2, 1, 2, 2]
-intelligencers	1.6	0.91652	[2, 2, 0, 2, 2, 0, 3, 2, 2, 1]
-intelligences	1.6	0.91652	[3, 0, 0, 2, 2, 2, 2, 1, 2, 2]
-intelligent	2.0	0.7746	[1, 2, 2, 1, 4, 2, 2, 2, 2, 2]
-intelligential	1.9	0.9434	[3, 2, 2, 1, 3, 2, 2, 3, 0, 1]
-intelligently	2.0	0.63246	[2, 3, 2, 3, 1, 2, 2, 1, 2, 2]
-intelligentsia	1.5	1.20416	[0, 1, 2, 0, 4, 3, 2, 1, 1, 1]
-intelligibility	1.5	0.80623	[2, 2, 0, 2, 2, 1, 2, 0, 2, 2]
-intelligible	1.4	0.8	[1, 2, 2, 1, 0, 2, 1, 1, 3, 1]
-intelligibleness	1.5	1.20416	[2, 1, 3, -1, 2, 2, 2, 0, 1, 3]
-intelligibly	1.2	0.87178	[1, 2, 1, 2, 1, -1, 2, 2, 1, 1]
-intense	0.3	0.45826	[0, 1, 1, 0, 0, 0, 0, 0, 1, 0]
-interest	2.0	1.18322	[2, 3, 3, 1, 1, 3, 4, 1, 2, 0]
-interested	1.7	0.45826	[2, 1, 2, 2, 1, 2, 2, 2, 1, 2]
-interestedly	1.5	0.67082	[2, 2, 2, 1, 2, 1, 2, 1, 0, 2]
-interesting	1.7	0.78102	[1, 2, 1, 3, 1, 1, 1, 3, 2, 2]
-interestingly	1.7	0.45826	[2, 2, 2, 1, 2, 1, 1, 2, 2, 2]
-interestingness	1.8	0.87178	[2, 3, 1, 3, 1, 3, 2, 1, 1, 1]
-interests	1.0	0.89443	[1, 0, 1, 2, 0, 0, 1, 1, 1, 3]
-interrogated	-1.6	1.0198	[-3, -1, -1, -1, -2, -1, -3, -1, -3, 0]
-interrupt	-1.4	0.4899	[-2, -1, -1, -1, -2, -2, -1, -1, -2, -1]
-interrupted	-1.2	0.6	[-1, -2, -1, 0, -1, -1, -2, -1, -2, -1]
-interrupter	-1.1	0.53852	[-1, -2, -1, 0, -1, -1, -1, -1, -2, -1]
-interrupters	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -1, -2, -1]
-interruptible	-1.3	1.00499	[-2, -1, 0, -2, 0, -3, -2, -1, 0, -2]
-interrupting	-1.2	0.4	[-2, -1, -1, -1, -1, -2, -1, -1, -1, -1]
-interruption	-1.5	0.67082	[-1, -1, -2, -3, -2, -1, -1, -1, -2, -1]
-interruptions	-1.7	0.45826	[-2, -2, -2, -2, -2, -1, -1, -1, -2, -2]
-interruptive	-1.4	0.66332	[-2, -2, -1, -2, -2, 0, -1, -1, -1, -2]
-interruptor	-1.3	0.64031	[-2, -1, -1, -1, 0, -2, -2, -2, -1, -1]
-interrupts	-1.3	0.64031	[-1, -1, -2, -1, -1, -1, -1, -1, -3, -1]
-intimidate	-0.8	1.46969	[-1, -2, -2, -2, -2, -1, 2, 1, 1, -2]
-intimidated	-1.9	0.7	[-2, -1, -3, -3, -1, -2, -2, -1, -2, -2]
-intimidates	-1.3	0.78102	[-2, -1, -1, -1, -3, -2, -1, -1, -1, 0]
-intimidating	-1.9	1.04403	[0, -2, -1, -3, -2, -1, -1, -3, -3, -3]
-intimidatingly	-1.1	1.64012	[2, -2, -3, -1, -2, -2, 2, -2, -1, -2]
-intimidation	-1.8	1.249	[1, -2, -3, -1, -2, -3, -1, -3, -1, -3]
-intimidations	-1.4	1.49666	[1, -2, -2, -2, -1, -1, -1, -4, 1, -3]
-intimidator	-1.6	0.4899	[-1, -1, -2, -2, -1, -2, -2, -1, -2, -2]
-intimidators	-1.6	0.8	[-1, -1, -3, -2, -1, -1, -3, -1, -2, -1]
-intimidatory	-1.1	1.22066	[-1, -2, -3, -1, -1, -1, -2, 2, -1, -1]
-intricate	0.6	0.66332	[1, 0, 2, 1, 0, 1, 1, 0, 0, 0]
-intrigues	0.9	0.9434	[2, -1, 2, 1, 2, 0, 1, 1, 0, 1]
-invigorate	1.9	0.83066	[2, 2, 2, 0, 2, 3, 3, 2, 1, 2]
-invigorated	0.8	1.8868	[-2, 3, 2, 2, -2, -2, 2, 2, 1, 2]
-invigorates	2.1	0.53852	[3, 2, 3, 2, 1, 2, 2, 2, 2, 2]
-invigorating	2.1	0.7	[2, 1, 1, 3, 3, 3, 2, 2, 2, 2]
-invigoratingly	2.0	0.63246	[2, 2, 1, 2, 1, 3, 2, 2, 2, 3]
-invigoration	1.5	1.36015	[2, 2, 1, -2, 1, 3, 3, 2, 1, 2]
-invigorations	1.2	0.87178	[1, -1, 2, 2, 1, 1, 2, 1, 2, 1]
-invigorator	1.1	1.3	[3, 1, 0, 2, 2, -2, 1, 1, 2, 1]
-invigorators	1.2	0.87178	[1, 1, 1, 1, 3, 2, 0, 0, 1, 2]
-invincible	2.2	1.77764	[4, 1, 3, 2, 4, 1, 4, -1, 0, 4]
-invite	0.6	0.66332	[2, 1, 1, 0, 0, 0, 0, 1, 1, 0]
-inviting	1.3	0.45826	[1, 1, 1, 2, 1, 2, 2, 1, 1, 1]
-invulnerable	1.3	1.73494	[2, 3, 4, 2, 0, 3, 0, 1, -2, 0]
-irate	-2.9	0.53852	[-3, -3, -3, -2, -3, -4, -3, -3, -2, -3]
-ironic	-0.5	1.28452	[1, 0, 0, 0, 0, 0, -4, -1, -1, 0]
-irony	-0.2	1.07703	[-1, 0, -3, 0, 0, 0, 1, 0, 1, 0]
-irrational	-1.4	0.4899	[-1, -1, -1, -2, -2, -2, -1, -1, -2, -1]
-irrationalism	-1.5	0.5	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -2]
-irrationalist	-2.1	0.9434	[-1, -4, -2, -2, -3, -3, -2, -1, -1, -2]
-irrationalists	-1.5	0.92195	[-2, -2, -1, -2, -2, 1, -1, -2, -2, -2]
-irrationalities	-1.5	0.80623	[-2, -2, 0, -1, -1, -1, -2, -3, -1, -2]
-irrationality	-1.7	0.9	[-3, -3, -1, -2, -1, -1, -1, -1, -3, -1]
-irrationally	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -2]
-irrationals	-1.1	0.83066	[-2, 0, -1, 0, -1, -1, -3, -1, -1, -1]
-irresistible	1.4	2.2	[2, 3, 2, 3, 4, 4, 1, -1, -2, -2]
-irresolute	-1.4	0.66332	[-2, -2, -1, -2, -1, -1, -1, -2, -2, 0]
-irresponsible	-1.9	0.3	[-2, -2, -2, -2, -2, -2, -1, -2, -2, -2]
-irreversible	-0.8	0.87178	[-2, -2, 0, -1, 0, 0, 0, -1, -2, 0]
-irritabilities	-1.7	0.64031	[-2, -2, -2, -1, -1, -1, -1, -2, -3, -2]
-irritability	-1.4	1.28062	[-2, -1, -2, -1, 2, -2, -2, -2, -1, -3]
-irritable	-2.1	0.7	[-2, -2, -3, -1, -2, -1, -3, -2, -3, -2]
-irritableness	-1.7	0.64031	[-2, -2, -2, -1, -2, -1, -1, -3, -1, -2]
-irritably	-1.8	0.6	[-2, -2, -1, -1, -3, -2, -1, -2, -2, -2]
-irritant	-2.3	0.78102	[-3, -3, -3, -3, -3, -1, -2, -2, -2, -1]
-irritants	-2.1	0.83066	[-2, -3, -1, -4, -2, -1, -2, -2, -2, -2]
-irritate	-1.8	0.6	[-3, -2, -2, -2, -1, -2, -1, -2, -1, -2]
-irritated	-2.0	0.63246	[-1, -2, -2, -2, -3, -2, -2, -3, -1, -2]
-irritates	-1.7	0.78102	[-1, -2, -1, -1, -3, -2, -2, -3, -1, -1]
-irritating	-2.0	0.63246	[-2, -2, -2, -1, -1, -3, -2, -2, -3, -2]
-irritatingly	-2.0	0.44721	[-2, -2, -2, -3, -1, -2, -2, -2, -2, -2]
-irritation	-2.3	0.78102	[-3, -2, -2, -2, -1, -3, -3, -1, -3, -3]
-irritations	-1.5	0.67082	[-2, -2, -1, -1, -1, -1, -1, -2, -3, -1]
-irritative	-2.0	0.63246	[-3, -2, -3, -2, -1, -2, -2, -2, -1, -2]
-isolatable	0.2	1.249	[1, 0, -2, 0, -1, -1, 2, 0, 2, 1]
-isolate	-0.8	0.74833	[-1, -1, -1, 0, 0, 0, 0, -2, -1, -2]
-isolated	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -2, -1, -3, -1]
-isolates	-1.3	0.64031	[-1, -1, -1, -1, -2, -1, -3, -1, -1, -1]
-isolation	-1.7	0.78102	[-1, -3, -1, -2, -2, -1, -3, -1, -2, -1]
-isolationism	0.4	1.62481	[2, 0, -1, -2, -1, 3, 0, 2, -1, 2]
-isolationist	0.7	1.55242	[2, 0, 0, -1, -1, 3, 0, 2, -1, 3]
-isolations	-0.5	1.11803	[-1, -2, -2, -1, 1, 1, -1, 0, 1, -1]
-isolator	-0.4	0.66332	[0, 0, -1, 0, -1, 0, -2, 0, 0, 0]
-isolators	-0.4	1.42829	[-2, -1, -1, -2, 2, 2, -1, 1, -1, -1]
-itchy	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -1, -2, -1]
-jackass	-1.8	1.07703	[-1, 0, -3, -2, -2, -3, 0, -2, -2, -3]
-jackasses	-2.8	0.9798	[-2, -2, -4, -3, -4, -4, -3, -1, -2, -3]
-jaded	-1.6	0.66332	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -3]
-jailed	-2.2	0.87178	[-4, -3, -2, -2, -1, -2, -2, -3, -1, -2]
-jaunty	1.2	0.6	[2, 1, 0, 2, 1, 1, 1, 2, 1, 1]
-jealous	-2.0	0.63246	[-2, -2, -3, -2, -3, -2, -1, -1, -2, -2]
-jealousies	-2.0	0.63246	[-2, -3, -2, -1, -2, -3, -2, -1, -2, -2]
-jealously	-2.0	0.89443	[-1, -3, -1, -4, -2, -2, -1, -2, -2, -2]
-jealousness	-1.7	0.45826	[-1, -2, -2, -2, -2, -1, -1, -2, -2, -2]
-jealousy	-1.3	1.73494	[-2, -3, -2, -2, -2, 2, -3, -1, 2, -2]
-jeopardy	-2.1	0.9434	[-3, -3, -3, -1, -1, -3, -2, -1, -1, -3]
-jerk	-1.4	0.8	[-1, -1, -1, -2, -3, 0, -2, -1, -1, -2]
-jerked	-0.8	0.74833	[0, -1, -1, 0, -2, -1, 0, -1, 0, -2]
-jerks	-1.1	1.51327	[-2, -2, -1, -2, -1, 0, -2, 3, -2, -2]
-jewel	1.5	1.20416	[1, 3, 2, 0, 2, 1, 3, 0, 3, 0]
-jewels	2.0	1.34164	[3, 1, 0, 0, 4, 3, 3, 2, 3, 1]
-jocular	1.2	1.249	[0, 1, 2, -2, 1, 2, 2, 2, 2, 2]
-join	1.2	0.74833	[2, 2, 1, 2, 1, 0, 1, 2, 0, 1]
-joke	1.2	0.74833	[1, 1, 1, 1, 1, 1, 0, 2, 1, 3]
-joked	1.3	0.64031	[1, 1, 2, 2, 0, 2, 1, 1, 2, 1]
-joker	0.5	0.92195	[1, 1, -1, 1, 2, -1, 1, 1, 0, 0]
-jokes	1.0	0.7746	[1, 1, -1, 1, 1, 2, 1, 1, 2, 1]
-jokester	1.5	0.67082	[2, 2, 2, 2, 1, 1, 0, 1, 2, 2]
-jokesters	0.9	0.83066	[0, 0, 2, 1, 1, 2, 2, 0, 1, 0]
-jokey	1.1	0.3	[1, 1, 2, 1, 1, 1, 1, 1, 1, 1]
-joking	0.9	0.53852	[1, 2, 1, 1, 1, 0, 1, 1, 0, 1]
-jollied	2.4	0.66332	[3, 3, 2, 2, 3, 3, 2, 2, 1, 3]
-jollier	2.4	0.4899	[2, 2, 3, 3, 2, 2, 2, 3, 2, 3]
-jollies	2.0	0.63246	[1, 2, 3, 2, 2, 2, 1, 2, 2, 3]
-jolliest	2.9	0.7	[3, 3, 2, 4, 3, 2, 3, 4, 2, 3]
-jollification	2.2	0.74833	[2, 3, 3, 1, 2, 1, 3, 2, 3, 2]
-jollifications	2.0	0.7746	[2, 3, 2, 2, 2, 2, 3, 2, 0, 2]
-jollify	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 3, 1, 2]
-jollily	2.7	0.64031	[3, 3, 3, 3, 3, 3, 3, 1, 3, 2]
-jolliness	2.5	0.67082	[3, 1, 2, 3, 2, 3, 3, 3, 2, 3]
-jollities	1.7	0.64031	[2, 1, 2, 2, 1, 2, 2, 3, 1, 1]
-jollity	1.8	1.6	[3, 2, 1, 1, 4, 3, 1, 2, 3, -2]
-jolly	2.3	1.00499	[4, 3, 3, 1, 1, 1, 3, 2, 3, 2]
-jollying	2.3	0.64031	[2, 3, 3, 1, 3, 3, 2, 2, 2, 2]
-jovial	1.9	0.53852	[2, 2, 1, 2, 1, 2, 3, 2, 2, 2]
-joy	2.8	0.74833	[3, 2, 3, 4, 3, 3, 3, 1, 3, 3]
-joyance	2.3	0.9	[1, 3, 4, 2, 2, 1, 2, 3, 2, 3]
-joyed	2.9	0.3	[3, 3, 3, 3, 3, 3, 3, 2, 3, 3]
-joyful	2.9	0.53852	[3, 2, 3, 3, 2, 3, 4, 3, 3, 3]
-joyfuller	2.4	0.66332	[2, 4, 3, 2, 2, 2, 3, 2, 2, 2]
-joyfully	2.5	0.67082	[2, 2, 3, 3, 2, 2, 3, 4, 2, 2]
-joyfulness	2.7	1.00499	[4, 3, 1, 3, 3, 3, 4, 2, 1, 3]
-joying	2.5	0.67082	[2, 2, 1, 3, 3, 3, 3, 3, 3, 2]
-joyless	-2.5	0.67082	[-1, -2, -3, -3, -3, -3, -2, -2, -3, -3]
-joylessly	-1.7	1.1	[-2, -2, -3, -3, -2, -1, 1, -2, -1, -2]
-joylessness	-2.7	0.9	[-4, -3, -3, -3, -3, -3, -3, -1, -1, -3]
-joyous	3.1	0.7	[3, 4, 3, 2, 4, 3, 3, 4, 2, 3]
-joyously	2.9	0.7	[2, 3, 4, 3, 4, 2, 2, 3, 3, 3]
-joyousness	2.8	0.74833	[3, 3, 1, 3, 3, 3, 4, 2, 3, 3]
-joypop	-0.2	1.93907	[-3, 1, 2, 2, -3, -1, -2, -1, 1, 2]
-joypoppers	-0.1	1.22066	[2, -1, 1, -1, -1, 1, 1, 0, -2, -1]
-joyridden	0.6	1.8	[-2, -1, 4, 0, 0, 2, 1, -1, 0, 3]
-joyride	1.1	1.22066	[-1, 1, 2, 0, 2, 0, 2, 2, 3, 0]
-joyrider	0.7	1.26886	[2, -2, 1, 2, 0, 2, -1, 1, 1, 1]
-joyriders	1.3	1.18743	[1, 0, 0, 1, 4, 3, 1, 1, 1, 1]
-joyrides	0.8	1.32665	[2, -2, 1, 2, 0, 2, -1, 1, 2, 1]
-joyriding	0.9	1.04403	[1, -1, 1, 1, 0, 2, 0, 1, 3, 1]
-joyrode	1.0	1.48324	[4, 0, -2, 0, 2, 1, 2, 1, 1, 1]
-joys	2.2	0.4	[2, 2, 2, 2, 2, 3, 2, 3, 2, 2]
-joystick	0.7	0.78102	[1, 0, 2, 2, 0, 0, 1, 1, 0, 0]
-joysticks	0.2	0.4	[0, 0, 0, 0, 1, 0, 0, 1, 0, 0]
-jubilant	3.0	0.63246	[3, 3, 4, 3, 3, 2, 3, 4, 2, 3]
-jumpy	-1.0	0.63246	[0, 0, -2, -1, -1, -1, -1, -1, -2, -1]
-justice	2.4	1.0198	[3, 2, 1, 2, 3, 2, 4, 4, 2, 1]
-justifiably	1.0	0.7746	[0, 1, 0, 1, 1, 1, 0, 2, 2, 2]
-justified	1.7	0.64031	[1, 2, 2, 3, 1, 1, 1, 2, 2, 2]
-keen	1.5	0.67082	[1, 1, 3, 1, 2, 1, 1, 2, 2, 1]
-keened	0.3	1.00499	[-2, 0, 1, 0, 1, 1, 0, 2, 0, 0]
-keener	0.5	1.20416	[-1, -1, 0, -1, 2, 1, 2, 2, 1, 0]
-keeners	0.6	0.4899	[1, 0, 0, 1, 1, 0, 1, 1, 0, 1]
-keenest	1.9	0.83066	[3, 3, 1, 1, 3, 2, 2, 1, 2, 1]
-keening	-0.7	1.41774	[0, -3, -1, -1, -3, 1, -1, 1, 1, -1]
-keenly	1.0	0.7746	[2, 1, 1, 0, 1, 0, 2, 1, 2, 0]
-keenness	1.4	0.4899	[1, 1, 2, 2, 1, 1, 1, 2, 2, 1]
-keens	0.1	1.22066	[1, -3, 0, 0, 0, 2, 1, 0, 0, 0]
-kewl	1.3	0.45826	[2, 1, 1, 1, 2, 1, 2, 1, 1, 1]
-kidding	0.4	0.8	[0, 1, 0, -1, 1, 1, 1, 1, -1, 1]
-kill	-3.7	0.45826	[-4, -4, -4, -4, -3, -4, -4, -4, -3, -3]
-killdeer	-1.1	1.04403	[-3, 0, 0, -1, -2, 0, -1, -2, -2, 0]
-killdeers	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
-killdees	-0.6	0.66332	[-2, 0, 0, 0, -1, 0, -1, -1, -1, 0]
-killed	-3.5	0.67082	[-3, -3, -2, -4, -4, -4, -3, -4, -4, -4]
-killer	-3.3	0.64031	[-4, -4, -3, -3, -4, -4, -3, -3, -2, -3]
-killers	-3.3	0.45826	[-3, -3, -4, -3, -3, -3, -4, -3, -4, -3]
-killick	0.1	0.3	[0, 1, 0, 0, 0, 0, 0, 0, 0, 0]
-killie	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
-killifish	-0.1	0.7	[0, 0, 0, 0, -2, 0, 0, 0, 1, 0]
-killifishes	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
-killing	-3.4	1.2	[-4, 0, -4, -4, -4, -3, -4, -3, -4, -4]
-killingly	-2.6	1.0198	[-3, -2, -4, -2, -1, -3, -4, -3, -3, -1]
-killings	-3.5	0.67082	[-4, -3, -4, -4, -2, -3, -4, -4, -3, -4]
-killjoy	-2.1	0.83066	[-1, -2, -3, -2, -1, -3, -2, -1, -3, -3]
-killjoys	-1.7	0.9	[-1, -3, -3, -1, -2, -1, -2, 0, -2, -2]
-killock	-0.3	0.64031	[0, 0, 0, 0, -2, 0, 0, 0, -1, 0]
-killocks	-0.4	0.66332	[0, 0, 0, -2, -1, 0, -1, 0, 0, 0]
-kills	-2.5	0.92195	[-2, -3, -2, -3, -4, -1, -3, -3, -1, -3]
-kind	2.4	0.66332	[2, 2, 3, 3, 2, 3, 3, 2, 1, 3]
-kinder	2.2	0.6	[3, 3, 3, 2, 2, 2, 2, 1, 2, 2]
-kindly	2.2	0.4	[2, 2, 2, 3, 2, 2, 2, 2, 2, 3]
-kindness	2.0	0.63246	[2, 1, 3, 3, 2, 1, 2, 2, 2, 2]
-kindnesses	2.3	0.64031	[3, 1, 3, 2, 3, 2, 3, 2, 2, 2]
-kiss	1.8	1.6	[4, 0, 3, 3, 2, 0, 4, 2, 0, 0]
-kissable	2.0	0.89443	[2, 2, 2, 2, 4, 2, 3, 1, 1, 1]
-kissably	1.9	1.04403	[1, 3, 4, 1, 2, 1, 3, 2, 1, 1]
-kissed	1.6	1.11355	[2, 4, 1, 1, 1, 2, 3, 0, 1, 1]
-kisser	1.7	1.34536	[2, 4, 1, 2, -1, 2, 3, 0, 2, 2]
-kissers	1.5	0.80623	[1, 1, 1, 0, 2, 2, 3, 2, 1, 2]
-kisses	2.3	0.9	[2, 4, 2, 2, 1, 2, 4, 2, 2, 2]
-kissing	2.7	0.78102	[3, 3, 4, 1, 3, 2, 2, 3, 3, 3]
-kissy	1.8	0.6	[2, 2, 2, 3, 1, 1, 2, 2, 1, 2]
-kudos	2.3	0.64031	[2, 4, 2, 3, 2, 2, 2, 2, 2, 2]
-lack	-1.3	0.45826	[-1, -1, -1, -1, -2, -1, -2, -1, -1, -2]
-lackadaisical	-1.6	0.66332	[-1, -1, -2, -1, -2, -2, -3, -1, -2, -1]
-lag	-1.4	0.66332	[-1, -1, -1, -1, -1, -3, -1, -2, -2, -1]
-lagged	-1.2	0.6	[-2, -2, -1, -2, -1, -1, 0, -1, -1, -1]
-lagging	-1.1	0.83066	[-2, -2, -2, -1, 0, 0, -1, 0, -1, -2]
-lags	-1.5	0.67082	[-2, -1, -1, -2, -1, -3, -1, -2, -1, -1]
-laidback	0.5	1.28452	[1, -1, 1, -2, -1, 1, 2, 1, 1, 2]
-lame	-1.8	0.74833	[-1, -3, -1, -2, -2, -1, -2, -3, -1, -2]
-lamebrain	-1.6	0.91652	[-3, -2, -1, 0, -3, -1, -1, -2, -2, -1]
-lamebrained	-2.5	0.67082	[-3, -3, -2, -2, -2, -2, -4, -3, -2, -2]
-lamebrains	-1.2	1.46969	[-2, -1, -3, -1, 2, -2, 1, -2, -2, -2]
-lamedh	0.1	0.53852	[0, 0, 0, 0, 0, 1, 1, -1, 0, 0]
-lamella	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
-lamellae	-0.1	0.3	[0, 0, 0, 0, 0, 0, -1, 0, 0, 0]
-lamellas	0.1	0.53852	[0, 0, 0, 0, 0, 1, 0, 1, 0, -1]
-lamellibranch	0.2	0.4	[0, 0, 0, 0, 0, 1, 0, 1, 0, 0]
-lamellibranchs	-0.1	0.3	[0, 0, -1, 0, 0, 0, 0, 0, 0, 0]
-lamely	-2.0	0.89443	[-2, -3, 0, -1, -2, -3, -2, -3, -2, -2]
-lameness	-0.8	1.07703	[-2, -2, -1, -1, -1, 0, 2, -1, -1, -1]
-lament	-2.0	1.26491	[-3, -3, 1, -1, -2, -2, -1, -3, -3, -3]
-lamentable	-1.5	1.0247	[-2, 0, -2, -1, 0, -2, -3, -1, -1, -3]
-lamentableness	-1.3	0.64031	[-2, -1, -1, 0, -2, -1, -1, -1, -2, -2]
-lamentably	-1.5	0.80623	[-2, 0, -3, -1, -1, -2, -2, -1, -1, -2]
-lamentation	-1.4	1.49666	[-3, -2, 0, -3, -1, -1, 2, -2, -1, -3]
-lamentations	-1.9	1.44568	[-2, -2, -2, -3, 2, -1, -3, -3, -2, -3]
-lamented	-1.4	0.91652	[-1, 0, -1, -2, -2, -1, -2, -3, -2, 0]
-lamenter	-1.2	0.87178	[-1, 0, -1, -1, -1, -1, -2, -3, -2, 0]
-lamenters	-0.5	0.67082	[-1, 0, 0, -1, -1, 0, 0, 0, -2, 0]
-lamenting	-2.0	1.09545	[0, -2, -1, -4, -1, -3, -2, -2, -3, -2]
-laments	-1.5	0.80623	[-1, -3, 0, -1, -2, -1, -2, -2, -2, -1]
-lamer	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -1, -2, -2, -1]
-lames	-1.2	0.6	[-2, -1, -1, -2, 0, -1, -1, -2, -1, -1]
-lamest	-1.5	1.28452	[-3, -2, -1, -4, 1, -1, -1, -1, -1, -2]
-landmark	0.3	0.64031	[2, 0, 0, 0, 0, 0, 0, 0, 1, 0]
-laugh	2.6	0.66332	[3, 2, 3, 1, 3, 3, 3, 3, 2, 3]
-laughable	0.2	1.72047	[-2, -1, 3, -1, 2, 2, -1, -1, -1, 2]
-laughableness	1.2	1.6	[2, 0, 3, 2, 2, 1, 3, -2, 2, -1]
-laughably	1.2	1.249	[2, 1, 2, 1, 1, 1, 2, 3, -2, 1]
-laughed	2.0	0.63246	[2, 2, 3, 1, 2, 1, 2, 2, 3, 2]
-laugher	1.7	0.45826	[2, 2, 1, 1, 2, 1, 2, 2, 2, 2]
-laughers	1.7	0.9	[1, 2, 4, 1, 2, 1, 2, 1, 1, 2]
-laughing	2.2	0.87178	[2, 4, 1, 1, 3, 2, 2, 2, 2, 3]
-laughingly	2.3	1.1	[2, 4, 0, 2, 3, 1, 3, 2, 3, 3]
-laughings	1.9	0.7	[2, 1, 1, 1, 2, 3, 2, 2, 3, 2]
-laughingstocks	-1.3	1.26886	[-3, -2, 1, -2, -1, -1, 1, -2, -2, -2]
-laughs	2.2	0.6	[1, 2, 2, 3, 3, 2, 3, 2, 2, 2]
-laughter	2.2	0.6	[2, 3, 2, 2, 2, 2, 3, 1, 3, 2]
-laughters	2.2	0.6	[3, 1, 2, 2, 2, 3, 3, 2, 2, 2]
-launched	0.5	0.80623	[2, 0, 0, 0, 0, 0, 0, 1, 2, 0]
-lawl	1.4	1.42829	[0, 2, 2, 1, 3, -2, 3, 1, 2, 2]
-lawsuit	-0.9	1.22066	[-2, -2, -1, -3, -1, 1, 0, 1, -1, -1]
-lawsuits	-0.6	1.68523	[-2, -1, 0, 3, 2, -1, -1, -2, -2, -2]
-lazier	-2.3	0.64031	[-3, -2, -3, -2, -1, -2, -2, -3, -2, -3]
-laziest	-2.7	0.64031	[-2, -2, -3, -4, -3, -3, -2, -2, -3, -3]
-lazy	-1.5	1.36015	[-3, -1, -3, -2, 2, -1, -1, -2, -2, -2]
-leak	-1.4	0.66332	[-1, -2, -1, -1, -1, -1, -1, -2, -3, -1]
-leaked	-1.3	0.78102	[-2, -2, -1, -3, -1, 0, -1, -1, -1, -1]
-leave	-0.2	0.9798	[1, -1, -1, 0, 0, -1, 2, -1, 0, -1]
-leet	1.3	1.48661	[2, 4, 2, 2, 0, 1, -2, 2, 1, 1]
-legal	0.5	0.80623	[0, 0, 0, 2, 0, 1, 0, 0, 2, 0]
-legally	0.4	0.8	[1, 0, 0, 0, 1, 0, 2, 1, 0, -1]
-lenient	1.1	1.04403	[1, 3, 1, 2, 1, 1, 2, -1, 0, 1]
-lethargic	-1.2	0.74833	[-2, -1, -2, -2, 0, -1, -1, -2, 0, -1]
-lethargy	-1.4	0.91652	[-1, 0, -2, -1, -2, 0, -2, -1, -3, -2]
-liabilities	-0.8	0.9798	[-1, 2, -1, -1, -1, -1, -1, -1, -2, -1]
-liability	-0.8	1.83303	[-2, -3, -1, -1, 3, -3, -1, -1, 2, -1]
-liar	-2.3	0.78102	[-1, -2, -3, -3, -2, -2, -3, -1, -3, -3]
-liards	-0.4	0.91652	[-2, 0, -1, 0, 0, 1, 0, 0, -2, 0]
-liars	-2.4	0.66332	[-3, -2, -2, -3, -2, -1, -3, -3, -2, -3]
-libelous	-2.1	1.3	[-3, -1, -1, -2, 1, -3, -3, -3, -3, -3]
-libertarian	0.9	0.9434	[1, 2, 0, 1, 0, 0, 0, 3, 1, 1]
-libertarianism	0.4	0.8	[0, 0, 2, 0, 2, 0, 0, 0, 0, 0]
-libertarianisms	0.1	1.13578	[0, 0, 0, 2, 2, 0, -2, 0, -1, 0]
-libertarians	0.1	0.83066	[0, 0, 1, 0, 0, -1, -1, 0, 2, 0]
-liberties	2.3	0.78102	[2, 4, 3, 2, 2, 1, 2, 3, 2, 2]
-libertinage	0.2	1.53623	[-1, -1, 0, 0, 4, 0, -2, 1, 1, 0]
-libertine	-0.9	1.44568	[0, -1, 0, 0, -1, -3, 2, -2, -1, -3]
-libertines	0.4	1.35647	[-1, 3, -1, -1, 1, 1, 1, 2, 0, -1]
-libertinisms	1.2	1.249	[0, 0, 3, 1, 1, 1, 4, 0, 1, 1]
-liberty	2.4	0.91652	[2, 2, 3, 3, 3, 3, 2, 4, 1, 1]
-lied	-1.6	1.2	[-3, 0, -3, 1, -2, -1, -2, -2, -2, -2]
-lies	-1.8	0.9798	[-1, -1, -1, 0, -2, -3, -3, -2, -3, -2]
-lifesaver	2.8	0.74833	[3, 3, 4, 2, 3, 1, 3, 3, 3, 3]
-lighthearted	1.8	0.4	[2, 2, 2, 2, 1, 2, 2, 1, 2, 2]
-like	1.5	0.67082	[1, 2, 2, 2, 1, 3, 1, 1, 1, 1]
-likeable	2.0	0.63246	[1, 3, 2, 2, 2, 3, 2, 1, 2, 2]
-liked	1.8	0.6	[2, 2, 1, 2, 2, 1, 3, 1, 2, 2]
-likes	1.8	0.6	[2, 2, 1, 2, 2, 2, 3, 1, 1, 2]
-liking	1.7	0.78102	[3, 1, 2, 1, 1, 2, 3, 1, 2, 1]
-limitation	-1.2	0.6	[-2, -1, 0, -1, -1, -2, -1, -2, -1, -1]
-limited	-0.9	0.53852	[-1, -1, 0, -2, -1, 0, -1, -1, -1, -1]
-litigation	-0.8	0.6	[0, -2, -1, 0, -1, -1, -1, -1, 0, -1]
-litigious	-0.8	0.9798	[-2, -1, 0, -2, 0, -2, 1, -1, 0, -1]
-livelier	1.7	0.78102	[2, 2, 1, 3, 1, 3, 2, 1, 1, 1]
-liveliest	2.1	0.9434	[2, 1, 2, 3, 1, 1, 2, 4, 3, 2]
-livelihood	0.8	1.07703	[0, 3, 1, 0, 2, 2, 0, 0, 0, 0]
-livelihoods	0.9	1.13578	[0, 0, 0, 3, 2, 2, 0, 2, 0, 0]
-livelily	1.8	0.6	[2, 2, 2, 3, 1, 2, 1, 2, 2, 1]
-liveliness	1.6	0.8	[1, 3, 0, 2, 2, 2, 2, 2, 1, 1]
-livelong	1.7	0.78102	[3, 0, 1, 1, 2, 2, 2, 2, 2, 2]
-lively	1.9	0.7	[2, 2, 3, 1, 1, 2, 3, 1, 2, 2]
-livid	-2.5	0.92195	[-2, -3, -1, -2, -4, -3, -1, -3, -3, -3]
-lmao	2.9	0.9434	[3, 4, 3, 1, 2, 4, 3, 3, 2, 4]
-loathe	-2.2	2.08806	[-1, -4, -3, -2, -4, 2, 1, -3, -4, -4]
-loathed	-2.1	1.44568	[-4, -3, -3, -3, -1, 1, -1, -1, -3, -3]
-loathes	-1.9	1.13578	[-1, -4, -1, -3, -3, -1, -1, -3, -1, -1]
-loathing	-2.7	0.78102	[-3, -3, -3, -1, -4, -2, -3, -3, -2, -3]
-lobby	0.1	0.53852	[0, 0, 0, 1, 0, 1, 0, -1, 0, 0]
-lobbying	-0.3	0.45826	[0, -1, 0, 0, 0, 0, 0, -1, -1, 0]
-lol	1.8	1.46969	[1, 3, 4, 1, 2, 4, 1, 2, -1, 1]
-lone	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -1]
-lonelier	-1.4	0.66332	[-2, -1, -2, -2, 0, -2, -1, -1, -1, -2]
-loneliest	-2.4	0.8	[-3, -1, -2, -4, -2, -2, -3, -3, -2, -2]
-loneliness	-1.8	0.6	[-2, -2, -1, -3, -2, -2, -1, -2, -1, -2]
-lonelinesses	-1.5	1.36015	[-2, -2, -1, -1, 2, -1, -3, -2, -3, -2]
-lonely	-1.5	0.5	[-1, -2, -2, -1, -1, -1, -1, -2, -2, -2]
-loneness	-1.1	0.83066	[-1, -2, -1, -2, -1, -1, -2, 1, -1, -1]
-loner	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -2, -2, -1]
-loners	-0.9	0.53852	[-1, -1, -2, -1, -1, -1, 0, 0, -1, -1]
-lonesome	-1.5	0.67082	[-2, -1, -2, -1, -2, -1, -2, 0, -2, -2]
-lonesomely	-1.3	1.00499	[-2, -2, -2, -2, -1, -2, 0, -2, -1, 1]
-lonesomeness	-1.8	0.6	[-2, -2, -1, -3, -1, -2, -2, -2, -1, -2]
-lonesomes	-1.4	0.4899	[-2, -1, -1, -1, -1, -1, -2, -2, -2, -1]
-longing	-0.1	0.9434	[0, -1, 0, -1, -1, 0, 2, -1, 1, 0]
-longingly	0.7	0.45826	[1, 0, 1, 0, 1, 1, 1, 0, 1, 1]
-longings	0.4	1.2	[2, 0, -1, -1, 0, 1, 3, 0, 0, 0]
-loom	-0.9	0.53852	[-1, -1, -1, -1, -1, -2, 0, -1, -1, 0]
-loomed	-1.1	1.04403	[-2, -2, -1, -1, -1, -1, 0, -1, -3, 1]
-looming	-0.5	1.5	[-2, -1, -1, 0, -2, -2, 3, -1, 0, 1]
-looms	-0.6	1.0198	[-1, -2, -1, -1, 0, 0, 1, -2, 1, -1]
-loose	-1.3	1.18743	[-2, -1, 0, -2, 0, -1, 0, -2, -4, -1]
-looses	-0.6	0.91652	[0, -1, 0, -1, 0, 0, 0, 0, -3, -1]
-lose	-1.7	0.45826	[-1, -2, -1, -2, -1, -2, -2, -2, -2, -2]
-loser	-2.4	0.66332	[-3, -2, -2, -2, -2, -3, -3, -1, -3, -3]
-losers	-2.4	0.8	[-3, -1, -2, -2, -4, -2, -3, -3, -2, -2]
-loses	-1.3	1.00499	[0, -1, -1, -1, -1, -4, -1, -1, -2, -1]
-losing	-1.6	0.8	[-1, -1, -1, -2, -1, -2, -3, -3, -1, -1]
-loss	-1.3	0.45826	[-1, -2, -1, -1, -1, -2, -2, -1, -1, -1]
-losses	-1.7	0.9	[-2, -1, -2, -3, 0, -1, -3, -1, -2, -2]
-lossy	-1.2	0.87178	[-2, -2, -1, -2, 0, 0, 0, -1, -2, -2]
-lost	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -2, -1, -1, -1]
-louse	-1.6	1.2	[-1, -1, -3, -4, 0, -3, -1, -1, -1, -1]
-loused	-1.0	0.7746	[-1, -1, -1, -1, 0, 0, -2, 0, -2, -2]
-louses	-1.3	0.78102	[-2, -1, -2, -1, -1, 0, -2, 0, -2, -2]
-lousewort	0.1	1.3	[-2, -2, 1, 0, 0, 0, 0, 2, 2, 0]
-louseworts	-0.6	0.66332	[0, 0, 0, -2, 0, -1, 0, -1, -1, -1]
-lousier	-2.2	0.4	[-2, -3, -2, -2, -3, -2, -2, -2, -2, -2]
-lousiest	-2.6	0.8	[-4, -2, -3, -3, -1, -2, -3, -3, -2, -3]
-lousily	-1.2	0.9798	[-1, -1, -2, -2, -2, -2, 0, -1, 1, -2]
-lousiness	-1.7	0.64031	[-2, -2, -1, -1, -2, -2, -3, -2, -1, -1]
-lousing	-1.1	0.9434	[-3, 0, 0, 0, -1, -2, -1, -2, -1, -1]
-lousy	-2.5	0.67082	[-2, -4, -2, -3, -2, -3, -2, -2, -3, -2]
-lovable	3.0	0.63246	[3, 3, 3, 4, 3, 2, 3, 3, 2, 4]
-love	3.2	0.4	[3, 3, 3, 3, 3, 3, 3, 4, 4, 3]
-loved	2.9	0.7	[3, 3, 4, 2, 2, 4, 3, 2, 3, 3]
-lovelies	2.2	0.74833	[3, 3, 3, 1, 2, 2, 3, 2, 1, 2]
-lovely	2.8	0.6	[2, 3, 3, 3, 2, 3, 4, 3, 2, 3]
-lover	2.8	0.87178	[3, 1, 2, 3, 4, 3, 2, 3, 4, 3]
-loverly	2.8	0.74833	[3, 2, 4, 3, 3, 2, 3, 2, 2, 4]
-lovers	2.4	1.11355	[2, 3, 2, 4, 4, 1, 1, 3, 3, 1]
-loves	2.7	0.9	[3, 3, 3, 2, 2, 4, 4, 2, 1, 3]
-loving	2.9	0.53852	[3, 2, 3, 3, 3, 2, 4, 3, 3, 3]
-lovingly	3.2	0.6	[3, 3, 3, 4, 4, 4, 2, 3, 3, 3]
-lovingness	2.7	1.67631	[4, 4, 3, 3, 2, 3, -2, 4, 3, 3]
-low	-1.1	0.53852	[-1, -1, -1, -1, -1, -2, -1, -2, 0, -1]
-lowball	-0.8	0.87178	[-1, -2, 0, -2, -1, -1, 0, 1, -1, -1]
-lowballed	-1.5	0.67082	[-2, 0, -1, -1, -2, -2, -1, -2, -2, -2]
-lowballing	-0.7	0.78102	[-2, -1, -1, 1, 0, -1, -1, 0, -1, -1]
-lowballs	-1.2	0.74833	[-1, -1, -1, -1, -3, -1, -2, 0, -1, -1]
-lowborn	-0.7	1.1	[-1, 0, -1, 0, -2, -1, -2, -1, -1, 2]
-lowboys	-0.6	1.0198	[-1, 0, 0, 0, -3, -1, 1, 0, -1, -1]
-lowbred	-2.6	1.0198	[-2, -1, -2, -4, -2, -2, -4, -4, -3, -2]
-lowbrow	-1.9	0.7	[-1, -3, -1, -2, -2, -2, -1, -3, -2, -2]
-lowbrows	-0.6	0.66332	[0, 0, -1, 0, -2, -1, -1, 0, 0, -1]
-lowdown	-0.8	0.9798	[-1, -1, 0, 0, 0, -2, -3, 0, -1, 0]
-lowdowns	-0.2	0.4	[0, 0, 0, -1, 0, 0, 0, 0, -1, 0]
-lowe	0.5	0.80623	[0, 0, 0, 0, 0, 1, 0, 0, 2, 2]
-lowed	-0.8	0.6	[0, -1, -1, -2, -1, 0, -1, 0, -1, -1]
-lower	-1.2	0.87178	[0, -2, -1, -1, -2, 0, -2, 0, -2, -2]
-lowercase	0.3	0.45826	[0, 0, 0, 0, 1, 0, 1, 0, 1, 0]
-lowercased	-0.2	0.4	[0, -1, 0, 0, 0, 0, -1, 0, 0, 0]
-lowerclassman	-0.4	0.4899	[0, -1, -1, -1, 0, 0, 0, 0, 0, -1]
-lowered	-0.5	1.11803	[-1, -1, -2, -1, -1, 2, -1, -1, 1, 0]
-lowering	-1.0	0.7746	[0, -1, -1, -1, -1, 0, -3, -1, -1, -1]
-lowermost	-1.4	1.11355	[-1, -1, -3, -1, -1, -1, -2, -3, 1, -2]
-lowers	-0.5	0.5	[-1, -1, 0, -1, 0, 0, 0, -1, -1, 0]
-lowery	-1.8	0.87178	[-1, -1, -2, -3, -1, -2, -3, -3, -1, -1]
-lowest	-1.6	0.4899	[-2, -2, -2, -2, -1, -2, -1, -1, -1, -2]
-lowing	-0.5	0.67082	[0, 0, 0, -1, 0, 0, -1, -2, -1, 0]
-lowish	-0.9	0.53852	[-2, -1, -1, 0, -1, 0, -1, -1, -1, -1]
-lowland	-0.1	0.3	[0, 0, -1, 0, 0, 0, 0, 0, 0, 0]
-lowlander	-0.4	0.66332	[0, 0, 0, 0, 0, 0, -1, -1, -2, 0]
-lowlanders	-0.3	0.64031	[0, 0, 0, -2, 0, -1, 0, 0, 0, 0]
-lowlands	-0.1	0.7	[0, -1, -1, 0, -1, 1, 0, 1, 0, 0]
-lowlier	-1.7	0.78102	[-2, -2, -2, -3, -1, -2, -2, -1, 0, -2]
-lowliest	-1.8	1.6	[-1, -3, -3, -4, -2, -1, -1, 0, 1, -4]
-lowlife	-1.5	0.67082	[-2, -2, -2, -1, -1, -2, -1, 0, -2, -2]
-lowlifes	-2.2	1.249	[-3, -2, -3, -4, -2, 1, -2, -3, -2, -2]
-lowlight	-2.0	1.26491	[-3, -2, -1, -3, 1, -2, -1, -3, -3, -3]
-lowlights	-0.3	0.78102	[0, 0, -1, 1, -2, -1, 0, 0, 0, 0]
-lowlihead	-0.3	1.34536	[-1, -1, 1, -3, 0, 0, 1, -1, 2, -1]
-lowliness	-1.1	0.53852	[-1, -2, -1, -2, -1, -1, -1, 0, -1, -1]
-lowlinesses	-1.2	1.07703	[-3, -1, -2, -2, 0, -1, -1, -1, -2, 1]
-lowlives	-2.1	0.7	[-2, -3, -3, -2, -1, -2, -3, -2, -1, -2]
-lowly	-1.0	1.34164	[-1, -2, -1, -2, 2, -2, -1, 1, -2, -2]
-lown	0.9	1.13578	[2, 2, 1, -1, 0, 1, 2, -1, 1, 2]
-lowness	-1.3	0.45826	[-1, -2, -2, -1, -1, -2, -1, -1, -1, -1]
-lowrider	-0.2	0.4	[0, 0, 0, -1, -1, 0, 0, 0, 0, 0]
-lowriders	0.1	0.53852	[0, 0, 0, 0, 1, 0, -1, 0, 1, 0]
-lows	-0.8	0.9798	[0, -1, -1, -1, 0, 1, -3, -1, -1, -1]
-lowse	-0.7	0.78102	[0, -1, 1, -1, -1, -1, 0, -1, -2, -1]
-loyal	2.1	0.7	[3, 2, 1, 1, 2, 2, 3, 2, 3, 2]
-loyalism	1.0	0.89443	[1, 2, 1, -1, 0, 1, 2, 1, 1, 2]
-loyalisms	0.9	0.83066	[2, 0, 0, 1, 1, 0, 2, 2, 1, 0]
-loyalist	1.5	0.92195	[1, 0, 2, 2, 3, 0, 2, 2, 1, 2]
-loyalists	1.1	0.83066	[1, 1, 1, 3, 0, 2, 1, 0, 1, 1]
-loyally	2.1	0.7	[3, 2, 2, 2, 1, 3, 1, 2, 3, 2]
-loyalties	1.9	0.7	[3, 1, 2, 2, 2, 3, 2, 1, 1, 2]
-loyalty	2.5	0.67082	[1, 3, 3, 3, 3, 2, 2, 2, 3, 3]
-luck	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
-lucked	1.9	0.7	[2, 2, 2, 1, 1, 2, 3, 3, 1, 2]
-luckie	1.6	0.66332	[1, 1, 1, 2, 2, 1, 1, 2, 2, 3]
-luckier	1.9	0.7	[1, 3, 1, 2, 2, 1, 2, 3, 2, 2]
-luckiest	2.9	0.7	[3, 3, 4, 2, 2, 4, 3, 3, 2, 3]
-luckily	2.3	0.45826	[2, 2, 3, 2, 2, 3, 2, 2, 2, 3]
-luckiness	1.0	1.61245	[2, 2, 1, -2, 3, 1, 1, 2, 2, -2]
-lucking	1.2	0.6	[2, 1, 1, 0, 1, 1, 1, 2, 2, 1]
-luckless	-1.3	0.45826	[-2, -1, -2, -1, -1, -1, -2, -1, -1, -1]
-lucks	1.6	0.91652	[0, 3, 1, 1, 3, 2, 2, 1, 2, 1]
-lucky	1.8	0.74833	[2, 1, 1, 1, 3, 2, 1, 2, 2, 3]
-ludicrous	-1.5	1.36015	[2, -2, -2, -1, -1, -1, -3, -3, -2, -2]
-ludicrously	-0.2	1.83303	[3, -1, 0, -2, -1, 0, 3, -3, -1, 0]
-ludicrousness	-1.9	1.57797	[-1, 2, -2, -3, -2, -2, -3, -4, -1, -3]
-lugubrious	-2.1	1.37477	[-3, -2, -3, -3, -3, 1, -2, -3, 0, -3]
-lulz	2.0	1.0	[2, 2, 2, 3, 4, 1, 3, 1, 1, 1]
-lunatic	-2.2	1.32665	[-2, -3, -4, -2, -3, -2, -1, -3, 1, -3]
-lunatics	-1.6	1.95959	[-4, -2, -3, -4, -2, 2, -1, -3, 1, 0]
-lurk	-0.8	0.87178	[-1, -1, 0, -3, -1, 0, -1, 0, -1, 0]
-lurking	-0.5	1.11803	[1, -1, -1, 0, -1, -2, 1, -2, 1, -1]
-lurks	-0.9	1.04403	[-1, -1, -1, -2, -2, -1, -1, -1, 2, -1]
-lying	-2.4	0.8	[-2, -4, -3, -1, -2, -2, -3, -2, -2, -3]
-mad	-2.2	0.74833	[-3, -3, -1, -1, -2, -3, -2, -2, -3, -2]
-maddening	-2.2	0.74833	[-3, -3, -1, -1, -3, -2, -2, -3, -2, -2]
-madder	-1.2	1.16619	[-2, 0, -3, 0, 0, -1, -3, -1, -2, 0]
-maddest	-2.8	1.16619	[-4, -4, -4, -4, -1, -3, -2, -1, -2, -3]
-madly	-1.7	1.1	[-2, 0, -2, -2, -2, -1, -4, -2, 0, -2]
-madness	-1.9	0.53852	[-1, -2, -1, -3, -2, -2, -2, -2, -2, -2]
-magnific	2.3	1.1	[2, 2, 0, 2, 4, 4, 2, 2, 3, 2]
-magnifical	2.4	1.28062	[1, 4, 1, 2, 4, 3, 1, 1, 4, 3]
-magnifically	2.4	1.2	[3, 3, 3, 2, 4, 0, 1, 2, 2, 4]
-magnification	1.0	0.89443	[2, 3, 1, 0, 0, 1, 1, 1, 0, 1]
-magnifications	1.2	1.249	[-1, 0, 0, 2, 2, 2, 0, 2, 3, 2]
-magnificence	2.4	1.0198	[3, 2, 1, 3, 2, 1, 4, 4, 2, 2]
-magnificences	2.3	0.9	[3, 4, 3, 1, 3, 2, 1, 2, 2, 2]
-magnificent	2.9	0.7	[2, 4, 2, 4, 3, 3, 3, 3, 2, 3]
-magnificently	3.4	0.66332	[3, 3, 3, 4, 4, 2, 4, 4, 3, 4]
-magnifico	1.8	0.87178	[2, 1, 1, 2, 1, 1, 3, 3, 3, 1]
-magnificoes	1.4	0.8	[2, 2, 0, 2, 1, 1, 3, 1, 1, 1]
-mandatory	0.3	0.9	[1, 0, -1, 0, -1, 0, 1, 2, 0, 1]
-maniac	-2.1	0.7	[-1, -2, -2, -2, -3, -3, -1, -2, -2, -3]
-maniacal	-0.3	1.73494	[2, -1, -3, -3, 0, 2, -1, 1, 1, -1]
-maniacally	-1.7	0.78102	[-1, -2, -1, -2, -3, -2, -1, -3, -1, -1]
-maniacs	-1.2	1.8868	[-3, 1, -2, 1, -3, -2, 0, 2, -3, -3]
-manipulated	-1.6	0.4899	[-2, -1, -1, -2, -1, -2, -2, -1, -2, -2]
-manipulating	-1.5	0.80623	[-1, -1, -1, -2, -2, -1, -2, -2, -3, 0]
-manipulation	-1.2	1.72047	[2, -3, -2, -3, -1, -1, -2, 2, -2, -2]
-marvel	1.8	0.6	[2, 1, 1, 2, 1, 2, 3, 2, 2, 2]
-marvelous	2.9	0.7	[2, 2, 3, 2, 3, 3, 4, 3, 4, 3]
-marvels	2.0	0.89443	[3, 1, 1, 3, 1, 2, 1, 2, 3, 3]
-masochism	-1.6	1.11355	[-1, 0, -2, -2, -2, -2, 0, -4, -1, -2]
-masochisms	-1.1	1.57797	[3, -3, -2, -2, -1, -1, -2, -1, 0, -2]
-masochist	-1.7	0.9	[-1, 0, -3, -1, -2, -2, -2, -2, -1, -3]
-masochistic	-2.2	1.16619	[-1, -1, -1, -2, -3, -2, -4, -3, -4, -1]
-masochistically	-1.6	1.35647	[-1, -1, -3, -3, -3, -3, 0, -2, 1, -1]
-masochists	-1.2	1.07703	[1, -2, 0, -2, -3, -1, -2, -1, -1, -1]
-masterpiece	3.1	0.83066	[3, 4, 4, 4, 2, 2, 2, 4, 3, 3]
-masterpieces	2.5	0.67082	[2, 2, 3, 2, 2, 2, 4, 3, 3, 2]
-matter	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
-matters	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
-mature	1.8	0.4	[2, 2, 2, 2, 2, 1, 2, 2, 1, 2]
-meaningful	1.3	0.9	[0, 0, 2, 1, 1, 3, 1, 2, 2, 1]
-meaningless	-1.9	0.7	[-1, -2, -2, -2, -1, -1, -2, -3, -3, -2]
-medal	2.1	1.22066	[2, 4, 3, 1, 0, 2, 2, 2, 1, 4]
-mediocrity	-0.3	1.1	[-1, 0, -2, 0, -1, 2, -1, -1, 0, 1]
-meditative	1.4	0.66332	[2, 0, 1, 2, 2, 1, 2, 1, 2, 1]
-meh	-0.3	0.78102	[-1, 0, -1, 0, -1, -1, 1, 0, 1, -1]
-melancholia	-0.5	1.28452	[0, -2, -2, 0, 1, -1, 2, -2, 0, -1]
-melancholiac	-2.0	0.63246	[-2, -2, -3, -2, -2, -3, -1, -1, -2, -2]
-melancholias	-1.6	0.8	[-1, -2, -3, -2, 0, -2, -1, -1, -2, -2]
-melancholic	-0.3	1.18743	[0, 2, -2, 0, 1, -1, 0, -2, 0, -1]
-melancholics	-1.0	1.0	[0, -1, -3, 1, -1, -2, -1, -1, -1, -1]
-melancholies	-1.1	0.83066	[-1, 0, -1, 0, -3, -1, -2, -1, -1, -1]
-melancholy	-1.9	1.13578	[-3, -2, -3, -2, -3, -2, -2, 1, -1, -2]
-menace	-2.2	0.87178	[-3, -3, -2, -1, -1, -2, -3, -1, -3, -3]
-menaced	-1.7	1.48661	[-3, -2, -2, -3, -3, -1, 1, -3, 1, -2]
-mercy	1.5	0.67082	[1, 2, 1, 1, 1, 3, 2, 2, 1, 1]
-merit	1.8	0.74833	[2, 2, 2, 2, 0, 2, 3, 2, 2, 1]
-merited	1.4	0.4899	[1, 2, 2, 1, 1, 1, 2, 1, 2, 1]
-meriting	1.1	1.13578	[1, 2, 1, -2, 1, 1, 2, 2, 1, 2]
-meritocracy	0.6	1.35647	[2, 4, 0, 0, 1, -1, 0, 0, 0, 0]
-meritocrat	0.4	0.8	[0, 0, 0, 1, -1, 0, 0, 1, 2, 1]
-meritocrats	1.1	1.13578	[2, 1, 1, 0, 0, 1, 1, 4, 0, 1]
-meritorious	2.1	0.53852	[3, 2, 2, 2, 2, 2, 2, 2, 3, 1]
-meritoriously	1.3	1.95192	[3, -1, 3, -2, 2, 0, -1, 3, 3, 3]
-meritoriousness	1.7	1.18743	[4, 1, 2, 1, 2, 0, 3, 2, 2, 0]
-merits	1.7	0.78102	[1, 3, 1, 1, 2, 2, 1, 1, 3, 2]
-merrier	1.7	1.41774	[3, 2, 2, 3, 2, 2, -1, -1, 3, 2]
-merriest	2.7	1.41774	[3, 4, 4, 4, 2, 3, -1, 2, 3, 3]
-merrily	2.4	0.66332	[3, 3, 2, 2, 2, 3, 2, 3, 1, 3]
-merriment	2.4	1.35647	[1, 3, 3, 4, 2, -1, 3, 3, 3, 3]
-merriments	2.0	0.89443	[2, 2, 3, 3, 0, 2, 2, 1, 2, 3]
-merriness	2.2	0.74833	[2, 1, 2, 3, 2, 2, 3, 3, 1, 3]
-merry	2.5	0.80623	[2, 4, 2, 2, 3, 3, 3, 3, 2, 1]
-merrymaker	2.2	1.4	[3, 1, 3, 3, 3, -1, 2, 1, 3, 4]
-merrymakers	1.7	1.34536	[1, 4, 1, 3, 1, 3, -1, 2, 1, 2]
-merrymaking	2.2	0.6	[3, 2, 2, 2, 2, 1, 3, 3, 2, 2]
-merrymakings	2.4	1.11355	[3, 3, 2, 3, 4, 2, 0, 3, 1, 3]
-merrythought	1.1	0.9434	[1, 1, 3, 0, 2, 0, 0, 1, 2, 1]
-merrythoughts	1.6	1.11355	[1, 3, 2, 1, 2, 1, 0, 3, 3, 0]
-mess	-1.5	0.92195	[-1, -3, -1, -1, -3, -1, -2, -1, 0, -2]
-messed	-1.4	0.8	[-2, -1, -1, -3, 0, -2, -2, -1, -1, -1]
-messy	-1.5	0.80623	[-1, -2, -2, -2, -1, -1, -2, 0, -1, -3]
-methodical	0.6	0.8	[0, 0, 0, 2, 2, 0, 1, 1, 0, 0]
-mindless	-1.9	0.7	[-2, -1, -2, -1, -1, -2, -3, -3, -2, -2]
-miracle	2.8	0.87178	[4, 4, 3, 2, 3, 4, 2, 2, 2, 2]
-mirth	2.6	0.66332	[3, 3, 3, 2, 3, 3, 3, 2, 1, 3]
-mirthful	2.7	0.45826	[3, 3, 3, 2, 3, 3, 3, 2, 3, 2]
-mirthfully	2.0	1.48324	[2, 3, 4, 3, 0, -1, 2, 1, 3, 3]
-misbehave	-1.9	0.7	[-3, -3, -1, -2, -2, -1, -1, -2, -2, -2]
-misbehaved	-1.6	0.4899	[-1, -2, -1, -2, -2, -2, -1, -2, -1, -2]
-misbehaves	-1.6	0.4899	[-1, -2, -2, -1, -2, -2, -1, -2, -1, -2]
-misbehaving	-1.7	0.64031	[-1, -2, -1, -2, -3, -2, -1, -2, -1, -2]
-mischief	-1.5	0.67082	[-2, -1, -1, -1, -1, -2, -3, -2, -1, -1]
-mischiefs	-0.8	1.72047	[-2, -1, -2, -2, 3, -1, -2, 2, -1, -2]
-miser	-1.8	0.87178	[-1, -2, 0, -3, -2, -2, -3, -2, -2, -1]
-miserable	-2.2	1.32665	[-2, -2, -3, -3, -4, -3, -1, -2, 1, -3]
-miserableness	-2.8	0.6	[-3, -3, -3, -3, -2, -2, -3, -4, -2, -3]
-miserably	-2.1	1.37477	[-2, -1, -3, -3, -4, -3, -1, -2, 1, -3]
-miserere	-0.8	1.07703	[-1, -1, 0, -3, 0, -1, 0, 1, -2, -1]
-misericorde	0.1	1.64012	[1, 1, -1, 2, 1, 2, -3, -1, -2, 1]
-misericordes	-0.5	1.36015	[0, 0, -1, 0, 0, 1, -3, 0, 1, -3]
-miseries	-2.7	0.78102	[-3, -4, -1, -2, -3, -3, -2, -3, -3, -3]
-miserliness	-2.6	1.0198	[-3, -1, -3, -2, -2, -1, -3, -4, -4, -3]
-miserly	-1.4	0.91652	[0, -2, -2, 0, -1, -2, -2, -1, -3, -1]
-misers	-1.5	0.92195	[0, -1, -1, -3, -1, -1, -2, -3, -2, -1]
-misery	-2.7	0.45826	[-2, -2, -3, -3, -2, -3, -3, -3, -3, -3]
-misgiving	-1.4	0.4899	[-2, -2, -2, -1, -1, -1, -2, -1, -1, -1]
-misinformation	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -3]
-misinformed	-1.6	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -2, -2]
-misinterpreted	-1.3	0.64031	[-1, -2, -1, 0, -2, -1, -1, -1, -2, -2]
-misleading	-1.7	0.64031	[-2, -1, -3, -1, -1, -2, -2, -2, -1, -2]
-misread	-1.1	0.3	[-1, -1, -1, -2, -1, -1, -1, -1, -1, -1]
-misreporting	-1.5	0.5	[-2, -1, -1, -1, -2, -1, -2, -2, -1, -2]
-misrepresentation	-2.0	0.63246	[-2, -3, -2, -1, -1, -3, -2, -2, -2, -2]
-miss	-0.6	1.35647	[-1, -1, -1, -1, -2, -1, 2, 2, -2, -1]
-missed	-1.2	0.74833	[-2, -1, 0, -1, -1, -1, -3, -1, -1, -1]
-misses	-0.9	0.3	[-1, -1, 0, -1, -1, -1, -1, -1, -1, -1]
-missing	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
-mistakable	-0.8	0.4	[-1, -1, -1, -1, -1, -1, -1, 0, 0, -1]
-mistake	-1.4	0.4899	[-1, -2, -1, -1, -1, -1, -2, -2, -2, -1]
-mistaken	-1.5	0.67082	[-2, -1, -2, -2, -1, -1, -1, -3, -1, -1]
-mistakenly	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -2, -1, -1]
-mistaker	-1.6	0.4899	[-2, -1, -2, -1, -2, -2, -1, -2, -1, -2]
-mistakers	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -1, -2, -2, -1]
-mistakes	-1.5	0.67082	[-2, -1, -2, -1, -3, -2, -1, -1, -1, -1]
-mistaking	-1.1	0.53852	[-1, -1, -1, -1, 0, -1, -1, -1, -2, -2]
-misunderstand	-1.5	0.67082	[-3, -2, -1, -1, -1, -1, -1, -2, -2, -1]
-misunderstanding	-1.8	0.6	[-1, -1, -1, -3, -2, -2, -2, -2, -2, -2]
-misunderstands	-1.3	0.45826	[-1, -2, -1, -2, -1, -1, -2, -1, -1, -1]
-misunderstood	-1.4	0.66332	[-1, -1, -1, -3, -1, -1, -2, -1, -2, -1]
-mlm	-1.4	1.68523	[0, -2, -2, -3, -4, -2, 0, 1, 1, -3]
-mmk	0.6	1.0198	[0, 0, 0, 0, 0, 3, 1, 0, 0, 2]
-moan	-0.6	1.62481	[-2, -1, 0, -3, 2, -2, 0, 0, -2, 2]
-moaned	-0.4	1.35647	[-2, 0, -3, 0, -1, -1, 2, 1, 0, 0]
-moaning	-0.4	1.28062	[-1, -1, 1, -1, 0, 0, 2, 0, -3, -1]
-moans	-0.6	0.8	[-2, 0, 0, -2, 0, -1, 0, 0, 0, -1]
-mock	-1.8	0.74833	[-3, -1, -1, -2, -2, -1, -3, -1, -2, -2]
-mocked	-1.3	1.26886	[-2, -2, -1, -2, -2, -3, -2, 1, 1, -1]
-mocker	-0.8	1.46969	[-1, -2, 2, -2, -2, -2, -2, 1, 1, -1]
-mockeries	-1.6	0.8	[-3, -1, -2, -2, -2, 0, -1, -2, -1, -2]
-mockers	-1.3	0.78102	[-2, -3, 0, -1, -1, -1, -2, -1, -1, -1]
-mockery	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -2, -1, -1]
-mocking	-1.7	0.64031	[-2, -1, -1, -2, -1, -1, -3, -2, -2, -2]
-mocks	-2.0	0.63246	[-1, -3, -2, -2, -2, -2, -2, -1, -3, -2]
-molest	-2.1	1.81384	[-4, -1, -2, -4, -3, 1, -3, 1, -2, -4]
-molestation	-1.9	1.57797	[-2, -2, -3, -2, -3, -2, -4, 1, 1, -3]
-molestations	-2.9	1.04403	[-3, -4, -4, -4, -3, -2, -2, -1, -2, -4]
-molested	-1.9	1.92094	[-4, 1, -1, -4, -2, -1, -4, -4, 1, -1]
-molester	-2.3	1.61555	[-4, -2, -1, -4, -2, -1, -4, -4, 1, -2]
-molesters	-2.2	1.66132	[-2, -4, -3, -3, -3, 1, 1, -3, -3, -3]
-molesting	-2.8	1.72047	[-4, -4, -4, -4, -3, -4, -1, -1, 1, -4]
-molests	-3.1	1.13578	[-3, -4, -4, -4, -3, -4, 0, -3, -3, -3]
-mongering	-0.8	1.16619	[-3, -2, 0, 0, -1, 1, -2, 0, -1, 0]
-monopolize	-0.8	1.6	[-1, -3, -2, -2, 0, -1, -1, -2, 2, 2]
-monopolized	-0.9	0.53852	[0, -2, -1, 0, -1, -1, -1, -1, -1, -1]
-monopolizes	-1.1	0.83066	[0, -3, -1, 0, -1, -1, -2, -1, -1, -1]
-monopolizing	-0.5	1.56525	[2, -1, -2, -1, -3, -1, -1, 2, 1, -1]
-mooch	-1.7	0.9	[-1, -1, -1, -3, -1, -3, -3, -2, -1, -1]
-mooched	-1.4	0.4899	[-2, -1, -2, -1, -1, -2, -1, -1, -2, -1]
-moocher	-1.5	0.67082	[-2, -1, -2, -1, -1, -2, -1, -1, -3, -1]
-moochers	-1.9	0.7	[-3, -2, -2, -3, -1, -1, -1, -2, -2, -2]
-mooches	-1.4	0.66332	[-2, -1, -2, -1, 0, -2, -1, -1, -2, -2]
-mooching	-1.7	0.64031	[-3, -2, -1, -1, -2, -2, -1, -2, -1, -2]
-moodier	-1.1	1.13578	[-2, -1, -1, -1, -2, -1, -2, 2, -1, -2]
-moodiest	-2.1	0.9434	[-1, -2, -2, -2, -1, -2, -4, -3, -1, -3]
-moodily	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -2, -1, -2, -1]
-moodiness	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -2, -1, -1, -2]
-moodinesses	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -1, -2, -2, -1]
-moody	-1.5	0.67082	[-1, -1, -1, -2, -2, -3, -1, -1, -1, -2]
-mope	-1.9	0.53852	[-2, -2, -1, -2, -2, -2, -2, -3, -1, -2]
-moping	-1.0	1.48324	[-2, -2, -1, -1, 1, 2, -3, -2, 0, -2]
-moron	-2.2	0.6	[-2, -1, -2, -3, -3, -2, -2, -3, -2, -2]
-moronic	-2.7	0.64031	[-3, -3, -3, -3, -2, -4, -2, -3, -2, -2]
-moronically	-1.4	1.8	[-4, -2, -1, 2, -2, -2, -3, -3, 0, 1]
-moronity	-1.1	1.22066	[-2, -1, -2, -1, 0, -2, 2, -2, -2, -1]
-morons	-1.3	1.1	[-1, -1, -1, 0, -3, -2, 0, 0, -2, -3]
-motherfucker	-3.6	0.66332	[-3, -4, -4, -4, -4, -2, -4, -3, -4, -4]
-motherfucking	-2.8	1.249	[-3, -1, -4, 0, -3, -3, -4, -4, -3, -3]
-motivate	1.6	0.4899	[1, 1, 1, 1, 2, 2, 2, 2, 2, 2]
-motivated	2.0	0.63246	[3, 3, 1, 2, 1, 2, 2, 2, 2, 2]
-motivating	2.2	0.6	[2, 2, 3, 3, 3, 2, 2, 2, 1, 2]
-motivation	1.4	0.66332	[1, 1, 2, 0, 2, 1, 2, 1, 2, 2]
-mourn	-1.8	0.6	[-2, -2, -2, -2, -2, -1, -2, -3, -1, -1]
-mourned	-1.3	1.55242	[-1, -2, -3, -3, -2, -1, 1, -2, 2, -2]
-mourner	-1.6	1.35647	[-3, 0, -2, -1, -1, 0, -2, 0, -3, -4]
-mourners	-1.8	0.74833	[-1, -2, -3, -1, -2, -1, -2, -1, -2, -3]
-mournful	-1.6	1.62481	[-2, -3, -3, 2, -2, -3, -2, 1, -2, -2]
-mournfuller	-1.9	0.9434	[-2, -3, -3, -3, 0, -2, -1, -2, -2, -1]
-mournfully	-1.7	1.55242	[-4, -3, -2, -3, 1, -2, -2, -2, 1, -1]
-mournfulness	-1.8	1.4	[-4, -3, 1, -3, -1, -2, 0, -2, -2, -2]
-mourning	-1.9	1.04403	[-1, -1, -1, -1, -2, -3, -4, -3, -2, -1]
-mourningly	-2.3	1.18743	[-3, -3, -3, -3, -2, -3, -2, 1, -2, -3]
-mourns	-2.4	0.66332	[-2, -2, -3, -2, -3, -3, -3, -1, -2, -3]
-muah	2.3	1.26886	[0, 3, 1, 2, 3, 1, 4, 4, 3, 2]
-mumpish	-1.4	0.66332	[-1, -1, -2, -2, 0, -1, -2, -2, -1, -2]
-murder	-3.7	0.64031	[-4, -4, -4, -4, -2, -4, -4, -4, -3, -4]
-murdered	-3.4	0.66332	[-4, -3, -2, -3, -4, -4, -3, -3, -4, -4]
-murderee	-3.2	0.6	[-3, -3, -2, -3, -4, -4, -3, -3, -4, -3]
-murderees	-3.1	0.7	[-2, -4, -3, -4, -3, -2, -3, -3, -4, -3]
-murderer	-3.6	0.4899	[-4, -3, -3, -3, -4, -4, -4, -3, -4, -4]
-murderers	-3.3	0.78102	[-3, -4, -4, -4, -4, -2, -4, -3, -3, -2]
-murderess	-2.2	1.72047	[-2, -2, -3, -4, -3, -3, -4, 1, 1, -3]
-murderesses	-2.6	0.8	[-2, -4, -3, -4, -2, -2, -2, -2, -3, -2]
-murdering	-3.3	0.78102	[-4, -2, -4, -3, -4, -3, -2, -4, -4, -3]
-murderous	-3.2	0.74833	[-3, -3, -4, -3, -4, -4, -4, -2, -2, -3]
-murderously	-3.1	0.9434	[-3, -4, -4, -4, -3, -4, -1, -2, -3, -3]
-murderousness	-2.9	0.7	[-3, -3, -4, -2, -2, -2, -4, -3, -3, -3]
-murders	-3.0	1.84391	[-4, -4, -4, 2, -4, -2, -4, -4, -2, -4]
-n00b	-1.6	0.8	[-1, -3, -1, -2, -2, -2, -2, -2, -1, 0]
-nag	-1.5	0.80623	[-1, -1, -3, -1, -3, -2, -1, -1, -1, -1]
-nagana	-1.7	0.9	[-2, -2, 0, 0, -2, -3, -2, -2, -2, -2]
-nagged	-1.7	0.45826	[-2, -1, -2, -1, -2, -2, -1, -2, -2, -2]
-nagger	-1.8	0.4	[-2, -1, -2, -2, -2, -2, -1, -2, -2, -2]
-naggers	-1.5	0.67082	[-1, -1, -2, -2, -2, -1, -1, -3, -1, -1]
-naggier	-1.4	1.11355	[-2, -3, -2, -2, 1, -1, -2, -1, 0, -2]
-naggiest	-2.4	0.91652	[-3, -2, -2, -1, -4, -2, -3, -3, -3, -1]
-nagging	-1.7	0.64031	[-1, -1, -1, -1, -2, -2, -2, -2, -3, -2]
-naggingly	-0.9	1.37477	[-2, 2, -1, -1, -1, -3, 1, -1, -1, -2]
-naggy	-1.7	0.64031	[-2, -2, -1, -1, -3, -2, -1, -2, -1, -2]
-nags	-1.1	0.53852	[-1, -1, -2, -1, -1, -2, -1, -1, 0, -1]
-nah	-0.4	1.28062	[0, 0, 1, -1, -3, -1, 0, 2, -1, -1]
-naive	-1.1	1.22066	[-2, -2, -1, 2, -1, -1, -1, -3, -1, -1]
-nastic	0.2	0.6	[2, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-nastier	-2.3	0.45826	[-2, -2, -2, -3, -3, -2, -3, -2, -2, -2]
-nasties	-2.1	0.3	[-2, -2, -2, -2, -3, -2, -2, -2, -2, -2]
-nastiest	-2.4	1.85472	[-4, -4, -4, -2, -3, -2, 1, 1, -3, -4]
-nastily	-1.9	0.7	[-2, -3, -1, -2, -2, -3, -1, -1, -2, -2]
-nastiness	-1.1	1.44568	[-2, -2, -3, -2, 1, -1, -1, -1, 2, -2]
-nastinesses	-2.6	0.66332	[-2, -3, -3, -2, -3, -3, -3, -1, -3, -3]
-nasturtium	0.4	0.66332	[0, 0, 0, 0, 0, 1, 1, 0, 2, 0]
-nasturtiums	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
-nasty	-2.6	1.0198	[-3, -1, -2, -4, -3, -3, -1, -2, -4, -3]
-natural	1.5	1.0247	[2, 0, 0, 1, 1, 3, 2, 2, 3, 1]
-neat	2.0	0.89443	[2, 1, 1, 2, 3, 1, 2, 2, 2, 4]
-neaten	1.2	0.4	[1, 1, 1, 1, 1, 2, 2, 1, 1, 1]
-neatened	2.0	1.09545	[0, 2, 1, 3, 1, 2, 4, 3, 2, 2]
-neatening	1.3	0.45826	[1, 1, 1, 1, 2, 2, 2, 1, 1, 1]
-neatens	1.1	0.83066	[0, 1, 0, 1, 1, 1, 1, 3, 2, 1]
-neater	1.0	0.44721	[1, 1, 1, 1, 1, 1, 2, 0, 1, 1]
-neatest	1.7	0.64031	[1, 2, 2, 1, 2, 2, 1, 2, 1, 3]
-neath	0.2	0.9798	[0, 0, -2, 0, 0, 2, 0, 1, 1, 0]
-neatherd	-0.4	0.8	[0, 0, 0, -2, 0, -1, 1, -1, -1, 0]
-neatly	1.4	0.66332	[2, 1, 1, 2, 2, 2, 0, 1, 1, 2]
-neatness	1.3	0.64031	[2, 1, 1, 0, 1, 1, 2, 2, 2, 1]
-neats	1.1	0.53852	[2, 1, 2, 1, 0, 1, 1, 1, 1, 1]
-needy	-1.4	0.4899	[-1, -2, -2, -2, -1, -1, -1, -1, -2, -1]
-negative	-2.7	0.9	[-1, -3, -3, -2, -4, -2, -2, -4, -3, -3]
-negativity	-2.3	0.45826	[-2, -2, -2, -2, -3, -2, -3, -3, -2, -2]
-neglect	-2.0	0.63246	[-2, -2, -1, -1, -3, -2, -3, -2, -2, -2]
-neglected	-2.4	1.0198	[-1, -2, -4, -3, -2, -2, -1, -4, -3, -2]
-neglecter	-1.7	0.64031	[-2, -2, -1, -1, -1, -3, -2, -2, -1, -2]
-neglecters	-1.5	0.67082	[-2, -1, -1, -1, -2, -1, -1, -2, -3, -1]
-neglectful	-2.0	0.63246	[-3, -3, -1, -2, -2, -2, -1, -2, -2, -2]
-neglectfully	-2.1	0.9434	[-1, -3, -3, -1, -1, -2, -2, -2, -4, -2]
-neglectfulness	-2.0	0.63246	[-2, -2, -2, -2, -1, -3, -2, -2, -1, -3]
-neglecting	-1.7	0.78102	[-2, -1, -3, -2, -1, -3, -1, -1, -2, -1]
-neglects	-2.2	0.4	[-2, -2, -2, -2, -2, -3, -2, -3, -2, -2]
-nerd	-1.2	0.6	[-1, -2, -1, -2, -1, 0, -1, -1, -2, -1]
-nerdier	-0.2	0.87178	[0, 0, -1, -1, 0, -1, 2, 0, 0, -1]
-nerdiest	0.6	1.28062	[2, 3, 0, -1, 1, 0, 0, -1, 2, 0]
-nerdish	-0.1	1.04403	[-1, -1, 2, 0, -1, -1, 1, 0, 1, -1]
-nerdy	-0.2	1.249	[-1, -1, -1, 3, 0, 0, 0, 0, -2, 0]
-nerves	-0.4	0.8	[0, -1, 0, 1, -2, -1, 0, -1, 0, 0]
-nervous	-1.1	0.53852	[-1, -1, -1, -2, -2, -1, -1, 0, -1, -1]
-nervously	-0.6	1.56205	[-1, -1, -1, -1, -1, -2, 4, -1, -1, -1]
-nervousness	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-neurotic	-1.4	1.11355	[-3, -2, -2, -1, 1, -2, -2, -1, 0, -2]
-neurotically	-1.8	1.16619	[0, -2, -1, -3, -3, -1, 0, -2, -3, -3]
-neuroticism	-0.9	1.22066	[-2, -1, -1, -1, -2, 0, -3, 1, 1, -1]
-neurotics	-0.7	1.61555	[-2, 0, -1, -2, -1, -3, 0, 2, 2, -2]
-nice	1.8	0.74833	[3, 1, 1, 2, 2, 1, 3, 1, 2, 2]
-nicely	1.9	0.83066	[2, 1, 2, 2, 4, 2, 1, 1, 2, 2]
-niceness	1.6	0.66332	[1, 1, 3, 2, 1, 1, 2, 2, 2, 1]
-nicenesses	2.1	1.22066	[4, 0, 3, 1, 2, 1, 4, 2, 2, 2]
-nicer	1.9	0.53852	[2, 2, 1, 2, 3, 2, 2, 2, 1, 2]
-nicest	2.2	0.87178	[1, 4, 1, 2, 2, 2, 3, 3, 2, 2]
-niceties	1.5	1.20416	[1, 4, 1, 1, 2, 1, 0, 3, 2, 0]
-nicety	1.2	1.07703	[1, 0, 4, 1, 1, 0, 2, 1, 1, 1]
-nifty	1.7	0.64031	[2, 2, 1, 1, 1, 2, 3, 2, 2, 1]
-niggas	-1.4	2.2	[-4, -3, 2, 1, -4, -2, 0, -1, 1, -4]
-nigger	-3.3	1.18743	[-4, -4, -4, -4, -4, -4, -1, -3, -1, -4]
-no	-1.2	0.74833	[-1, -1, -1, -1, -1, -1, 0, -1, -2, -3]
-noble	2.0	0.89443	[2, 1, 2, 2, 3, 0, 2, 3, 2, 3]
-noisy	-0.7	0.64031	[-2, 0, -1, -1, 0, -1, -1, 0, 0, -1]
-nonsense	-1.7	0.64031	[-3, -1, -1, -1, -2, -1, -2, -2, -2, -2]
-noob	-0.2	1.16619	[-2, 0, -1, 0, -1, 2, 1, 1, -1, -1]
-nosey	-0.8	1.16619	[-2, -2, -2, 1, -1, -1, 0, 1, 0, -2]
-notorious	-1.9	1.3	[-2, -4, -3, -2, -2, -2, -1, -1, -3, 1]
-novel	1.3	0.64031	[2, 0, 1, 1, 1, 1, 2, 2, 2, 1]
-numb	-1.4	0.66332	[-1, -1, -1, -1, -2, -1, -1, -3, -2, -1]
-numbat	0.2	0.4	[0, 0, 0, 0, 1, 1, 0, 0, 0, 0]
-numbed	-0.9	0.53852	[-1, -1, -1, -1, 0, 0, -2, -1, -1, -1]
-number	0.3	0.64031	[0, 0, 1, 0, 0, 2, 0, 0, 0, 0]
-numberable	0.6	0.91652	[0, 2, 0, 0, 0, 2, 2, 0, 0, 0]
-numbest	-1.0	0.89443	[-2, -1, 0, 0, -3, -1, -1, -1, 0, -1]
-numbfish	-0.4	0.66332	[-1, 0, 0, 0, -2, 0, 0, -1, 0, 0]
-numbfishes	-0.7	0.9	[0, -1, 0, -1, -1, 0, -1, 0, 0, -3]
-numbing	-1.1	0.83066	[-1, 0, -1, -1, -2, -1, -3, -1, 0, -1]
-numbingly	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -2, -1, -2, -1]
-numbles	0.4	0.66332	[0, 0, 0, 0, 1, 2, 0, 0, 1, 0]
-numbly	-1.4	1.0198	[-3, -2, 0, -1, -1, -3, -1, -2, -1, 0]
-numbness	-1.1	0.7	[-1, -1, -2, -1, -1, -2, -1, 0, -2, 0]
-numbs	-0.7	1.00499	[-1, 0, -1, 0, 1, 0, -3, -1, -1, -1]
-numbskull	-2.3	1.41774	[-2, -4, -3, 0, -2, -2, -4, -4, 0, -2]
-numbskulls	-2.2	1.07703	[-2, -2, -4, -2, -2, -1, -3, -3, 0, -3]
-nurtural	1.5	0.80623	[2, 1, 2, 2, 1, 3, 0, 1, 2, 1]
-nurturance	1.6	0.8	[1, 2, 1, 1, 3, 0, 2, 2, 2, 2]
-nurturances	1.3	1.55242	[0, -2, 3, 1, 1, 2, 3, 0, 2, 3]
-nurturant	1.7	0.78102	[2, 1, 3, 2, 2, 2, 2, 1, 0, 2]
-nurture	1.4	0.8	[3, 1, 2, 2, 1, 2, 1, 0, 1, 1]
-nurtured	1.9	0.9434	[2, 1, 3, 3, 3, 1, 2, 2, 0, 2]
-nurturer	1.9	0.83066	[2, 1, 3, 3, 3, 1, 2, 2, 1, 1]
-nurturers	0.8	1.66132	[2, -1, 2, 2, 1, -2, -2, 2, 2, 2]
-nurtures	1.9	0.83066	[2, 1, 3, 3, 3, 1, 2, 2, 1, 1]
-nurturing	2.0	0.63246	[3, 3, 2, 2, 1, 2, 2, 1, 2, 2]
-nuts	-1.3	1.26886	[-2, -1, -2, -3, 1, -1, 1, -2, -2, -2]
-o.o	-0.8	1.07703	[-1, -1, 0, -2, -1, -1, -2, 1, -2, 1]
-o/\o	2.1	1.04403	[1, 2, 3, 1, 3, 4, 1, 2, 3, 1]
-o_0	-0.1	0.53852	[-1, -1, 0, 0, 0, 0, 0, 0, 1, 0]
-obliterate	-2.9	0.83066	[-3, -4, -3, -3, -3, -3, -2, -1, -4, -3]
-obliterated	-2.1	1.3	[-3, 0, -1, -4, -3, -2, 0, -2, -3, -3]
-obnoxious	-2.0	0.44721	[-1, -2, -3, -2, -2, -2, -2, -2, -2, -2]
-obnoxiously	-2.3	0.64031	[-3, -2, -1, -2, -2, -3, -2, -3, -3, -2]
-obnoxiousness	-2.1	0.7	[-3, -1, -1, -2, -2, -3, -2, -2, -3, -2]
-obscene	-2.8	0.87178	[-3, -3, -2, -1, -3, -4, -3, -4, -2, -3]
-obsess	-1.0	0.89443	[-2, 0, -2, -1, 1, -1, -2, -1, -1, -1]
-obsessed	-0.7	0.78102	[0, 0, -1, 0, -1, 0, -1, -2, -2, 0]
-obsesses	-1.0	0.7746	[-2, -2, -1, -2, 0, -1, -1, -1, 0, 0]
-obsessing	-1.4	0.66332	[-1, -1, -1, -2, -1, -1, -1, -3, -2, -1]
-obsession	-1.4	0.8	[0, -2, -2, -1, -1, -1, -3, -1, -1, -2]
-obsessional	-1.5	0.92195	[0, -2, -1, -1, -3, -1, -2, -1, -3, -1]
-obsessionally	-1.3	0.9	[-1, -2, -2, -2, -2, -1, 1, -1, -1, -2]
-obsessions	-0.9	1.44568	[-1, -4, -2, -1, 1, -1, 0, 1, 0, -2]
-obsessive	-0.9	1.04403	[-2, 0, -1, 0, 1, -1, -3, -1, -1, -1]
-obsessively	-0.4	1.2	[-1, -1, -1, -1, -1, 1, 2, -2, 1, -1]
-obsessiveness	-1.2	1.32665	[0, -3, -1, -1, -1, 1, -4, -1, -1, -1]
-obsessives	-0.7	0.9	[-1, -1, -1, -1, -1, 1, -2, 1, -1, -1]
-obsolete	-1.2	0.74833	[-1, -1, -1, -1, -2, -1, -1, -3, -1, 0]
-obstacle	-1.5	1.0247	[-1, -3, -1, -2, -2, -2, 1, -1, -2, -2]
-obstacles	-1.6	0.8	[-3, -1, -2, -1, -2, -2, 0, -2, -1, -2]
-obstinate	-1.2	0.74833	[-2, -1, -1, -1, 0, 0, -2, -1, -2, -2]
-odd	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -2, -1, -2, -1]
-offence	-1.2	1.93907	[-2, -2, -3, 3, -2, -2, -3, 2, -1, -2]
-offences	-1.4	1.49666	[-2, -2, -4, -1, -2, -2, -1, 0, 2, -2]
-offend	-1.2	1.4	[-2, -2, -2, -2, -1, -2, -2, 1, 2, -2]
-offended	-1.0	1.41421	[-2, -2, -2, -2, -1, 0, -2, 2, 1, -2]
-offender	-1.5	1.28452	[-3, -2, -2, -2, -2, -2, -2, 1, 1, -2]
-offenders	-1.5	1.28452	[-2, -1, -2, -2, -2, -2, 2, -3, -2, -1]
-offending	-2.3	0.64031	[-2, -2, -3, -2, -2, -4, -2, -2, -2, -2]
-offends	-2.0	0.7746	[-3, -1, -1, -2, -2, -2, -3, -1, -2, -3]
-offense	-1.0	1.61245	[-2, 1, -1, -2, -2, -2, -3, 2, 1, -2]
-offenseless	0.7	1.79165	[3, 1, 0, 2, 1, 2, 1, 0, -4, 1]
-offenses	-1.5	1.5	[-1, -2, -2, -4, -1, -2, 1, -3, 1, -2]
-offensive	-2.0	1.48324	[-3, -3, -3, -2, -1, -2, 2, -2, -3, -3]
-offensively	-2.8	0.87178	[-2, -4, -3, -3, -2, -4, -4, -2, -2, -2]
-offensiveness	-2.3	0.45826	[-2, -2, -2, -2, -2, -3, -2, -3, -3, -2]
-offensives	-0.8	1.249	[0, 0, -1, -2, 0, 2, -2, -1, -2, -2]
-offline	-0.5	0.92195	[0, 0, 0, 0, -3, 0, -1, 0, -1, 0]
-ok	1.2	0.4	[1, 2, 1, 1, 1, 1, 2, 1, 1, 1]
-okay	0.9	0.53852	[1, 1, 0, 0, 1, 1, 1, 2, 1, 1]
-okays	2.1	1.13578	[1, 1, 1, 4, 3, 2, 2, 1, 2, 4]
-ominous	-1.4	1.49666	[-3, -2, -1, -2, -2, -1, -1, 1, 1, -4]
-once-in-a-lifetime	1.8	1.4	[4, 2, 1, 0, 1, 1, 4, 3, 2, 0]
-openness	1.4	0.8	[2, 1, 1, 2, 2, 1, 1, 1, 3, 0]
-opportune	1.7	0.78102	[2, 2, 0, 1, 2, 3, 2, 2, 1, 2]
-opportunely	1.5	1.0247	[1, 1, 4, 1, 2, 1, 1, 2, 2, 0]
-opportuneness	1.2	1.249	[0, 1, 2, 2, 2, 2, 2, 2, -2, 1]
-opportunism	0.4	1.11355	[-1, -1, 0, -1, 1, 2, 0, 1, 2, 1]
-opportunisms	0.2	1.4	[2, -1, 0, -1, 1, -2, 2, 2, -1, 0]
-opportunist	0.2	0.9798	[-1, -1, 0, -1, 0, 2, 0, 1, 1, 1]
-opportunistic	-0.1	2.11896	[-2, 1, -1, 0, -4, 2, -1, 4, 1, -1]
-opportunistically	0.9	1.51327	[1, -3, 1, 3, 2, 2, 1, 0, 1, 1]
-opportunists	0.3	1.34536	[0, -1, -1, 2, 1, 3, -1, -1, 1, 0]
-opportunities	1.6	0.4899	[1, 1, 2, 2, 2, 1, 2, 2, 1, 2]
-opportunity	1.8	0.6	[2, 2, 2, 2, 3, 1, 2, 1, 1, 2]
-oppressed	-2.1	0.53852	[-2, -2, -2, -1, -2, -2, -3, -2, -2, -3]
-oppressive	-1.7	1.34536	[-3, -2, -1, -2, -2, -2, -3, 2, -2, -2]
-optimal	1.5	0.67082	[1, 2, 1, 3, 1, 1, 1, 2, 2, 1]
-optimality	1.9	0.7	[3, 3, 2, 1, 2, 1, 2, 2, 1, 2]
-optimally	1.3	0.9	[0, 3, 0, 1, 1, 2, 1, 1, 2, 2]
-optimisation	1.6	0.8	[3, 1, 1, 1, 2, 1, 1, 3, 2, 1]
-optimisations	1.8	0.6	[3, 1, 1, 2, 1, 2, 2, 2, 2, 2]
-optimise	1.9	0.83066	[1, 2, 3, 2, 3, 3, 2, 1, 1, 1]
-optimised	1.7	1.26886	[2, 4, 1, 2, 1, 2, 3, 2, 1, -1]
-optimises	1.6	1.0198	[3, 1, 1, 1, 1, 3, 2, 0, 3, 1]
-optimising	1.7	1.00499	[1, 2, 3, 3, 1, 2, 1, 3, 0, 1]
-optimism	2.5	0.67082	[2, 2, 3, 3, 3, 4, 2, 2, 2, 2]
-optimisms	2.0	0.63246	[2, 3, 1, 3, 1, 2, 2, 2, 2, 2]
-optimist	2.4	0.4899	[3, 2, 3, 2, 3, 3, 2, 2, 2, 2]
-optimistic	1.3	1.48661	[2, 2, -3, 2, 2, 2, 1, 2, 1, 2]
-optimistically	2.1	0.53852	[3, 2, 2, 2, 3, 2, 1, 2, 2, 2]
-optimists	1.6	0.66332	[3, 2, 2, 1, 2, 1, 2, 1, 1, 1]
-optimization	1.6	0.8	[2, 3, 1, 1, 1, 2, 0, 2, 2, 2]
-optimizations	0.9	1.04403	[0, 2, 0, 2, 1, 0, 3, 1, 0, 0]
-optimize	2.2	0.87178	[2, 3, 3, 2, 1, 2, 4, 2, 2, 1]
-optimized	2.0	0.44721	[1, 3, 2, 2, 2, 2, 2, 2, 2, 2]
-optimizer	1.5	0.67082	[1, 3, 1, 1, 2, 2, 1, 2, 1, 1]
-optimizers	2.1	0.7	[3, 3, 1, 3, 2, 2, 1, 2, 2, 2]
-optimizes	1.8	0.6	[1, 3, 2, 1, 2, 2, 1, 2, 2, 2]
-optimizing	2.0	0.7746	[1, 1, 2, 2, 1, 3, 3, 3, 2, 2]
-optionless	-1.7	0.64031	[-2, -1, -2, -3, -1, -2, -2, -2, -1, -1]
-original	1.3	0.9	[0, 2, 0, 2, 2, 0, 2, 1, 2, 2]
-outcry	-2.3	0.64031	[-3, -2, -2, -3, -2, -1, -3, -2, -2, -3]
-outgoing	1.2	1.16619	[1, 1, 1, 2, -1, 1, 3, 3, 0, 1]
-outmaneuvered	0.5	1.36015	[-2, 2, 0, 0, 3, 1, 1, 0, 1, -1]
-outrage	-2.3	1.00499	[-2, -2, -4, -3, -1, -3, -3, -1, -1, -3]
-outraged	-2.5	0.92195	[-3, -2, -2, -1, -3, -3, -1, -4, -3, -3]
-outrageous	-2.0	1.34164	[-3, 0, -2, -1, -3, 0, -3, -3, -4, -1]
-outrageously	-1.2	1.32665	[-1, -1, -3, -3, -2, -1, 2, -1, -1, -1]
-outrageousness	-1.2	1.249	[-2, 0, 1, -2, -1, -1, -3, 0, -1, -3]
-outrageousnesses	-1.3	1.67631	[-1, -3, -2, 1, 0, 1, 0, -3, -2, -4]
-outrages	-2.3	1.00499	[-3, -2, -2, -1, -3, -3, -1, -4, -1, -3]
-outraging	-2.0	1.18322	[-4, -1, -2, -3, -1, 0, -1, -3, -3, -2]
-outreach	1.1	0.7	[2, 1, 0, 0, 2, 1, 1, 1, 2, 1]
-outstanding	3.0	0.89443	[3, 1, 3, 3, 4, 4, 2, 3, 4, 3]
-overjoyed	2.7	0.78102	[4, 3, 3, 4, 2, 2, 2, 2, 3, 2]
-overload	-1.5	0.67082	[-2, 0, -1, -2, -2, -1, -1, -2, -2, -2]
-overlooked	-0.1	1.44568	[-1, -2, -1, -1, 2, 0, -1, 2, -1, 2]
-overreact	-1.0	1.73205	[-2, -2, -2, -2, 0, -3, 1, 3, -1, -2]
-overreacted	-1.7	0.64031	[-2, -2, -2, -1, -1, -1, -1, -3, -2, -2]
-overreaction	-0.7	1.34536	[-2, -1, 0, -1, -1, 3, -2, -1, -1, -1]
-overreacts	-2.2	0.87178	[-2, -2, -2, -3, -4, -1, -3, -1, -2, -2]
-oversell	-0.9	0.7	[0, -1, -1, 0, -2, -1, -1, -1, -2, 0]
-overselling	-0.8	1.16619	[0, -1, 0, -1, -2, -1, -1, -2, -2, 2]
-oversells	0.3	1.26886	[-1, -1, 0, 0, 2, 2, 2, -1, 1, -1]
-oversimplification	0.2	1.53623	[-1, 1, -1, -1, 1, -1, -2, 1, 2, 3]
-oversimplifies	0.1	1.37477	[3, 0, 0, -1, 1, -1, 2, -1, -1, -1]
-oversimplify	-0.6	1.35647	[-3, -1, 0, -2, 0, 1, 2, -1, -1, -1]
-overstatement	-1.1	0.7	[-2, 0, -1, -2, -1, 0, -1, -1, -2, -1]
-overstatements	-0.7	1.34536	[-1, -1, -3, -1, 2, 0, -1, -1, -2, 1]
-overweight	-1.5	0.67082	[-3, -2, -1, -1, -1, -2, -1, -2, -1, -1]
-overwhelm	-0.7	1.26886	[-1, 2, -1, -1, -2, -2, 1, 0, -1, -2]
-overwhelmed	0.2	1.53623	[-2, -1, 2, -2, 2, 1, -1, 2, 1, 0]
-overwhelmingly	-0.5	1.28452	[0, -2, -1, 0, -2, -1, -2, 0, 1, 2]
-overwhelms	-0.8	1.249	[-2, -2, -1, -1, -1, -2, 2, 1, -1, -1]
-oxymoron	-0.5	0.80623	[0, 0, -1, -1, -1, -2, 1, 0, 0, -1]
-pain	-2.3	0.64031	[-2, -3, -2, -2, -2, -2, -2, -2, -2, -4]
-pained	-1.8	0.6	[-1, -2, -3, -2, -2, -2, -2, -1, -1, -2]
-painful	-1.9	0.9434	[-2, -1, -1, -3, -4, -1, -1, -2, -2, -2]
-painfuller	-1.7	1.34536	[-2, -2, -2, 2, -1, -3, -2, -2, -3, -2]
-painfully	-2.4	0.4899	[-2, -3, -2, -3, -3, -2, -2, -2, -2, -3]
-painfulness	-2.7	0.64031	[-3, -4, -3, -2, -3, -3, -3, -2, -2, -2]
-paining	-1.7	0.45826	[-1, -2, -2, -2, -2, -2, -1, -2, -1, -2]
-painless	1.2	0.87178	[1, 2, -1, 1, 2, 1, 2, 1, 2, 1]
-painlessly	1.1	0.3	[1, 1, 1, 1, 1, 1, 1, 1, 1, 2]
-painlessness	0.4	1.0198	[1, 1, 1, 1, -1, 1, -2, 0, 1, 1]
-pains	-1.8	0.6	[-2, -2, -1, -1, -1, -2, -2, -2, -3, -2]
-palatable	1.6	0.8	[2, 1, 2, 1, 2, 1, 3, 0, 2, 2]
-palatableness	0.8	0.87178	[2, 1, 1, 0, -1, 2, 0, 1, 1, 1]
-palatably	1.1	0.83066	[2, 1, 2, 1, 1, 1, 2, -1, 1, 1]
-panic	-2.3	0.64031	[-3, -2, -1, -2, -2, -2, -3, -3, -2, -3]
-panicked	-2.0	1.61245	[-2, -4, -3, -3, -3, 1, -2, -2, 1, -3]
-panicking	-1.9	0.53852	[-2, -2, -3, -2, -2, -2, -2, -2, -1, -1]
-panicky	-1.5	0.67082	[-2, -2, -1, -1, -1, -1, -1, -2, -3, -1]
-panicle	0.5	0.67082	[2, 0, 0, 0, 0, 0, 0, 1, 1, 1]
-panicled	0.1	0.83066	[2, 0, 0, 0, 0, -1, 0, -1, 1, 0]
-panicles	-0.2	0.6	[1, 0, 0, 0, 0, -1, 0, -1, -1, 0]
-panics	-1.9	1.3	[-2, -3, -2, -3, -1, -2, 1, -4, -1, -2]
-paniculate	0.1	0.3	[0, 0, 0, 1, 0, 0, 0, 0, 0, 0]
-panicums	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
-paradise	3.2	0.9798	[4, 1, 4, 2, 4, 4, 3, 3, 3, 4]
-paradox	-0.4	0.66332	[-1, -1, 0, 0, -1, 0, -1, 0, 1, -1]
-paranoia	-1.0	1.48324	[1, -2, -2, -3, -1, 0, -2, -1, -2, 2]
-paranoiac	-1.3	1.61555	[-2, -3, -2, -2, 1, -3, 2, -2, 0, -2]
-paranoiacs	-0.7	1.18743	[-1, 0, -1, -1, -3, 1, -2, 0, 1, -1]
-paranoias	-1.5	1.0247	[-2, -3, -2, 0, -1, -3, 0, -1, -1, -2]
-paranoid	-1.0	1.41421	[0, -3, -3, -2, -1, -1, 0, 1, -2, 1]
-paranoids	-1.6	0.91652	[-2, -1, -1, -2, -2, -1, -1, -1, -4, -1]
-pardon	1.3	0.45826	[1, 2, 1, 2, 1, 2, 1, 1, 1, 1]
-pardoned	0.9	0.9434	[1, 1, 1, 1, 1, 1, 1, 0, 3, -1]
-pardoning	1.7	0.78102	[3, 2, 2, 2, 1, 1, 2, 2, 0, 2]
-pardons	1.2	0.6	[2, 1, 1, 1, 1, 2, 1, 2, 0, 1]
-parley	-0.4	0.66332	[0, -2, 0, 0, -1, -1, 0, 0, 0, 0]
-partied	1.4	1.11355	[2, 3, 1, 1, 1, 2, 3, -1, 1, 1]
-partier	1.4	0.8	[2, 2, 1, 1, 0, 2, 3, 1, 1, 1]
-partiers	0.7	1.00499	[0, 0, 3, 0, 0, 0, 2, 1, 0, 1]
-parties	1.7	0.78102	[2, 3, 1, 1, 1, 2, 3, 1, 2, 1]
-party	1.7	0.78102	[3, 2, 2, 1, 3, 2, 1, 1, 1, 1]
-partyer	1.2	1.07703	[1, 3, 1, 0, 1, 0, 2, 1, 3, 0]
-partyers	1.1	0.83066	[1, 2, 0, 3, 1, 1, 1, 0, 1, 1]
-partying	1.6	1.11355	[0, 3, 1, 0, 3, 2, 3, 1, 2, 1]
-passion	2.0	0.44721	[2, 2, 1, 3, 2, 2, 2, 2, 2, 2]
-passional	1.6	0.8	[2, 1, 3, 0, 2, 1, 1, 2, 2, 2]
-passionate	2.4	1.35647	[0, 4, 3, 3, 4, 2, 0, 2, 3, 3]
-passionately	2.4	0.91652	[3, 0, 3, 3, 2, 3, 2, 3, 2, 3]
-passionateness	2.3	0.64031	[1, 3, 2, 3, 2, 3, 2, 3, 2, 2]
-passionflower	0.3	0.45826	[0, 0, 0, 0, 1, 0, 1, 1, 0, 0]
-passionflowers	0.4	0.66332	[0, 0, 0, 0, 2, 1, 1, 0, 0, 0]
-passionless	-1.9	0.7	[-3, -2, -2, -2, -1, -1, -1, -3, -2, -2]
-passions	2.2	0.6	[3, 3, 3, 2, 2, 1, 2, 2, 2, 2]
-passive	0.8	1.46969	[4, 1, 1, 0, -2, 0, 1, 1, 2, 0]
-passively	-0.7	0.64031	[0, -1, 0, 0, -1, -2, 0, -1, -1, -1]
-pathetic	-2.7	1.48661	[-3, -4, -3, -4, -2, 1, -2, -2, -4, -4]
-pathetical	-1.2	1.249	[-2, -1, -2, -1, -2, 1, -3, 1, -1, -2]
-pathetically	-1.8	1.72047	[-3, -4, -2, 0, -3, -2, -3, -3, 1, 1]
-pay	-0.4	0.91652	[0, 0, -3, 0, 0, 0, 0, 0, -1, 0]
-peace	2.5	1.0247	[3, 2, 1, 4, 2, 3, 4, 1, 3, 2]
-peaceable	1.7	0.45826	[2, 2, 1, 2, 1, 2, 2, 1, 2, 2]
-peaceableness	1.8	1.16619	[2, 2, 4, 2, 2, 2, 2, 1, 2, -1]
-peaceably	2.0	0.63246	[2, 3, 2, 2, 1, 2, 3, 1, 2, 2]
-peaceful	2.2	0.74833	[4, 2, 1, 2, 2, 2, 3, 2, 2, 2]
-peacefuller	1.9	0.7	[2, 2, 2, 1, 3, 3, 2, 2, 1, 1]
-peacefullest	3.1	0.7	[3, 3, 2, 3, 4, 2, 4, 3, 4, 3]
-peacefully	2.4	0.66332	[3, 2, 2, 2, 4, 2, 2, 3, 2, 2]
-peacefulness	2.1	0.83066	[3, 2, 1, 2, 3, 1, 3, 3, 1, 2]
-peacekeeper	1.6	1.11355	[1, 1, 0, 2, 1, 1, 4, 3, 2, 1]
-peacekeepers	1.6	1.11355	[4, 1, 1, 2, 1, 1, 2, 3, 0, 1]
-peacekeeping	2.0	0.63246	[2, 1, 1, 2, 3, 3, 2, 2, 2, 2]
-peacekeepings	1.6	0.8	[0, 1, 1, 2, 2, 3, 2, 2, 2, 1]
-peacemaker	2.0	0.89443	[2, 1, 2, 4, 2, 2, 1, 3, 1, 2]
-peacemakers	2.4	1.0198	[0, 3, 4, 2, 3, 2, 3, 3, 2, 2]
-peacemaking	1.7	0.78102	[1, 1, 1, 3, 3, 1, 2, 2, 2, 1]
-peacenik	0.8	0.87178	[1, 1, 0, 1, 2, 0, 1, 1, -1, 2]
-peaceniks	0.7	1.00499	[2, 0, 0, 1, 0, 2, 1, -1, 2, 0]
-peaces	2.1	0.83066	[2, 2, 2, 2, 3, 0, 3, 3, 2, 2]
-peacetime	2.2	1.16619	[3, 1, 4, 2, 4, 3, 1, 1, 2, 1]
-peacetimes	2.1	0.83066	[3, 2, 2, 4, 1, 2, 2, 2, 1, 2]
-peculiar	0.6	1.2	[-1, 0, -1, 1, 2, -1, 2, 1, 2, 1]
-peculiarities	0.1	1.37477	[-1, -1, 0, -1, -1, 1, 3, 2, -1, 0]
-peculiarity	0.6	1.2	[-1, 1, -1, 0, 2, -1, 1, 2, 2, 1]
-peculiarly	-0.4	1.2	[-1, 2, -2, -1, 0, 0, -2, 1, -1, 0]
-penalty	-2.0	0.63246	[-2, -3, -2, -2, -1, -2, -3, -2, -2, -1]
-pensive	0.3	1.1	[1, 0, 0, 1, 0, -1, 3, 0, -1, 0]
-perfect	2.7	0.78102	[2, 4, 2, 3, 4, 2, 3, 2, 3, 2]
-perfecta	1.4	1.42829	[1, 0, 0, 3, 1, 0, 0, 4, 3, 2]
-perfectas	0.6	1.11355	[0, 0, -1, 1, 0, 2, 3, 0, 1, 0]
-perfected	2.7	0.78102	[1, 3, 3, 4, 2, 3, 3, 2, 3, 3]
-perfecter	1.8	0.9798	[2, 1, 3, 1, 2, 1, 2, 4, 1, 1]
-perfecters	1.4	1.11355	[2, 1, 3, 0, 0, 3, 2, 0, 1, 2]
-perfectest	3.1	1.04403	[2, 4, 4, 4, 3, 2, 1, 3, 4, 4]
-perfectibilities	2.1	1.04403	[3, 2, 2, 3, 4, 1, 2, 2, 0, 2]
-perfectibility	1.8	1.249	[4, 3, 3, 0, 1, 0, 1, 2, 2, 2]
-perfectible	1.5	0.67082	[1, 2, 1, 1, 2, 1, 1, 3, 2, 1]
-perfecting	2.3	0.9	[1, 2, 3, 3, 1, 2, 2, 4, 2, 3]
-perfection	2.7	1.1	[3, 3, 3, 1, 2, 4, 4, 1, 2, 4]
-perfectionism	1.3	1.26886	[3, -1, 2, 1, 2, 2, 2, -1, 1, 2]
-perfectionist	1.5	1.20416	[3, -1, 3, 1, 2, 2, 2, 0, 1, 2]
-perfectionistic	0.7	1.67631	[-1, 0, 2, 0, 1, 0, 3, -1, 4, -1]
-perfectionists	0.1	1.22066	[1, -1, 1, -1, 0, 0, -1, 0, 3, -1]
-perfections	2.5	1.43178	[2, 4, 4, 3, 3, 4, -1, 2, 2, 2]
-perfective	1.2	0.87178	[1, 0, 1, 1, 3, 2, 2, 0, 1, 1]
-perfectively	2.1	1.13578	[3, 3, 1, 4, 0, 2, 1, 2, 2, 3]
-perfectiveness	0.9	1.51327	[-2, 3, -1, 0, 2, 0, 2, 2, 2, 1]
-perfectives	0.9	0.83066	[0, 2, 1, 1, 1, 0, 2, 0, 2, 0]
-perfectivity	2.2	0.9798	[3, 2, 0, 3, 1, 2, 3, 3, 2, 3]
-perfectly	3.2	0.4	[3, 4, 4, 3, 3, 3, 3, 3, 3, 3]
-perfectness	3.0	0.63246	[4, 3, 3, 3, 3, 2, 4, 2, 3, 3]
-perfecto	1.3	1.34536	[1, 0, 0, 2, 0, 0, 1, 4, 3, 2]
-perfects	1.6	1.11355	[1, 1, 1, 2, 1, 0, 1, 4, 3, 2]
-peril	-1.7	1.67631	[-3, -2, -2, 3, -3, -2, -3, -2, -1, -2]
-perjury	-1.9	0.9434	[-3, -2, -3, -2, -2, 0, -1, -2, -3, -1]
-perpetrator	-2.2	0.74833	[-2, -3, -2, -2, -2, -2, -4, -2, -1, -2]
-perpetrators	-1.0	1.67332	[-1, -2, -2, -2, -2, 2, 0, -4, 1, 0]
-perplexed	-1.3	0.64031	[-1, -1, -2, -1, -1, -1, 0, -2, -2, -2]
-persecute	-2.1	1.37477	[-2, -3, -2, 1, -1, -4, -2, -2, -2, -4]
-persecuted	-1.3	1.61555	[-2, -1, -2, -1, -2, 2, -4, 1, -2, -2]
-persecutes	-1.2	1.4	[-2, -1, -2, 0, -2, 1, -3, 1, -1, -3]
-persecuting	-1.5	1.62788	[-3, -2, -2, 0, -4, -3, -2, -1, 1, 1]
-perturbed	-1.4	0.8	[-2, -1, -1, 0, -2, -2, -2, 0, -2, -2]
-perverse	-1.8	1.8868	[-2, -4, -3, 1, -2, -4, 1, 0, -1, -4]
-perversely	-2.2	0.87178	[-1, -2, -2, -2, -1, -3, -2, -3, -4, -2]
-perverseness	-2.1	1.22066	[-3, -3, 1, -2, -3, -2, -3, -2, -1, -3]
-perversenesses	-0.5	1.74642	[-2, 3, -1, -2, 1, 0, 1, 0, -2, -3]
-perversion	-1.3	1.34536	[-3, -2, -2, 1, 1, -3, -1, -2, -1, -1]
-perversions	-1.2	1.83303	[-2, 0, -4, -2, -3, -3, 0, 1, -1, 2]
-perversities	-1.1	1.22066	[-2, -1, -2, 0, -2, -2, -2, 1, 1, -2]
-perversity	-2.6	0.8	[-2, -3, -2, -2, -4, -3, -3, -1, -3, -3]
-perversive	-2.1	0.7	[-3, -1, -3, -2, -2, -2, -2, -1, -3, -2]
-pervert	-2.3	0.9	[-2, -2, -1, -3, -4, -2, -3, -1, -3, -2]
-perverted	-2.5	1.56525	[-2, -4, -2, -4, -3, -4, 1, -2, -1, -4]
-pervertedly	-1.2	1.77764	[-3, -2, -1, -2, 2, -3, 1, -3, 1, -2]
-pervertedness	-1.2	1.46969	[1, -2, -3, -2, 0, -2, -3, 1, 0, -2]
-perverter	-1.7	1.48661	[-3, -4, -2, -2, -1, -1, 2, -2, -2, -2]
-perverters	-0.6	1.68523	[-2, -2, -1, 0, -1, 2, -3, 1, 2, -2]
-perverting	-1.0	2.09762	[4, -2, -2, -4, -2, 1, 0, -1, -2, -2]
-perverts	-2.8	0.6	[-3, -3, -2, -3, -3, -2, -2, -4, -3, -3]
-pesky	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
-pessimism	-1.5	1.36015	[-2, -3, 1, -2, -2, -1, 1, -3, -2, -2]
-pessimisms	-2.0	1.0	[-3, -1, -2, -2, -3, -1, 0, -2, -3, -3]
-pessimist	-1.5	1.36015	[-1, -3, 1, -2, -2, -2, 1, -3, -2, -2]
-pessimistic	-1.5	1.43178	[-3, -1, -1, 1, -3, -3, -2, -2, -2, 1]
-pessimistically	-2.0	1.0	[-1, -1, -3, -4, -2, -1, -1, -3, -2, -2]
-pessimists	-1.0	1.26491	[-1, 1, -1, 0, -2, -2, -2, -3, -1, 1]
-petrifaction	-1.9	1.3	[-3, -2, -1, -4, -3, 0, -1, 0, -2, -3]
-petrifactions	-0.3	1.00499	[0, -1, 0, 0, 0, 0, 0, 0, -3, 1]
-petrification	-0.1	1.44568	[-1, 2, -1, -1, 0, 2, 2, -2, -1, -1]
-petrifications	-0.4	0.8	[0, 0, -2, 0, 0, 0, 0, 0, -2, 0]
-petrified	-2.5	0.92195	[-4, -3, -2, -1, -2, -3, -2, -2, -2, -4]
-petrifies	-2.3	1.00499	[-4, -3, -2, -1, -2, -2, -1, -2, -2, -4]
-petrify	-1.7	0.9	[-2, -3, -1, -2, -1, -1, -2, -3, 0, -2]
-petrifying	-2.6	0.8	[-2, -3, -3, -2, -4, -2, -3, -1, -3, -3]
-pettier	-0.3	1.41774	[-1, -1, -1, -1, 2, 0, 2, -2, 1, -2]
-pettiest	-1.3	1.95192	[1, -3, -3, -3, -2, -1, 2, -1, 1, -4]
-petty	-0.8	1.32665	[1, -3, -2, -1, -1, -1, -1, -1, 2, -1]
-phobia	-1.6	1.0198	[-2, -2, 1, -2, -3, -1, -1, -2, -2, -2]
-phobias	-2.0	1.0	[-3, -2, -2, -3, -3, 0, -1, -2, -1, -3]
-phobic	-1.2	1.16619	[-2, -2, 1, -1, -2, -1, 1, -2, -2, -2]
-phobics	-1.3	0.64031	[-1, -1, -1, -2, -2, -1, 0, -2, -2, -1]
-picturesque	1.6	1.11355	[4, 1, 1, 2, 1, 2, 1, 0, 3, 1]
-pileup	-1.1	1.13578	[-2, 1, 0, -1, 0, -1, -3, -2, -2, -1]
-pique	-1.1	1.13578	[-2, -2, -2, 0, 0, -1, 1, -1, -1, -3]
-piqued	0.1	1.04403	[0, -2, 0, 1, 1, 1, -1, 1, -1, 1]
-piss	-1.7	0.9	[-2, -1, -1, -2, -1, -3, -3, 0, -2, -2]
-pissant	-1.5	1.5	[-1, -3, -3, 1, -3, -1, -1, -2, 1, -3]
-pissants	-2.5	0.80623	[-4, -3, -3, -2, -3, -1, -2, -3, -2, -2]
-pissed	-3.2	0.6	[-3, -3, -4, -3, -2, -4, -4, -3, -3, -3]
-pisser	-2.0	1.09545	[-2, -4, -1, -3, -2, -3, -1, -2, -2, 0]
-pissers	-1.4	2.00998	[-1, -1, -4, -2, -3, 4, -2, -1, -2, -2]
-pisses	-1.4	0.8	[-2, -2, -1, -3, -1, -1, -1, -2, -1, 0]
-pissing	-1.7	1.26886	[0, 0, -2, -2, -3, 0, -3, -1, -3, -3]
-pissoir	-0.8	1.4	[-2, 0, 0, -2, -1, -3, 0, -2, 0, 2]
-piteous	-1.2	1.46969	[-2, -1, -2, -2, -2, -1, 3, -1, -2, -2]
-pitiable	-1.1	1.22066	[-1, 0, -1, -1, 1, -2, -4, -1, -1, -1]
-pitiableness	-1.1	1.64012	[-2, -1, -1, -2, -4, 2, 1, 0, -2, -2]
-pitiably	-1.1	0.9434	[-1, 0, 0, -2, 0, -2, -3, -1, -1, -1]
-pitied	-1.3	1.1	[-2, -1, -3, -1, 1, 0, -2, -2, -1, -2]
-pitier	-1.2	1.32665	[-3, -1, -2, -3, -1, -1, 1, 1, -2, -1]
-pitiers	-1.3	0.9	[0, -1, -2, -2, -1, -1, -1, -3, -2, 0]
-pities	-1.2	1.249	[-2, -1, -2, -3, -1, -1, 1, 1, -2, -2]
-pitiful	-2.2	0.9798	[-3, -2, -1, -3, -2, -2, -3, -3, -3, 0]
-pitifuller	-1.8	1.07703	[-1, -1, -2, -3, -4, 0, -2, -2, -1, -2]
-pitifullest	-1.1	2.11896	[-2, 1, -1, -4, -4, -1, -3, -1, 2, 2]
-pitifully	-1.2	1.249	[-2, -1, -3, -2, -1, -1, -2, -1, 2, -1]
-pitifulness	-1.2	1.77764	[-3, -2, -1, -3, -2, -1, 3, 1, -2, -2]
-pitiless	-1.8	0.87178	[-2, 0, -2, -2, -2, -3, -1, -3, -1, -2]
-pitilessly	-2.1	0.7	[-2, -2, -1, -3, -3, -1, -3, -2, -2, -2]
-pitilessness	-0.5	1.62788	[1, 3, 1, -3, -2, -1, -1, -1, -1, -1]
-pity	-1.2	0.4	[-2, -2, -1, -1, -1, -1, -1, -1, -1, -1]
-pitying	-1.4	0.91652	[-1, -3, -1, -3, -2, -1, 0, -1, -1, -1]
-pityingly	-1.0	1.26491	[-2, -2, -1, -2, -2, 0, 0, -1, 2, -2]
-pityriasis	-0.8	0.87178	[-2, 0, 0, 0, -1, 0, -2, -1, -2, 0]
-play	1.4	1.0198	[2, 0, 1, 1, 1, 2, 1, 4, 1, 1]
-played	1.4	1.42829	[2, 1, 1, 1, 4, 0, 1, 0, 4, 0]
-playful	1.9	0.83066	[4, 2, 2, 2, 1, 1, 1, 2, 2, 2]
-playfully	1.6	0.4899	[2, 1, 1, 2, 1, 2, 2, 2, 1, 2]
-playfulness	1.2	0.87178	[2, 1, 2, -1, 1, 2, 1, 2, 1, 1]
-playing	0.8	0.87178	[0, 2, 2, 1, 0, 0, 2, 0, 0, 1]
-plays	1.0	1.09545	[0, 2, 0, 2, 0, 1, 0, 2, 3, 0]
-pleasant	2.3	0.64031	[2, 3, 3, 3, 2, 1, 2, 2, 3, 2]
-pleasanter	1.5	0.67082	[2, 2, 2, 1, 0, 1, 1, 2, 2, 2]
-pleasantest	2.6	0.8	[3, 3, 3, 1, 2, 4, 3, 2, 2, 3]
-pleasantly	2.1	0.53852	[1, 2, 3, 2, 2, 2, 2, 2, 3, 2]
-pleasantness	2.3	0.9	[3, 2, 3, 3, 3, 1, 1, 3, 1, 3]
-pleasantnesses	2.3	0.78102	[3, 1, 2, 3, 1, 2, 3, 3, 2, 3]
-pleasantries	1.3	0.45826	[1, 1, 1, 1, 1, 2, 1, 2, 2, 1]
-pleasantry	2.0	0.7746	[2, 2, 1, 1, 4, 2, 2, 2, 2, 2]
-please	1.3	0.78102	[2, 1, 2, 2, 2, 0, 2, 1, 0, 1]
-pleased	1.9	0.53852	[2, 2, 2, 2, 1, 1, 2, 3, 2, 2]
-pleaser	1.7	0.45826	[2, 2, 2, 2, 1, 1, 1, 2, 2, 2]
-pleasers	1.0	1.0	[1, 1, 2, 0, 1, 3, 1, 1, -1, 1]
-pleases	1.7	0.45826	[2, 1, 2, 2, 1, 1, 2, 2, 2, 2]
-pleasing	2.4	0.91652	[2, 3, 2, 2, 2, 2, 4, 4, 1, 2]
-pleasurability	1.9	0.83066	[1, 2, 2, 2, 2, 0, 2, 3, 3, 2]
-pleasurable	2.4	0.4899	[2, 3, 3, 2, 3, 3, 2, 2, 2, 2]
-pleasurableness	2.4	0.91652	[2, 3, 2, 1, 2, 3, 4, 3, 1, 3]
-pleasurably	2.6	0.4899	[2, 2, 2, 3, 3, 3, 3, 2, 3, 3]
-pleasure	2.7	0.9	[4, 4, 3, 2, 2, 3, 2, 1, 3, 3]
-pleasured	2.3	0.64031	[3, 2, 3, 2, 3, 3, 1, 2, 2, 2]
-pleasureless	-1.6	0.8	[-1, -1, -1, -1, -2, -3, -3, -2, -1, -1]
-pleasures	1.9	1.37477	[3, -2, 3, 2, 3, 2, 2, 2, 2, 2]
-pleasuring	2.8	0.4	[3, 2, 3, 3, 3, 3, 3, 2, 3, 3]
-poised	1.0	0.44721	[1, 1, 1, 1, 1, 1, 0, 1, 1, 2]
-poison	-2.5	0.92195	[-4, -3, -2, -4, -2, -2, -2, -3, -1, -2]
-poisoned	-2.2	0.9798	[-4, -1, -4, -1, -2, -2, -2, -2, -2, -2]
-poisoner	-2.7	0.78102	[-2, -3, -3, -4, -4, -2, -2, -2, -2, -3]
-poisoners	-3.1	0.83066	[-3, -4, -3, -4, -3, -4, -3, -3, -1, -3]
-poisoning	-2.8	1.249	[-4, -4, -2, 0, -2, -3, -4, -3, -2, -4]
-poisonings	-2.4	1.11355	[-2, 0, -2, -1, -4, -3, -3, -3, -3, -3]
-poisonous	-2.7	0.78102	[-3, -3, -4, -2, -1, -3, -3, -3, -3, -2]
-poisonously	-2.9	0.53852	[-3, -2, -3, -3, -2, -3, -3, -4, -3, -3]
-poisons	-2.7	0.9	[-3, -4, -3, -1, -2, -3, -3, -2, -2, -4]
-poisonwood	-1.0	0.89443	[0, -2, 0, 0, 0, -1, -2, -2, -2, -1]
-pollute	-2.3	0.64031	[-3, -2, -2, -2, -2, -3, -3, -1, -3, -2]
-polluted	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -2, -3, -2]
-polluter	-1.8	0.6	[-2, -1, -2, -1, -2, -2, -3, -1, -2, -2]
-polluters	-2.0	0.44721	[-2, -2, -2, -2, -2, -3, -2, -1, -2, -2]
-pollutes	-2.2	0.87178	[-2, -1, -2, -1, -3, -1, -3, -3, -3, -3]
-poor	-2.1	1.13578	[-2, -2, -1, -4, -2, 0, -2, -4, -2, -2]
-poorer	-1.5	1.56525	[-2, -3, -2, -2, -2, -2, 3, -2, -1, -2]
-poorest	-2.5	0.80623	[-2, -3, -3, -1, -2, -3, -3, -4, -2, -2]
-popular	1.8	0.74833	[2, 3, 1, 2, 2, 1, 3, 1, 2, 1]
-popularise	1.6	0.66332	[1, 1, 2, 2, 3, 2, 1, 2, 1, 1]
-popularised	1.1	0.9434	[1, 1, 0, 0, 3, 2, 1, 2, 1, 0]
-popularises	0.5	0.67082	[1, 0, 0, 0, 0, 1, 1, 2, 0, 0]
-popularising	1.2	0.6	[1, 0, 2, 2, 1, 1, 1, 2, 1, 1]
-popularities	1.6	0.8	[2, 1, 1, 2, 0, 2, 1, 2, 3, 2]
-popularity	2.1	1.04403	[2, 1, 1, 1, 3, 2, 3, 4, 3, 1]
-popularization	1.3	0.78102	[1, 2, 1, 2, 1, 0, 1, 1, 3, 1]
-popularizations	0.9	0.7	[1, 1, 1, 0, 2, 0, 1, 1, 2, 0]
-popularize	1.3	0.64031	[2, 2, 0, 2, 1, 1, 1, 1, 2, 1]
-popularized	1.9	0.83066	[3, 2, 3, 2, 1, 0, 2, 2, 2, 2]
-popularizer	1.8	0.74833	[2, 2, 3, 2, 1, 0, 2, 2, 2, 2]
-popularizers	1.0	0.89443	[0, 0, 1, 2, 1, 1, 1, 1, 3, 0]
-popularizes	1.4	0.8	[2, 1, 3, 2, 1, 0, 1, 2, 1, 1]
-popularizing	1.5	0.67082	[2, 2, 1, 1, 1, 2, 2, 0, 2, 2]
-popularly	1.8	0.74833	[1, 3, 2, 1, 3, 1, 2, 1, 2, 2]
-positive	2.6	0.91652	[2, 1, 2, 2, 3, 3, 4, 3, 4, 2]
-positively	2.4	0.66332	[2, 2, 3, 3, 4, 2, 2, 2, 2, 2]
-positiveness	2.3	1.18743	[2, 1, 4, 3, 4, 2, 0, 3, 2, 2]
-positivenesses	2.2	0.74833	[3, 3, 2, 2, 2, 2, 1, 3, 1, 3]
-positiver	2.3	0.78102	[1, 4, 2, 2, 2, 3, 2, 2, 2, 3]
-positives	2.4	0.4899	[3, 3, 2, 2, 2, 2, 3, 2, 3, 2]
-positivest	2.9	1.04403	[4, 3, 2, 1, 3, 4, 4, 4, 2, 2]
-positivism	1.6	1.35647	[3, 0, 2, 1, 2, 0, 3, 4, 1, 0]
-positivisms	1.8	0.9798	[4, 1, 2, 2, 2, 0, 2, 2, 1, 2]
-positivist	2.0	1.0	[3, 1, 2, 2, 2, 0, 2, 4, 2, 2]
-positivistic	1.9	0.83066	[2, 3, 1, 3, 1, 1, 3, 2, 1, 2]
-positivists	1.7	1.1	[1, 2, 1, 4, 2, 1, 3, 0, 1, 2]
-positivities	2.6	0.91652	[2, 2, 4, 3, 2, 3, 4, 3, 1, 2]
-positivity	2.3	0.9	[2, 2, 2, 3, 3, 3, 3, 0, 3, 2]
-possessive	-0.9	1.22066	[-1, -1, -2, -2, 0, -1, 0, -2, 2, -2]
-postpone	-0.9	0.83066	[1, -1, -2, -1, -1, -2, -1, -1, 0, -1]
-postponed	-0.8	0.4	[-1, -1, 0, 0, -1, -1, -1, -1, -1, -1]
-postpones	-1.1	0.83066	[-1, -1, -1, 0, -1, 0, -2, -1, -3, -1]
-postponing	-0.5	0.5	[0, -1, 0, -1, 0, 0, 0, -1, -1, -1]
-poverty	-2.3	1.00499	[-2, -4, -2, -4, -3, -1, -2, -2, -1, -2]
-powerful	1.8	0.9798	[4, 0, 2, 1, 2, 2, 2, 2, 1, 2]
-powerless	-2.2	0.6	[-2, -3, -2, -2, -3, -2, -3, -2, -1, -2]
-praise	2.6	0.8	[2, 4, 3, 3, 2, 1, 3, 3, 2, 3]
-praised	2.2	0.6	[3, 2, 2, 2, 2, 3, 1, 3, 2, 2]
-praiser	2.0	0.89443	[3, 1, 3, 1, 1, 2, 1, 3, 2, 3]
-praisers	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
-praises	2.4	0.4899	[3, 2, 2, 3, 2, 3, 2, 3, 2, 2]
-praiseworthily	1.9	0.7	[2, 1, 1, 3, 2, 2, 2, 3, 1, 2]
-praiseworthiness	2.4	0.8	[1, 3, 2, 4, 2, 2, 3, 2, 3, 2]
-praiseworthy	2.6	0.4899	[3, 3, 3, 3, 2, 2, 3, 2, 3, 2]
-praising	2.5	0.67082	[2, 3, 3, 2, 2, 3, 3, 3, 1, 3]
-pray	1.3	1.18743	[0, 3, 2, 1, 1, 1, -1, 3, 1, 2]
-praying	1.5	0.92195	[2, 2, 0, 3, 1, 3, 1, 1, 1, 1]
-prays	1.4	1.0198	[2, 0, 2, 0, 1, 1, 3, 1, 3, 1]
-prblm	-1.6	0.8	[-1, -1, -1, -1, -1, -3, -3, -2, -2, -1]
-prblms	-2.3	1.00499	[-2, -2, -2, -2, -4, -4, -3, -1, -2, -1]
-precious	2.7	0.64031	[3, 3, 3, 3, 3, 1, 3, 3, 2, 3]
-preciously	2.2	0.74833	[3, 3, 3, 2, 2, 1, 1, 3, 2, 2]
-preciousness	1.9	0.83066	[2, 4, 2, 2, 2, 1, 1, 1, 2, 2]
-prejudice	-2.3	0.78102	[-2, -1, -2, -2, -3, -2, -2, -3, -4, -2]
-prejudiced	-1.9	0.53852	[-2, -3, -1, -2, -1, -2, -2, -2, -2, -2]
-prejudices	-1.8	0.74833	[-2, -3, -1, -2, -1, -3, -2, -1, -1, -2]
-prejudicial	-2.6	0.8	[-3, -3, -2, -2, -3, -4, -2, -1, -3, -3]
-prejudicially	-1.5	1.74642	[-3, -1, -1, -3, -3, -1, -3, 1, 2, -3]
-prejudicialness	-2.4	1.42829	[-2, -3, 1, -3, -2, -4, -4, -3, -1, -3]
-prejudicing	-1.8	1.07703	[-2, -2, -2, -3, -2, -1, 1, -3, -2, -2]
-prepared	0.9	0.3	[1, 1, 1, 1, 1, 0, 1, 1, 1, 1]
-pressure	-1.2	0.6	[-1, -1, -1, -1, -2, -2, -1, -2, 0, -1]
-pressured	-0.9	1.04403	[-2, -1, -2, -1, 2, -1, -1, -1, -1, -1]
-pressureless	1.0	1.26491	[2, 0, 1, -1, -1, 2, 1, 2, 1, 3]
-pressures	-1.3	0.64031	[-2, -1, -1, -1, -3, -1, -1, -1, -1, -1]
-pressuring	-1.4	0.91652	[-3, -1, -1, -1, -1, -1, -1, -3, -2, 0]
-pressurise	-0.6	1.0198	[0, -2, 0, 1, 0, -2, 0, -2, 0, -1]
-pressurised	-0.4	0.66332	[0, 0, 0, -1, 0, -1, 0, -2, 0, 0]
-pressurises	-0.8	0.6	[-1, -1, -1, 0, -1, -1, 0, -1, 0, -2]
-pressurising	-0.6	1.28062	[-1, 0, 0, 2, -1, -1, -3, 0, -2, 0]
-pressurizations	-0.3	1.00499	[0, 0, 1, -2, 0, 0, -1, -2, 0, 1]
-pressurize	-0.7	1.34536	[0, -2, -2, 0, 0, -1, -3, 2, -1, 0]
-pressurized	0.1	0.83066	[0, 0, 0, 2, 0, 0, -1, -1, 0, 1]
-pressurizer	0.1	0.83066	[0, 0, 0, 1, 0, 0, -1, -1, 0, 2]
-pressurizers	-0.7	0.9	[-1, 0, -2, -1, -2, -1, 0, 0, 1, -1]
-pressurizes	-0.2	0.87178	[0, 0, -1, 1, 0, 0, -1, -2, 0, 1]
-pressurizing	-0.2	0.9798	[1, 0, -1, -1, -1, 0, -1, 2, 0, -1]
-pretend	-0.4	0.91652	[0, 1, -1, -1, -2, 0, -1, -1, 1, 0]
-pretending	0.4	1.49666	[2, 0, -1, -1, 0, 3, -2, 1, 0, 2]
-pretends	-0.4	0.66332	[0, -1, 0, -1, 1, 0, 0, -1, -1, -1]
-prettied	1.6	0.66332	[2, 1, 1, 1, 1, 2, 3, 2, 1, 2]
-prettier	2.1	0.53852	[2, 2, 2, 2, 2, 2, 3, 1, 2, 3]
-pretties	1.7	0.78102	[2, 1, 1, 2, 1, 2, 3, 1, 1, 3]
-prettiest	2.7	0.78102	[4, 3, 4, 2, 2, 2, 3, 2, 2, 3]
-pretty	2.2	0.6	[3, 2, 2, 2, 3, 1, 2, 2, 2, 3]
-prevent	0.1	1.22066	[-2, 1, 0, 0, -1, 2, -1, 2, 0, 0]
-prevented	0.1	0.7	[0, -1, 0, 2, 0, 0, 0, 0, 0, 0]
-preventing	-0.1	1.51327	[-2, 0, -2, 3, 0, 0, -1, -1, 2, 0]
-prevents	0.3	1.34536	[0, -2, 0, 0, 0, 2, 0, -1, 3, 1]
-prick	-1.4	1.42829	[-2, -2, -2, -1, 1, -1, -4, -2, 1, -2]
-pricked	-0.6	1.0198	[-1, -1, -2, 1, 0, -1, -2, -1, 1, 0]
-pricker	-0.3	0.9	[-1, -1, 0, 2, 0, -1, -1, -1, 0, 0]
-prickers	-0.2	0.87178	[1, -1, -1, 0, 1, -1, 0, 1, -1, -1]
-pricket	-0.5	0.67082	[0, -1, -1, -2, 0, 0, 0, 0, -1, 0]
-prickets	0.3	0.64031	[0, 2, 0, 0, 0, 1, 0, 0, 0, 0]
-pricking	-0.9	1.22066	[-2, -1, -2, 2, -2, -2, -1, 0, -1, 0]
-prickle	-1.0	0.44721	[-1, -1, -1, -1, -1, -1, -2, 0, -1, -1]
-prickled	-0.2	1.53623	[-1, -1, 3, -1, -2, 2, 0, 0, 0, -2]
-prickles	-0.8	0.74833	[0, -1, -1, -1, -2, -1, 0, 0, 0, -2]
-pricklier	-1.6	0.8	[-1, -2, -2, -2, -2, -1, -2, -1, 0, -3]
-prickliest	-1.4	1.35647	[-4, -2, -1, 0, -3, -1, -1, 1, -2, -1]
-prickliness	-0.6	0.91652	[-2, -1, -1, -1, -1, 1, -1, 1, 0, -1]
-prickling	-0.8	0.6	[-2, -1, 0, -1, 0, 0, -1, -1, -1, -1]
-prickly	-0.9	1.04403	[-2, -1, -1, -2, -1, 1, -2, -1, 1, -1]
-pricks	-0.9	1.04403	[-2, 0, -1, -3, -1, 1, 0, -1, -1, -1]
-pricky	-0.6	1.2	[-2, 1, -1, -2, -1, 2, 0, -1, -1, -1]
-pride	1.4	1.11355	[0, 2, 2, 2, 3, 1, -1, 2, 2, 1]
-prison	-2.3	0.64031	[-3, -3, -2, -2, -1, -2, -3, -3, -2, -2]
-prisoner	-2.5	1.0247	[-3, -1, -4, -4, -3, -2, -3, -2, -1, -2]
-prisoners	-2.3	0.78102	[-3, -2, -3, -3, -1, -3, -2, -1, -2, -3]
-privilege	1.5	0.80623	[2, 1, 0, 1, 3, 1, 2, 2, 2, 1]
-privileged	1.9	0.9434	[2, 3, 3, 2, 3, 1, 1, 2, 0, 2]
-privileges	1.6	1.2	[2, 1, 3, 1, 2, 2, 0, 0, 4, 1]
-privileging	0.7	1.1	[1, 1, 2, 2, -1, 2, 1, 0, 0, -1]
-prize	2.3	1.1	[2, 2, 0, 4, 4, 3, 2, 2, 2, 2]
-prized	2.4	0.8	[3, 3, 3, 2, 3, 2, 1, 3, 1, 3]
-prizefight	-0.1	1.13578	[-2, 2, 0, 0, 0, -2, 0, 1, 0, 0]
-prizefighter	1.0	1.0	[0, 2, 0, 0, 0, 2, 0, 2, 2, 2]
-prizefighters	-0.1	1.04403	[0, 0, -3, 0, 0, 0, 0, 1, 1, 0]
-prizefighting	0.4	0.91652	[0, 0, 0, 1, 0, 3, 0, 0, 0, 0]
-prizefights	0.3	0.78102	[1, 2, 0, 0, -1, 0, 0, 1, 0, 0]
-prizer	1.0	1.0	[0, 3, 0, 0, 2, 1, 2, 1, 0, 1]
-prizers	0.8	0.9798	[2, 0, 0, 1, 3, 1, 0, 1, 0, 0]
-prizes	2.0	1.09545	[3, 3, 2, 0, 2, 1, 2, 4, 1, 2]
-prizewinner	2.3	1.00499	[3, 0, 3, 3, 2, 2, 2, 4, 2, 2]
-prizewinners	2.4	1.11355	[4, 2, 2, 2, 0, 4, 2, 3, 3, 2]
-prizewinning	3.0	0.7746	[3, 3, 3, 3, 3, 4, 3, 1, 3, 4]
-proactive	1.8	0.87178	[2, 3, 3, 1, 1, 1, 1, 3, 1, 2]
-problem	-1.7	0.64031	[-2, -2, -1, -1, -1, -3, -1, -2, -2, -2]
-problematic	-1.9	0.53852	[-1, -2, -2, -2, -2, -3, -2, -1, -2, -2]
-problematical	-1.8	0.6	[-3, -1, -1, -2, -2, -2, -2, -2, -1, -2]
-problematically	-2.0	1.0	[-2, -1, -3, -1, -1, -2, -4, -3, -1, -2]
-problematics	-1.3	1.1	[0, -1, -1, 0, -2, -1, -4, -1, -2, -1]
-problems	-1.7	0.78102	[-2, -1, -1, -3, -2, -1, -3, -1, -1, -2]
-profit	1.9	0.7	[2, 3, 2, 1, 2, 1, 3, 1, 2, 2]
-profitabilities	1.1	0.7	[1, 1, 3, 1, 1, 1, 1, 0, 1, 1]
-profitability	1.1	1.44568	[1, 1, -2, 2, 0, 3, 1, 3, 2, 0]
-profitable	1.9	0.9434	[2, 3, 0, 3, 1, 2, 1, 3, 2, 2]
-profitableness	2.4	1.11355	[1, 4, 2, 4, 2, 2, 4, 2, 1, 2]
-profitably	1.6	0.91652	[1, 2, 0, 3, 1, 3, 1, 1, 2, 2]
-profited	1.3	1.00499	[2, 2, 2, 1, 0, 0, 1, 3, 0, 2]
-profiteer	0.8	1.6	[2, -2, -1, 3, -1, 2, 1, 2, 0, 2]
-profiteered	-0.5	1.9105	[0, 0, 2, -2, -3, -2, 3, 0, -3, 0]
-profiteering	-0.6	2.05913	[-1, 2, -2, -4, -2, 2, 1, -2, 2, -2]
-profiteers	0.5	1.5	[-2, 1, -1, -1, 1, -1, 2, 2, 2, 2]
-profiter	0.7	1.55242	[2, 2, 2, 1, -1, 1, -1, 3, 0, -2]
-profiterole	0.4	0.66332	[0, 0, 0, 0, 0, 1, 0, 1, 2, 0]
-profiteroles	0.5	0.92195	[0, 0, -1, 2, 2, 0, 0, 1, 0, 1]
-profiting	1.6	0.91652	[1, 0, 3, 2, 1, 2, 3, 1, 1, 2]
-profitless	-1.5	0.92195	[-2, -2, -3, -1, -1, -1, 0, -1, -1, -3]
-profits	1.9	1.04403	[2, 2, 1, 0, 2, 1, 2, 4, 3, 2]
-profitwise	0.9	0.83066	[1, 2, 0, 0, 1, 2, 2, 0, 1, 0]
-progress	1.8	0.74833	[3, 2, 1, 2, 3, 1, 1, 2, 2, 1]
-prominent	1.3	0.45826	[2, 1, 1, 2, 1, 1, 1, 2, 1, 1]
-promiscuities	-0.8	1.32665	[-1, 0, -2, -2, -1, 2, -3, -1, 0, 0]
-promiscuity	-1.8	1.07703	[-1, -2, -4, -2, -3, -1, 0, -2, -1, -2]
-promiscuous	-0.3	1.34536	[2, -3, -1, -1, 0, -1, 0, -1, 1, 1]
-promiscuously	-1.5	1.28452	[-2, -1, -3, 2, -2, -2, -1, -2, -2, -2]
-promiscuousness	-0.9	1.37477	[-3, -1, 1, -2, -2, 1, 1, -1, -2, -1]
-promise	1.3	0.64031	[1, 0, 1, 1, 2, 2, 1, 1, 2, 2]
-promised	1.5	0.92195	[2, 1, 1, 0, 0, 2, 2, 3, 2, 2]
-promisee	0.8	0.87178	[2, 1, 0, 0, 0, 2, 0, 2, 1, 0]
-promisees	1.1	0.9434	[2, 0, 1, 0, 0, 0, 2, 2, 2, 2]
-promiser	1.3	0.9	[2, 1, 1, 0, 0, 2, 2, 3, 1, 1]
-promisers	1.6	0.4899	[2, 1, 2, 1, 2, 1, 2, 1, 2, 2]
-promises	1.6	0.8	[2, 1, 1, 0, 2, 1, 3, 2, 2, 2]
-promising	1.7	0.45826	[1, 2, 2, 1, 2, 2, 1, 2, 2, 2]
-promisingly	1.2	0.6	[2, 2, 1, 1, 1, 2, 1, 0, 1, 1]
-promisor	1.0	0.63246	[2, 2, 0, 1, 1, 1, 0, 1, 1, 1]
-promisors	0.4	0.8	[0, 0, 0, 2, 0, 2, 0, 0, 0, 0]
-promissory	0.9	1.13578	[2, 0, 0, 3, 0, 2, 2, 0, 0, 0]
-promote	1.6	0.8	[2, 1, 2, 3, 0, 1, 2, 2, 1, 2]
-promoted	1.8	0.74833	[2, 2, 1, 1, 1, 2, 2, 1, 3, 3]
-promotes	1.4	0.91652	[1, 2, 0, 0, 1, 2, 2, 1, 3, 2]
-promoting	1.5	0.67082	[1, 2, 2, 1, 2, 1, 2, 0, 2, 2]
-propaganda	-1.0	1.54919	[-2, -3, -2, -3, -2, 1, -1, 1, 0, 1]
-prosecute	-1.7	1.00499	[-2, -2, -2, -1, -1, -2, 0, -1, -4, -2]
-prosecuted	-1.6	1.95959	[-2, -2, -2, -3, -3, -3, -4, 2, 2, -1]
-prosecutes	-1.8	1.53623	[-2, -2, -2, -3, -2, -2, -4, 1, 1, -3]
-prosecution	-2.2	1.07703	[-4, -1, -2, -2, -3, -2, -1, -4, -1, -2]
-prospect	1.2	0.87178	[1, 3, 1, 0, 2, 2, 1, 0, 1, 1]
-prospects	1.2	0.6	[2, 1, 1, 1, 1, 0, 1, 2, 2, 1]
-prosperous	2.1	1.86815	[-3, 3, 3, 2, 4, 2, 3, 3, 3, 1]
-protect	1.6	0.8	[1, 3, 1, 1, 1, 1, 3, 2, 1, 2]
-protected	1.9	0.7	[1, 1, 2, 3, 2, 2, 2, 1, 3, 2]
-protects	1.3	0.78102	[2, 2, 0, 2, 1, 1, 0, 2, 2, 1]
-protest	-1.0	1.34164	[-2, -1, -1, -2, -1, -2, 1, -2, 2, -2]
-protested	-0.5	1.62788	[-2, -3, -1, -1, 0, 2, 2, -2, 1, -1]
-protesters	-0.9	0.7	[0, 0, 0, -1, -2, -2, -1, -1, -1, -1]
-protesting	-1.8	0.74833	[-2, -2, -1, -2, -1, -1, -2, -1, -3, -3]
-protests	-0.9	1.57797	[-2, -2, 2, 0, -1, -2, -2, -2, 2, -2]
-proud	2.1	0.3	[2, 3, 2, 2, 2, 2, 2, 2, 2, 2]
-prouder	2.2	1.16619	[2, 3, 3, 4, 0, 1, 1, 3, 2, 3]
-proudest	2.6	0.66332	[4, 2, 2, 2, 2, 3, 2, 3, 3, 3]
-proudful	1.9	1.51327	[3, 3, 0, 1, -1, 1, 4, 3, 2, 3]
-proudhearted	1.4	0.91652	[2, -1, 1, 2, 2, 1, 2, 2, 2, 1]
-proudly	2.6	0.4899	[2, 2, 3, 3, 2, 3, 3, 3, 2, 3]
-provoke	-1.7	0.64031	[-2, -2, -1, -1, -1, -2, -2, -1, -3, -2]
-provoked	-1.1	0.83066	[-1, -1, 0, -2, -2, -2, -2, 0, 0, -1]
-provokes	-1.3	0.78102	[-2, -2, -1, -2, -1, -2, -2, 0, 0, -1]
-provoking	-0.8	1.249	[-2, -2, -1, -2, 1, -1, 1, 1, -1, -2]
-pseudoscience	-1.2	1.32665	[-1, -1, -3, -4, 0, 0, -2, 0, 0, -1]
-puke	-2.4	1.0198	[-1, -3, -3, -2, -4, -4, -2, -1, -2, -2]
-puked	-1.8	0.6	[-1, -2, -2, -3, -1, -1, -2, -2, -2, -2]
-pukes	-1.9	0.7	[-1, -2, -3, -3, -1, -1, -2, -2, -2, -2]
-puking	-1.8	1.46969	[0, -2, -4, -3, -2, -3, 1, -1, -1, -3]
-pukka	2.8	0.4	[3, 2, 3, 3, 3, 2, 3, 3, 3, 3]
-punish	-2.4	0.91652	[-1, -3, -3, -4, -3, -1, -2, -2, -2, -3]
-punishabilities	-1.7	0.78102	[0, -2, -3, -2, -1, -2, -2, -1, -2, -2]
-punishability	-1.6	1.49666	[-2, -2, -1, -1, -2, -2, -3, 2, -4, -1]
-punishable	-1.9	0.7	[-3, -1, -1, -2, -2, -1, -3, -2, -2, -2]
-punished	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -2, -3, -2]
-punisher	-1.9	0.53852	[-3, -1, -2, -2, -2, -2, -2, -1, -2, -2]
-punishers	-2.6	0.8	[-3, -3, -3, -3, -2, -2, -4, -2, -1, -3]
-punishes	-2.1	0.7	[-3, -2, -3, -2, -1, -2, -2, -3, -1, -2]
-punishing	-2.6	0.8	[-2, -3, -3, -3, -4, -1, -3, -2, -2, -3]
-punishment	-2.2	0.6	[-2, -1, -2, -2, -3, -3, -2, -2, -2, -3]
-punishments	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -2, -3, -1, -2]
-punitive	-2.3	0.78102	[-4, -2, -3, -1, -2, -2, -2, -2, -3, -2]
-pushy	-1.1	0.83066	[-2, -2, -1, -1, -1, 1, -1, -2, -1, -1]
-puzzled	-0.7	0.45826	[0, 0, -1, -1, 0, -1, -1, -1, -1, -1]
-quaking	-1.5	0.67082	[-1, -2, -2, -2, -1, 0, -2, -1, -2, -2]
-questionable	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-questioned	-0.4	1.0198	[-2, 0, 0, -1, -1, 2, 0, 0, -1, -1]
-questioning	-0.4	0.66332	[0, -1, -1, 0, 0, 0, -2, 0, 0, 0]
-racism	-3.1	0.9434	[-4, -4, -4, -2, -3, -4, -2, -2, -2, -4]
-racist	-3.0	0.89443	[-1, -3, -3, -4, -3, -4, -4, -2, -3, -3]
-racists	-2.5	0.92195	[-3, 0, -3, -2, -2, -3, -3, -3, -3, -3]
-radian	0.4	0.66332	[0, 0, 0, 0, 0, 0, 1, 2, 0, 1]
-radiance	1.4	1.11355	[3, 1, 2, 3, 1, 1, -1, 1, 2, 1]
-radiances	1.1	0.53852	[1, 2, 2, 1, 1, 1, 0, 1, 1, 1]
-radiancies	0.8	1.16619	[-1, 0, 3, 1, 1, 1, 1, 2, -1, 1]
-radiancy	1.4	0.66332	[2, 1, 1, 3, 1, 1, 1, 1, 2, 1]
-radians	0.2	0.6	[0, 2, 0, 0, 0, 0, 0, 0, 0, 0]
-radiant	2.1	0.83066	[4, 2, 2, 2, 2, 1, 1, 3, 2, 2]
-radiantly	1.3	0.78102	[3, 2, 1, 1, 1, 1, 1, 0, 1, 2]
-radiants	1.2	0.6	[2, 1, 0, 2, 1, 1, 1, 2, 1, 1]
-rage	-2.6	0.8	[-3, -2, -2, -3, -3, -4, -1, -2, -3, -3]
-raged	-2.0	0.63246	[-2, -1, -1, -3, -3, -2, -2, -2, -2, -2]
-ragee	-0.4	1.42829	[-2, -1, 0, 3, 0, -2, -2, 0, 0, 0]
-rageful	-2.8	0.6	[-3, -3, -3, -3, -2, -4, -2, -3, -2, -3]
-rages	-2.1	0.7	[-3, -1, -1, -3, -3, -2, -2, -2, -2, -2]
-raging	-2.4	1.0198	[-1, -3, -3, -1, -3, -3, -1, -4, -2, -3]
-rainy	-0.3	0.64031	[-1, 0, 1, 0, 0, 0, -1, 0, -1, -1]
-rancid	-2.5	1.11803	[-3, -3, -3, -2, -3, 0, -3, -1, -4, -3]
-rancidity	-2.6	0.8	[-4, -3, -3, -2, -2, -2, -2, -2, -2, -4]
-rancidly	-2.5	1.20416	[-2, -1, -4, -3, -4, -1, -2, -3, -4, -1]
-rancidness	-2.6	0.91652	[-3, -4, -2, -3, -4, -2, -3, -1, -2, -2]
-rancidnesses	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -2, -1, -2]
-rant	-1.4	0.66332	[-1, -2, -2, -1, -2, -2, -2, -1, 0, -1]
-ranter	-1.2	1.16619	[-1, -2, -2, -2, -1, -1, -1, -2, 2, -2]
-ranters	-1.2	0.87178	[-1, -1, -1, 0, -1, -1, -3, -2, 0, -2]
-rants	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -1, -2, -2, -1]
-rape	-3.7	0.64031	[-4, -2, -4, -4, -4, -4, -4, -4, -3, -4]
-raped	-3.6	0.4899	[-3, -3, -4, -4, -3, -4, -4, -4, -3, -4]
-raper	-3.4	0.66332	[-3, -3, -4, -4, -3, -3, -4, -4, -2, -4]
-rapers	-3.6	0.66332	[-2, -4, -4, -3, -4, -3, -4, -4, -4, -4]
-rapes	-3.5	0.67082	[-4, -3, -4, -4, -3, -4, -4, -3, -2, -4]
-rapeseeds	-0.5	1.20416	[0, 0, 0, 0, 0, -4, 0, 0, -1, 0]
-raping	-3.8	0.4	[-3, -4, -4, -4, -4, -4, -4, -4, -3, -4]
-rapist	-3.9	0.3	[-4, -4, -4, -4, -4, -4, -3, -4, -4, -4]
-rapists	-3.3	0.64031	[-3, -3, -4, -3, -4, -3, -4, -2, -4, -3]
-rapture	0.6	2.2891	[-2, 2, -2, 3, 3, 4, -1, -1, 2, -2]
-raptured	0.9	1.97231	[0, -2, 0, 2, 4, -1, 4, -1, 1, 2]
-raptures	0.7	2.05183	[0, -2, 0, 2, 4, -2, 4, -1, 1, 1]
-rapturous	1.7	1.95192	[3, 4, 0, 3, 2, 2, 4, -2, -1, 2]
-rash	-1.7	0.78102	[-2, -1, -1, -3, -2, -2, -1, -1, -1, -3]
-ratified	0.6	0.4899	[1, 0, 0, 1, 1, 0, 1, 1, 0, 1]
-reach	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
-reached	0.4	0.4899	[1, 0, 0, 0, 1, 1, 0, 1, 0, 0]
-reaches	0.2	0.4	[0, 0, 0, 1, 0, 1, 0, 0, 0, 0]
-reaching	0.8	0.6	[1, 0, 2, 0, 1, 0, 1, 1, 1, 1]
-readiness	1.0	0.63246	[1, 1, 1, 1, 0, 1, 2, 1, 2, 0]
-ready	1.5	1.0247	[2, 1, 1, 0, 2, 2, 1, 1, 1, 4]
-reassurance	1.5	0.5	[1, 1, 1, 1, 2, 1, 2, 2, 2, 2]
-reassurances	1.4	0.8	[0, 1, 1, 2, 1, 1, 1, 2, 3, 2]
-reassure	1.4	0.4899	[2, 2, 1, 1, 2, 1, 2, 1, 1, 1]
-reassured	1.7	0.45826	[2, 1, 1, 1, 2, 2, 2, 2, 2, 2]
-reassures	1.5	0.92195	[2, 1, 1, 2, 2, 2, -1, 2, 2, 2]
-reassuring	1.7	1.48661	[3, 3, 2, -2, 1, 3, 3, 2, 1, 1]
-reassuringly	1.8	0.87178	[1, 3, 2, 1, 2, 3, 3, 1, 1, 1]
-rebel	-0.6	1.49666	[-2, -1, -1, 0, -2, -1, 2, 1, 1, -3]
-rebeldom	-1.5	1.0247	[-2, -2, -1, -3, -2, -2, -1, 1, -1, -2]
-rebelled	-1.0	1.26491	[-2, -2, 0, -2, 0, -2, -2, -1, -1, 2]
-rebelling	-1.1	1.51327	[-3, -1, -2, -1, -2, -1, -1, -3, 2, 1]
-rebellion	-0.5	1.80278	[-2, -2, -1, -1, 3, -1, 1, -3, 2, -1]
-rebellions	-1.1	1.57797	[-2, -4, -3, 0, 0, -1, 1, -2, -1, 1]
-rebellious	-1.2	1.249	[-2, -1, -3, -1, -2, -2, 1, -1, 1, -2]
-rebelliously	-1.8	0.87178	[-3, 0, -2, -2, -1, -2, -3, -1, -2, -2]
-rebelliousness	-1.2	1.16619	[0, -3, -1, -2, 1, -1, -2, 0, -2, -2]
-rebels	-0.8	1.07703	[-1, 0, 0, -2, 0, -3, 0, 0, 0, -2]
-recession	-1.8	1.07703	[-3, -1, -4, -2, -1, -1, -1, -1, -3, -1]
-reckless	-1.7	0.64031	[-2, -1, -1, -3, -1, -2, -1, -2, -2, -2]
-recommend	1.5	0.67082	[1, 1, 1, 1, 2, 3, 2, 2, 1, 1]
-recommended	0.8	1.07703	[1, 1, 0, -2, 1, 2, 1, 2, 1, 1]
-recommends	0.9	0.9434	[1, 1, 2, 0, 0, 2, 1, -1, 2, 1]
-redeemed	1.3	0.9	[2, 1, 2, 2, 1, -1, 2, 1, 2, 1]
-reek	-2.4	0.66332	[-3, -3, -2, -3, -3, -2, -2, -2, -1, -3]
-reeked	-2.0	1.09545	[-4, -3, -2, -3, -1, -2, 0, -1, -2, -2]
-reeker	-1.7	1.1	[0, -2, -1, 0, -3, -3, -2, -1, -3, -2]
-reekers	-1.5	1.0247	[-3, 0, 0, 0, -2, -2, -2, -2, -2, -2]
-reeking	-2.0	1.48324	[2, -2, -2, -3, -3, -3, -1, -3, -3, -2]
-refuse	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-refused	-1.2	0.74833	[0, -1, -1, -1, -1, -1, -2, -1, -3, -1]
-refusing	-1.7	0.64031	[-1, -1, -1, -2, -2, -2, -3, -1, -2, -2]
-regret	-1.8	0.6	[-2, -2, -2, -2, -1, -3, -1, -1, -2, -2]
-regretful	-1.9	0.83066	[-1, -2, -1, -2, -1, -2, -1, -3, -3, -3]
-regretfully	-1.9	0.83066	[-1, -1, -1, -3, -2, -3, -1, -3, -2, -2]
-regretfulness	-1.6	0.66332	[-1, -3, -1, -1, -1, -2, -1, -2, -2, -2]
-regrets	-1.5	0.5	[-2, -2, -2, -1, -2, -1, -1, -2, -1, -1]
-regrettable	-2.3	0.78102	[-3, -1, -2, -1, -3, -2, -3, -3, -2, -3]
-regrettably	-2.0	0.63246	[-2, -3, -1, -3, -2, -1, -2, -2, -2, -2]
-regretted	-1.6	0.4899	[-2, -1, -2, -2, -2, -2, -1, -1, -1, -2]
-regretter	-1.6	0.66332	[-2, -1, -2, -2, -3, -2, -1, -1, -1, -1]
-regretters	-2.0	0.89443	[-1, -2, -2, -2, -4, -3, -1, -1, -2, -2]
-regretting	-1.7	0.78102	[-3, -2, -2, -1, -3, -1, -1, -1, -2, -1]
-reinvigorate	2.3	0.78102	[3, 3, 3, 2, 3, 1, 2, 1, 2, 3]
-reinvigorated	1.9	1.13578	[2, 2, 3, 1, 2, 3, 3, -1, 2, 2]
-reinvigorates	1.8	0.9798	[2, 2, 3, 0, 2, 2, 3, 0, 2, 2]
-reinvigorating	1.7	0.64031	[1, 2, 1, 1, 2, 2, 2, 1, 3, 2]
-reinvigoration	2.2	0.4	[2, 2, 2, 3, 2, 3, 2, 2, 2, 2]
-reject	-1.7	0.64031	[-1, -2, -2, -2, -1, -3, -1, -1, -2, -2]
-rejected	-2.3	0.45826	[-3, -2, -3, -3, -2, -2, -2, -2, -2, -2]
-rejectee	-2.3	0.45826	[-3, -2, -2, -3, -2, -3, -2, -2, -2, -2]
-rejectees	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -2, -2, -1]
-rejecter	-1.6	0.66332	[-2, -1, -1, -3, -2, -2, -1, -1, -1, -2]
-rejecters	-1.8	0.6	[-2, -3, -1, -1, -2, -1, -2, -2, -2, -2]
-rejecting	-2.0	0.7746	[-1, -2, -3, -1, -2, -3, -2, -1, -3, -2]
-rejectingly	-1.7	0.64031	[-1, -2, -2, -2, -1, -2, -2, -1, -3, -1]
-rejection	-2.5	0.67082	[-3, -3, -2, -4, -3, -2, -2, -2, -2, -2]
-rejections	-2.1	0.53852	[-3, -2, -2, -2, -1, -2, -3, -2, -2, -2]
-rejective	-1.8	0.6	[-3, -2, -2, -2, -1, -1, -2, -2, -1, -2]
-rejector	-1.8	0.74833	[-2, -1, -2, -3, -1, -2, -1, -2, -3, -1]
-rejects	-2.2	0.4	[-3, -2, -2, -2, -2, -3, -2, -2, -2, -2]
-rejoice	1.9	0.9434	[2, 3, 1, 3, 1, 3, 1, 3, 1, 1]
-rejoiced	2.0	0.63246	[2, 1, 2, 3, 2, 2, 3, 1, 2, 2]
-rejoices	2.1	0.7	[2, 1, 2, 3, 2, 3, 3, 2, 2, 1]
-rejoicing	2.8	0.4	[3, 3, 2, 3, 3, 3, 2, 3, 3, 3]
-relax	1.9	1.13578	[2, 1, 1, 1, 4, 4, 2, 1, 1, 2]
-relaxant	1.0	0.89443	[2, 1, 0, 0, 1, 0, 1, 3, 1, 1]
-relaxants	0.7	0.9	[0, 1, 1, 0, -1, 2, 1, 2, 1, 0]
-relaxation	2.4	0.4899	[3, 2, 3, 2, 2, 3, 3, 2, 2, 2]
-relaxations	1.0	0.89443	[-1, 0, 2, 1, 1, 2, 1, 2, 1, 1]
-relaxed	2.2	0.87178	[2, 3, 1, 3, 3, 3, 1, 2, 1, 3]
-relaxedly	1.5	0.5	[2, 2, 1, 1, 2, 1, 2, 2, 1, 1]
-relaxedness	2.0	0.63246	[2, 2, 3, 1, 3, 2, 2, 2, 1, 2]
-relaxer	1.6	0.8	[0, 2, 1, 2, 1, 3, 1, 2, 2, 2]
-relaxers	1.4	0.4899	[2, 1, 1, 1, 2, 2, 2, 1, 1, 1]
-relaxes	1.5	0.5	[2, 1, 1, 1, 1, 2, 2, 2, 1, 2]
-relaxin	1.7	0.64031	[2, 2, 1, 2, 0, 2, 2, 2, 2, 2]
-relaxing	2.2	0.6	[1, 2, 2, 2, 2, 3, 3, 3, 2, 2]
-relaxins	1.2	1.4	[1, 3, 2, 1, 0, 1, -2, 3, 2, 1]
-relentless	0.2	1.07703	[3, -1, 0, -1, 0, 1, 0, 0, 0, 0]
-reliant	0.5	1.20416	[0, 2, -1, 1, 0, 1, 2, -1, 2, -1]
-relief	2.1	0.53852	[2, 2, 2, 3, 2, 3, 2, 1, 2, 2]
-reliefs	1.3	0.78102	[1, 2, 2, 2, 2, 2, 0, 0, 1, 1]
-relievable	1.1	1.22066	[1, -2, 1, 1, 1, 1, 3, 2, 1, 2]
-relieve	1.5	0.5	[1, 2, 1, 2, 1, 1, 2, 2, 1, 2]
-relieved	1.6	0.66332	[2, 1, 2, 1, 1, 3, 2, 1, 1, 2]
-relievedly	1.4	0.4899	[1, 2, 1, 1, 1, 2, 2, 2, 1, 1]
-reliever	1.5	0.80623	[2, 1, 2, 2, 1, 2, 0, 1, 1, 3]
-relievers	1.0	0.63246	[1, 1, 1, 1, 2, 0, 2, 0, 1, 1]
-relieves	1.5	0.80623	[2, 1, 2, 2, 1, 2, 0, 1, 1, 3]
-relieving	1.5	1.0247	[2, 2, 1, 2, 3, -1, 2, 1, 1, 2]
-relievo	1.3	1.00499	[0, 2, 1, 2, 2, -1, 2, 2, 2, 1]
-relishing	1.6	0.8	[1, 2, 1, 3, 2, 3, 1, 1, 1, 1]
-reluctance	-1.4	0.4899	[-2, -2, -1, -1, -1, -1, -2, -1, -2, -1]
-reluctancy	-1.6	0.8	[-3, -2, -1, -1, -1, -1, -2, -1, -3, -1]
-reluctant	-1.0	0.7746	[0, -1, 0, -1, -1, 0, -1, -2, -2, -2]
-reluctantly	-0.4	1.42829	[-1, 2, -1, -2, -2, -1, 1, -1, 2, -1]
-remarkable	2.6	1.0198	[3, 4, 3, 2, 2, 3, 3, 0, 3, 3]
-remorse	-1.1	1.51327	[-3, -1, -3, 1, 2, -2, -1, -1, -2, -1]
-remorseful	-0.9	2.07123	[-1, 1, -2, -3, 2, -1, -3, -2, 3, -3]
-remorsefully	-0.7	1.34536	[-1, -1, 0, -1, -2, -1, -1, 1, -3, 2]
-remorsefulness	-0.7	1.61555	[-1, -2, 2, -2, -2, -1, 0, -3, 2, 0]
-remorseless	-2.3	0.64031	[-4, -2, -2, -2, -3, -2, -2, -2, -2, -2]
-remorselessly	-2.0	1.09545	[-3, -3, -3, -2, -1, -1, -4, -1, -1, -1]
-remorselessness	-2.8	1.16619	[-3, -4, -2, -2, -3, -4, -1, -1, -4, -4]
-repetitive	-1.0	0.06325	[-1, -1, 0, -2, -1, -2, -1, -1, 0, -1]
-repress	-1.4	0.66332	[-1, -1, -3, -2, -1, -1, -2, -1, -1, -1]
-repressed	-1.3	0.78102	[-1, 0, -3, -1, -1, -2, -1, -1, -2, -1]
-represses	-1.3	1.00499	[-1, 0, -3, -1, 0, -3, -1, -1, -2, -1]
-repressible	-1.5	0.92195	[-1, -2, -3, -1, 0, -1, -3, -1, -2, -1]
-repressing	-1.8	0.6	[-1, -2, -2, -2, -1, -3, -2, -1, -2, -2]
-repression	-1.6	0.91652	[-2, -2, -1, -1, -1, -1, -4, -1, -2, -1]
-repressions	-1.7	1.00499	[-2, -3, -1, -2, -2, -3, -2, 0, 0, -2]
-repressive	-1.4	1.11355	[-3, -1, -1, -2, -1, -3, 1, -2, -1, -1]
-repressively	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -2, -2, -1, -1]
-repressiveness	-1.0	1.73205	[-2, -1, -2, -3, -1, -1, 1, -3, 3, -1]
-repressor	-1.4	1.28062	[-1, 0, -3, -1, -2, -4, 0, -1, 0, -2]
-repressors	-2.2	1.66132	[-2, -4, 0, -2, -1, -3, -4, -3, 1, -4]
-repressurize	-0.3	0.64031	[0, 0, 0, 0, 0, 0, -2, 0, -1, 0]
-repressurized	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
-repressurizes	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
-repressurizing	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
-repulse	-2.8	0.4	[-3, -3, -3, -3, -2, -3, -3, -3, -2, -3]
-repulsed	-2.2	0.9798	[0, -2, -2, -2, -3, -3, -1, -3, -3, -3]
-rescue	2.3	0.78102	[1, 3, 1, 3, 2, 3, 3, 2, 2, 3]
-rescued	1.8	1.53623	[3, 2, 2, -2, 3, 2, 1, 4, 1, 2]
-rescues	1.3	0.78102	[3, 2, 0, 2, 1, 1, 1, 1, 1, 1]
-resent	-0.7	1.26886	[-2, -2, 0, -1, -1, -1, -2, 1, 2, -1]
-resented	-1.6	1.35647	[-2, -3, -2, -2, -1, -1, 2, -3, -2, -2]
-resentence	-1.0	0.7746	[-1, 0, -1, -1, 0, -2, -1, 0, -2, -2]
-resentenced	-0.8	0.9798	[0, -2, -1, 0, -1, 0, 0, 0, -3, -1]
-resentences	-0.6	0.8	[0, -2, -1, 0, -1, 0, 0, 0, -2, 0]
-resentencing	0.2	0.87178	[-1, -1, 0, 1, 0, 0, 1, 2, 0, 0]
-resentful	-2.1	0.83066	[-3, -1, -2, -3, -1, -1, -3, -2, -2, -3]
-resentfully	-1.4	1.11355	[-1, -2, -1, -1, -3, 1, -1, -3, -1, -2]
-resentfulness	-2.0	0.7746	[-2, -2, -3, -3, -2, -3, -2, -1, -1, -1]
-resenting	-1.2	1.72047	[-2, -1, -2, -2, -1, -3, -3, 2, 2, -2]
-resentment	-1.9	0.83066	[-1, -3, -2, -3, -2, -3, -1, -1, -1, -2]
-resentments	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -2, -2, -1, -3]
-resents	-1.2	1.32665	[-2, -1, -1, -3, 1, -1, 1, -3, -2, -1]
-resign	-1.4	0.66332	[-2, -1, -3, -1, -1, -1, -1, -2, -1, -1]
-resignation	-1.2	0.4	[-1, -1, -1, -2, -1, -1, -1, -1, -2, -1]
-resignations	-1.2	0.6	[0, -1, -1, -2, -2, -2, -1, -1, -1, -1]
-resigned	-1.0	0.63246	[-2, -1, 0, -1, -2, -1, -1, -1, 0, -1]
-resignedly	-0.7	1.26886	[-3, -1, -1, -1, -1, 1, 1, 1, -2, -1]
-resignedness	-0.8	1.07703	[-1, -2, 1, -2, -1, -1, 0, -2, -1, 1]
-resigner	-1.2	0.6	[-2, -1, 0, -1, -2, -2, -1, -1, -1, -1]
-resigners	-1.0	1.09545	[-1, 0, -1, -3, -1, 0, 0, -1, -3, 0]
-resigning	-0.9	1.22066	[-1, -1, -1, -1, -1, 0, -1, -3, -2, 2]
-resigns	-1.3	0.9	[0, -1, -1, 0, -2, -1, -3, -1, -2, -2]
-resolute	1.1	0.53852	[2, 1, 0, 1, 1, 1, 2, 1, 1, 1]
-resolvable	1.0	0.0	[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
-resolve	1.6	0.66332	[2, 1, 1, 2, 2, 1, 3, 1, 1, 2]
-resolved	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
-resolvent	0.7	0.78102	[1, 0, 1, 2, 0, -1, 1, 1, 1, 1]
-resolvents	0.4	0.66332	[2, 0, 0, 1, 0, 0, 1, 0, 0, 0]
-resolver	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
-resolvers	1.4	0.4899	[2, 1, 2, 1, 1, 1, 2, 1, 2, 1]
-resolves	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
-resolving	1.6	0.4899	[2, 2, 1, 2, 2, 1, 1, 1, 2, 2]
-respect	2.1	0.53852	[2, 2, 2, 2, 3, 3, 2, 2, 1, 2]
-respectabilities	1.8	0.4	[2, 2, 2, 1, 2, 2, 2, 1, 2, 2]
-respectability	2.4	0.8	[4, 1, 3, 2, 3, 3, 2, 2, 2, 2]
-respectable	1.9	0.7	[2, 2, 2, 2, 1, 3, 3, 1, 1, 2]
-respectableness	1.2	1.32665	[2, 1, 1, 0, 3, 2, -2, 2, 2, 1]
-respectably	1.7	0.78102	[2, 2, 1, 3, 1, 3, 2, 1, 1, 1]
-respected	2.1	0.7	[2, 2, 1, 2, 3, 1, 2, 3, 3, 2]
-respecter	2.1	0.53852	[3, 2, 2, 2, 2, 2, 1, 3, 2, 2]
-respecters	1.6	0.8	[2, 1, 2, 2, 3, 1, 2, 2, 0, 1]
-respectful	2.0	0.7746	[1, 1, 3, 2, 2, 3, 1, 2, 3, 2]
-respectfully	1.7	0.64031	[1, 2, 1, 2, 2, 2, 1, 3, 1, 2]
-respectfulness	1.9	1.37477	[4, 2, 2, 1, 2, 4, -1, 1, 2, 2]
-respectfulnesses	1.3	1.18743	[1, 1, 2, 2, 2, 2, 2, 1, -2, 2]
-respecting	2.2	0.6	[1, 3, 2, 3, 2, 2, 3, 2, 2, 2]
-respective	1.8	1.16619	[2, 2, 3, 0, 1, 3, 3, 1, 0, 3]
-respectively	1.4	0.91652	[0, 0, 2, 2, 0, 2, 2, 2, 2, 2]
-respectiveness	1.1	1.04403	[0, 2, 1, 0, 1, 0, 2, 2, 0, 3]
-respects	1.3	1.00499	[2, 0, 0, 0, 2, 1, 2, 1, 2, 3]
-responsible	1.3	1.1	[1, 1, 0, 4, 2, 2, 1, 0, 1, 1]
-responsive	1.5	0.92195	[3, 1, 1, 0, 1, 1, 2, 3, 2, 1]
-restful	1.5	0.67082	[1, 1, 1, 1, 2, 1, 2, 1, 2, 3]
-restless	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -1]
-restlessly	-1.4	0.91652	[-1, -4, -1, -1, -1, -2, -1, -1, -1, -1]
-restlessness	-1.2	0.74833	[-3, -1, -1, 0, -1, -2, -1, -1, -1, -1]
-restore	1.2	0.9798	[1, 1, 2, 2, 2, 2, 1, -1, 0, 2]
-restored	1.4	0.91652	[2, 2, 1, 2, 1, 2, 2, 1, -1, 2]
-restores	1.2	0.6	[2, 1, 1, 2, 1, 0, 1, 1, 2, 1]
-restoring	1.2	0.4	[2, 1, 1, 1, 1, 2, 1, 1, 1, 1]
-restrict	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -2, -1, -1, -2]
-restricted	-1.6	0.4899	[-1, -2, -1, -1, -1, -2, -2, -2, -2, -2]
-restricting	-1.6	0.4899	[-2, -2, -2, -2, -1, -2, -1, -1, -2, -1]
-restriction	-1.1	0.9434	[-1, -1, -1, -1, -3, 1, -2, -1, -1, -1]
-restricts	-1.3	1.1	[-2, -2, -3, -1, -1, -2, 1, -1, -2, 0]
-retained	0.1	0.7	[-1, 1, 1, 1, 0, -1, 0, 0, 0, 0]
-retard	-2.4	0.8	[-2, -2, -2, -1, -3, -2, -4, -3, -3, -2]
-retarded	-2.7	1.26886	[-4, -1, -3, -3, -4, -4, -2, -1, -1, -4]
-retreat	0.8	1.07703	[2, 2, 0, 0, -1, 1, 2, 0, 2, 0]
-revenge	-2.4	0.66332	[-2, -3, -2, -3, -3, -3, -2, -1, -2, -3]
-revenged	-0.9	1.37477	[-2, -3, -2, -1, -1, 2, -1, 1, -1, -1]
-revengeful	-2.4	0.4899	[-2, -2, -2, -3, -3, -2, -3, -3, -2, -2]
-revengefully	-1.4	2.00998	[-3, -2, -2, -2, 3, 2, -3, -3, -2, -2]
-revengefulness	-2.2	0.87178	[-2, -3, -3, -2, -2, -2, -1, -4, -1, -2]
-revenger	-2.1	0.83066	[-2, -3, -2, -1, -1, -2, -3, -3, -1, -3]
-revengers	-2.0	0.44721	[-2, -2, -3, -2, -2, -2, -1, -2, -2, -2]
-revenges	-1.9	0.7	[-2, -3, -2, -1, -1, -2, -3, -2, -1, -2]
-revered	2.3	1.1	[3, 3, 1, 3, 3, 3, 0, 3, 3, 1]
-revive	1.4	1.11355	[4, 0, 2, 1, 1, 0, 2, 2, 1, 1]
-revives	1.6	0.4899	[1, 1, 2, 2, 1, 2, 2, 2, 1, 2]
-reward	2.7	0.78102	[3, 4, 1, 2, 3, 3, 2, 3, 3, 3]
-rewardable	2.0	1.0	[3, 1, 4, 3, 1, 2, 1, 2, 2, 1]
-rewarded	2.2	0.74833	[1, 2, 3, 2, 2, 4, 2, 2, 2, 2]
-rewarder	1.6	0.8	[1, 2, 3, 1, 1, 3, 2, 1, 1, 1]
-rewarders	1.9	0.83066	[1, 2, 2, 1, 3, 3, 1, 2, 1, 3]
-rewarding	2.4	0.8	[3, 4, 2, 2, 1, 3, 3, 2, 2, 2]
-rewardingly	2.4	0.8	[3, 2, 3, 4, 3, 2, 2, 2, 1, 2]
-rewards	2.1	0.83066	[2, 1, 3, 4, 2, 2, 2, 2, 1, 2]
-rich	2.6	0.8	[2, 3, 2, 4, 4, 3, 2, 2, 2, 2]
-richened	1.9	0.83066	[3, 2, 2, 1, 3, 1, 2, 3, 1, 1]
-richening	1.0	1.34164	[2, 2, 0, 0, -1, 1, 2, 3, -1, 2]
-richens	0.8	0.9798	[1, 0, 3, 0, 0, 0, 1, 2, 1, 0]
-richer	2.4	1.2	[1, 4, 2, 1, 2, 4, 4, 1, 3, 2]
-riches	2.4	1.0198	[2, 4, 1, 1, 2, 4, 3, 2, 3, 2]
-richest	2.4	1.11355	[4, 4, 2, 2, 3, 0, 2, 2, 3, 2]
-richly	1.9	0.53852	[2, 2, 2, 2, 3, 1, 2, 2, 1, 2]
-richness	2.2	0.74833	[2, 3, 2, 2, 2, 2, 2, 1, 4, 2]
-richnesses	2.1	0.9434	[2, 1, 2, 2, 3, 1, 3, 1, 4, 2]
-richweed	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
-richweeds	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
-ridicule	-2.0	0.63246	[-2, -2, -2, -2, -3, -2, -1, -2, -1, -3]
-ridiculed	-1.5	0.5	[-1, -1, -1, -2, -2, -2, -1, -2, -1, -2]
-ridiculer	-1.6	0.91652	[-1, -1, -1, -2, -2, 0, -1, -3, -2, -3]
-ridiculers	-1.6	0.66332	[-2, -1, -1, -2, -3, -2, -1, -2, -1, -1]
-ridicules	-1.8	0.6	[-1, -1, -2, -2, -2, -2, -1, -2, -2, -3]
-ridiculing	-1.8	0.6	[-2, -3, -2, -1, -1, -2, -2, -1, -2, -2]
-ridiculous	-1.5	0.67082	[-3, -2, -1, -1, -2, -1, -2, -1, -1, -1]
-ridiculously	-1.4	0.8	[-1, -2, -1, 0, -2, -1, -1, -3, -1, -2]
-ridiculousness	-1.1	1.51327	[-1, -1, -1, -2, -1, 3, -3, -2, -1, -2]
-ridiculousnesses	-1.6	1.11355	[-3, 0, -2, -2, -1, -1, -1, -4, -1, -1]
-rig	-0.5	1.0247	[0, 0, 0, 0, -2, 0, 0, 0, -3, 0]
-rigged	-1.5	1.0247	[-2, -3, -2, -1, -1, -2, 1, -1, -2, -2]
-rigid	-0.5	0.67082	[-2, -1, 0, 0, 0, 0, 0, -1, -1, 0]
-rigidification	-1.1	0.9434	[-1, -2, 0, 0, 0, -2, -2, -2, 0, -2]
-rigidifications	-0.8	0.9798	[-2, -1, 0, 0, -2, -1, 0, 1, -2, -1]
-rigidified	-0.7	1.00499	[0, -1, 0, 0, 0, 0, -2, 0, -1, -3]
-rigidifies	-0.6	0.8	[0, -1, 0, 0, 0, 0, -2, 0, -1, -2]
-rigidify	-0.3	0.64031	[0, 0, 0, 0, -1, 0, 0, 0, -2, 0]
-rigidities	-0.7	0.78102	[0, -1, 0, 0, 0, 0, -2, -1, -1, -2]
-rigidity	-0.7	0.64031	[-1, 0, -1, 0, -1, 0, -2, 0, -1, -1]
-rigidly	-0.7	0.45826	[-1, -1, -1, -1, 0, 0, -1, 0, -1, -1]
-rigidness	-0.3	1.00499	[0, -1, -1, 0, 2, -1, -1, -1, 1, -1]
-rigorous	-1.1	1.51327	[-2, -3, 1, 0, 1, 0, -1, -1, -3, -3]
-rigorously	-0.4	1.28062	[0, 2, 1, 0, -1, 0, -1, -1, -3, -1]
-riot	-2.6	1.0198	[-3, 0, -3, -2, -3, -3, -3, -4, -3, -2]
-riots	-2.3	0.78102	[-2, -3, -3, -2, -1, -1, -3, -2, -3, -3]
-risk	-1.1	0.7	[-1, -1, 0, -2, -1, 0, -2, -2, -1, -1]
-risked	-0.9	0.7	[-1, -2, 0, 0, -1, 0, -2, -1, -1, -1]
-risker	-0.8	0.4	[-1, -1, -1, 0, -1, 0, -1, -1, -1, -1]
-riskier	-1.4	0.91652	[0, -3, -1, 0, -1, -2, -1, -2, -2, -2]
-riskiest	-1.5	1.0247	[-2, -3, -1, -1, -3, 0, -1, -2, 0, -2]
-riskily	-0.7	1.34536	[-1, -2, -1, -1, 3, 0, -1, -1, -1, -2]
-riskiness	-1.3	1.00499	[-3, -1, -1, 0, -1, 0, -1, -3, -2, -1]
-riskinesses	-1.6	0.91652	[-2, -1, -1, 0, -3, -1, -2, -1, -3, -2]
-risking	-1.3	1.1	[0, 0, -2, 0, -1, -3, -3, -1, -2, -1]
-riskless	1.3	0.9	[2, 1, 0, 1, 1, 1, 2, 3, 0, 2]
-risks	-1.1	0.9434	[-1, 0, -1, -1, 0, 0, -2, -1, -3, -2]
-risky	-0.8	0.9798	[-1, 1, -1, -1, -1, 0, 0, -1, -3, -1]
-rob	-2.6	0.8	[-2, -4, -3, -2, -3, -4, -2, -2, -2, -2]
-robber	-2.6	1.0198	[-4, -1, -2, -3, -2, -1, -4, -3, -3, -3]
-robed	-0.7	0.9	[-2, 0, 0, 0, 0, -2, 0, -2, -1, 0]
-robing	-1.5	1.56525	[0, 0, 0, 0, -2, -3, -3, -4, -3, 0]
-robs	-2.0	1.0	[-2, -1, -3, -2, -2, -1, -4, -3, -1, -1]
-robust	1.4	1.42829	[1, 0, 0, 1, 4, 0, 2, 3, 3, 0]
-roflcopter	2.1	0.53852	[2, 2, 2, 1, 3, 2, 3, 2, 2, 2]
-romance	2.6	0.66332	[2, 3, 4, 2, 3, 2, 3, 2, 3, 2]
-romanced	2.2	0.87178	[2, 3, 2, 4, 2, 1, 2, 3, 1, 2]
-romancer	1.3	1.1	[0, 0, 2, 2, 2, 2, 3, 2, 0, 0]
-romancers	1.7	1.00499	[0, 2, 2, 2, 2, 2, 1, 3, 0, 3]
-romances	1.3	0.9	[0, 1, 2, 2, 2, 2, 2, 2, 0, 0]
-romancing	2.0	0.89443	[4, 1, 1, 2, 2, 2, 2, 1, 3, 2]
-romantic	1.7	0.78102	[2, 2, 2, 1, 2, 3, 2, 2, 0, 1]
-romantically	1.8	0.87178	[3, 1, 2, 0, 1, 2, 2, 2, 3, 2]
-romanticise	1.7	1.61555	[-1, 4, 2, 1, 3, 1, 3, 3, 2, -1]
-romanticised	1.7	0.9	[2, 2, 2, 2, 2, 2, 3, 0, 2, 0]
-romanticises	1.3	1.1	[2, 2, 1, 1, 1, 2, 3, -1, 2, 0]
-romanticising	2.7	0.78102	[3, 3, 3, 2, 1, 3, 2, 3, 4, 3]
-romanticism	2.2	1.32665	[1, 4, 2, 1, 3, 1, 3, 3, 4, 0]
-romanticisms	2.1	0.9434	[2, 3, 2, 1, 2, 3, 3, 2, 3, 0]
-romanticist	1.9	1.3	[1, 4, 2, 0, 3, 1, 2, 3, 3, 0]
-romanticists	1.3	1.00499	[2, 0, 0, 1, 3, 3, 1, 1, 1, 1]
-romanticization	1.5	1.36015	[1, 3, 2, 2, -1, 2, 0, 1, 4, 1]
-romanticizations	2.0	1.0	[4, 1, 3, 1, 2, 3, 1, 2, 2, 1]
-romanticize	1.8	0.9798	[2, 2, 1, 1, 2, 1, 3, 3, 3, 0]
-romanticized	0.9	1.22066	[0, 1, 1, 3, -1, 0, 1, 1, 3, 0]
-romanticizes	1.8	0.87178	[2, 3, 2, 1, 2, 3, 0, 1, 2, 2]
-romanticizing	1.2	1.07703	[0, 1, 2, 1, 3, 0, 1, 1, 0, 3]
-romantics	1.9	0.83066	[2, 3, 2, 1, 0, 2, 3, 2, 2, 2]
-rotten	-2.3	0.78102	[-2, -3, -1, -3, -3, -1, -3, -2, -3, -2]
-rude	-2.0	0.44721	[-2, -1, -3, -2, -2, -2, -2, -2, -2, -2]
-rudely	-2.2	0.87178	[-3, -2, -3, -1, -2, -4, -2, -2, -1, -2]
-rudeness	-1.5	0.67082	[-2, -1, -1, -1, -1, -3, -2, -2, -1, -1]
-ruder	-2.1	0.83066	[-2, -1, -4, -2, -3, -1, -2, -2, -2, -2]
-ruderal	-0.8	1.46969	[-3, 0, -1, -2, 0, -1, -3, 0, 2, 0]
-ruderals	-0.4	0.66332	[0, -1, 0, -2, 0, -1, 0, 0, 0, 0]
-rudesby	-2.0	0.7746	[-2, -3, -2, -2, -1, -3, -1, -1, -2, -3]
-rudest	-2.5	0.5	[-3, -2, -3, -3, -2, -2, -2, -3, -2, -3]
-ruin	-2.8	0.87178	[-3, -3, -1, -4, -4, -3, -3, -2, -2, -3]
-ruinable	-1.6	0.8	[-1, -2, -1, -3, -1, -3, -1, -1, -2, -1]
-ruinate	-2.8	0.87178	[-4, -4, -3, -3, -1, -3, -3, -3, -2, -2]
-ruinated	-1.5	1.56525	[0, -4, 0, -4, -1, -2, 0, -1, -3, 0]
-ruinates	-1.5	1.56525	[0, -4, 0, -4, -1, -2, 0, -1, -3, 0]
-ruinating	-1.5	1.20416	[-2, -2, -2, -3, 0, -1, 1, -3, -1, -2]
-ruination	-2.7	1.00499	[-4, -4, -3, -3, -2, -1, -3, -3, -3, -1]
-ruinations	-1.6	1.35647	[-2, -2, -3, -4, 0, -1, 1, -2, -1, -2]
-ruined	-2.1	0.7	[-3, -2, -2, -1, -2, -2, -3, -3, -1, -2]
-ruiner	-2.0	0.63246	[-1, -3, -2, -2, -1, -2, -3, -2, -2, -2]
-ruing	-1.6	0.91652	[-2, -1, -2, -1, -1, -1, -3, 0, -3, -2]
-ruining	-1.0	1.94936	[-3, -3, 0, -2, 1, -3, 2, -2, 2, -2]
-ruinous	-2.7	0.78102	[-2, -3, -3, -3, -3, -4, -2, -3, -1, -3]
-ruinously	-2.6	0.8	[-3, -2, -2, -3, -1, -3, -4, -2, -3, -3]
-ruinousness	-1.0	1.09545	[-1, -2, -3, -1, -1, -2, 1, 0, -1, 0]
-ruins	-1.9	0.9434	[-1, -2, -1, -2, -1, -2, -4, -1, -3, -2]
-sabotage	-2.4	0.91652	[-3, -3, -3, -2, -2, -4, -2, -3, -1, -1]
-sad	-2.1	0.9434	[-1, -1, -2, -2, -3, -2, -3, -2, -4, -1]
-sadden	-2.6	0.4899	[-2, -3, -2, -3, -2, -3, -2, -3, -3, -3]
-saddened	-2.4	0.4899	[-3, -2, -3, -2, -3, -3, -2, -2, -2, -2]
-saddening	-2.2	0.4	[-3, -2, -2, -2, -2, -2, -3, -2, -2, -2]
-saddens	-1.9	0.7	[-3, -1, -1, -1, -2, -2, -2, -2, -3, -2]
-sadder	-2.4	0.91652	[-2, -2, -3, -4, -3, -1, -3, -1, -2, -3]
-saddest	-3.0	0.63246	[-4, -3, -2, -3, -3, -2, -3, -4, -3, -3]
-sadly	-1.8	0.6	[-2, -2, -2, -1, -2, -3, -2, -1, -1, -2]
-sadness	-1.9	0.3	[-2, -1, -2, -2, -2, -2, -2, -2, -2, -2]
-safe	1.9	0.3	[2, 1, 2, 2, 2, 2, 2, 2, 2, 2]
-safecracker	-0.7	1.61555	[-3, -2, 0, -3, 0, -2, 0, 1, 2, 0]
-safecrackers	-0.9	1.04403	[-1, 0, -2, 0, -1, 0, 0, -3, 0, -2]
-safecracking	-0.9	0.9434	[0, 0, 0, 0, -2, 0, -1, -2, -2, -2]
-safecrackings	-0.7	1.67631	[-2, -1, -2, -4, 2, -1, -1, 0, 1, 1]
-safeguard	1.6	0.4899	[2, 2, 1, 1, 1, 2, 2, 2, 2, 1]
-safeguarded	1.5	0.92195	[1, 2, 2, 0, 2, 0, 3, 1, 2, 2]
-safeguarding	1.1	0.7	[2, 1, 1, 0, 1, 0, 2, 1, 1, 2]
-safeguards	1.4	0.66332	[1, 2, 1, 1, 0, 2, 2, 2, 2, 1]
-safekeeping	1.4	0.66332	[3, 1, 1, 2, 1, 1, 2, 1, 1, 1]
-safelight	1.1	1.22066	[0, 3, 0, 2, 0, 3, 0, 2, 1, 0]
-safelights	0.8	1.07703	[0, 3, 1, 0, 0, 2, 0, 2, 0, 0]
-safely	2.2	0.74833	[2, 2, 2, 3, 4, 2, 2, 1, 2, 2]
-safeness	1.5	0.67082	[1, 1, 1, 1, 3, 1, 2, 2, 2, 1]
-safer	1.8	0.6	[2, 1, 2, 3, 2, 2, 1, 1, 2, 2]
-safes	0.4	0.8	[0, 0, 2, 0, 0, 0, 0, 0, 2, 0]
-safest	1.7	1.61555	[2, 2, 2, 2, -3, 3, 3, 2, 2, 2]
-safeties	1.5	1.0247	[2, 0, 1, 3, 2, 1, 3, 1, 0, 2]
-safety	1.8	0.6	[2, 2, 2, 2, 1, 1, 2, 3, 1, 2]
-safetyman	0.3	0.64031	[0, 0, 0, 0, 2, 0, 1, 0, 0, 0]
-salient	1.1	1.22066	[1, 3, 0, -1, 0, 1, 2, 1, 1, 3]
-sappy	-1.0	1.18322	[-2, -1, 2, -2, -2, 0, -1, -1, -2, -1]
-sarcasm	-0.9	0.7	[0, -2, -1, -1, 0, 0, -1, -1, -2, -1]
-sarcasms	-0.9	0.7	[0, -1, 0, -1, -1, -2, 0, -1, -1, -2]
-sarcastic	-1.0	0.7746	[-1, -1, -1, -1, -1, -1, -1, -2, 1, -2]
-sarcastically	-1.1	1.37477	[-1, -4, 1, -1, -1, -2, 1, -2, -1, -1]
-satisfaction	1.9	0.9434	[1, 3, 2, 4, 2, 1, 1, 1, 2, 2]
-satisfactions	2.1	0.7	[3, 3, 3, 1, 2, 2, 1, 2, 2, 2]
-satisfactorily	1.6	1.11355	[1, 2, 2, -1, 2, 1, 3, 3, 1, 2]
-satisfactoriness	1.5	0.5	[1, 2, 1, 2, 2, 1, 2, 1, 2, 1]
-satisfactory	1.5	0.67082	[2, 3, 1, 1, 1, 2, 2, 1, 1, 1]
-satisfiable	1.9	0.83066	[3, 1, 2, 1, 2, 3, 1, 2, 3, 1]
-satisfied	1.8	0.6	[2, 2, 2, 1, 1, 2, 3, 1, 2, 2]
-satisfies	1.8	0.6	[3, 1, 2, 1, 1, 2, 2, 2, 2, 2]
-satisfy	2.0	0.63246	[3, 2, 2, 2, 2, 1, 1, 2, 3, 2]
-satisfying	2.0	1.48324	[2, 3, 2, 1, 3, 3, 3, 2, -2, 3]
-satisfyingly	1.9	0.9434	[1, 2, 2, 1, 2, 1, 4, 1, 3, 2]
-savage	-2.0	1.73205	[-3, -4, -3, 1, -2, -1, -3, -4, -2, 1]
-savaged	-2.0	1.34164	[-1, 0, -4, -3, -3, -3, -2, 0, -1, -3]
-savagely	-2.2	0.74833	[-2, -1, -3, -2, -2, -1, -2, -3, -3, -3]
-savageness	-2.6	1.0198	[-3, -1, -2, -3, -2, -1, -4, -4, -3, -3]
-savagenesses	-0.9	1.86815	[-2, 3, -1, -3, -2, 2, -3, -1, -1, -1]
-savageries	-1.9	1.75784	[-3, 1, -3, -4, -3, 1, -2, -3, 0, -3]
-savagery	-2.5	1.62788	[-2, -3, -3, -3, 2, -3, -3, -4, -4, -2]
-savages	-2.4	1.0198	[-2, -2, -3, -4, -3, -3, -2, 0, -2, -3]
-save	2.2	1.16619	[1, 3, 3, 1, 2, 1, 2, 4, 1, 4]
-saved	1.8	0.6	[1, 2, 2, 2, 1, 3, 2, 2, 1, 2]
-scam	-2.7	0.64031	[-2, -3, -3, -3, -2, -2, -4, -3, -3, -2]
-scams	-2.8	0.87178	[-3, -1, -3, -4, -4, -3, -2, -2, -3, -3]
-scandal	-1.9	1.81384	[-3, -2, -2, -4, 3, -3, -3, -1, -2, -2]
-scandalous	-2.4	0.8	[-2, -1, -3, -2, -4, -2, -3, -3, -2, -2]
-scandals	-2.2	0.9798	[-2, -3, -3, -2, -1, 0, -3, -3, -2, -3]
-scapegoat	-1.7	0.64031	[-3, -2, -2, -2, -1, -1, -1, -2, -1, -2]
-scapegoats	-1.4	0.8	[-1, -2, -2, -1, 0, -2, -2, 0, -2, -2]
-scare	-2.2	0.87178	[-2, -2, -4, -2, -3, -1, -2, -1, -2, -3]
-scarecrow	-0.8	0.9798	[-1, 0, -1, 0, 0, 0, -2, -3, -1, 0]
-scarecrows	-0.7	1.1	[2, 0, -1, -1, -1, -2, -1, -2, 0, -1]
-scared	-1.9	0.7	[-1, -1, -2, -3, -2, -3, -1, -2, -2, -2]
-scaremonger	-2.1	0.53852	[-1, -2, -2, -3, -2, -2, -3, -2, -2, -2]
-scaremongers	-2.0	1.0	[-2, -2, 0, -4, -2, -2, -1, -2, -3, -2]
-scarer	-1.7	0.78102	[-2, -1, -1, -2, -3, -1, -3, -1, -2, -1]
-scarers	-1.3	0.9	[-1, -2, -1, 0, 0, -1, -3, -2, -1, -2]
-scares	-1.4	0.4899	[-1, -1, -2, -1, -1, -2, -1, -2, -2, -1]
-scarey	-1.7	0.64031	[-1, -1, -2, -2, -1, -2, -1, -2, -3, -2]
-scaring	-1.9	1.22066	[-3, -2, -1, -3, -1, -3, -2, -2, 1, -3]
-scary	-2.2	0.87178	[-2, -1, -4, -3, -3, -2, -2, -2, -2, -1]
-sceptic	-1.0	0.89443	[-3, 0, -1, -1, -1, 0, 0, -2, -1, -1]
-sceptical	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-scepticism	-0.8	0.87178	[-1, -2, -2, 0, 0, -1, 1, -1, -1, -1]
-sceptics	-0.7	0.78102	[0, 0, 0, -1, -2, 0, -1, -1, 0, -2]
-scold	-1.7	0.78102	[-2, -1, -1, -1, -3, -3, -2, -2, -1, -1]
-scoop	0.6	0.8	[0, 0, 1, 0, 2, 0, 2, 0, 1, 0]
-scorn	-1.7	0.64031	[-2, -3, -2, -1, -1, -1, -1, -2, -2, -2]
-scornful	-1.8	1.16619	[-3, -3, -2, -1, -4, 0, -2, -1, -1, -1]
-scream	-1.7	0.78102	[0, -3, -1, -1, -2, -2, -2, -2, -2, -2]
-screamed	-1.3	1.1	[-2, -3, -2, -1, -1, -2, -2, -1, 1, 0]
-screamers	-1.5	0.92195	[-2, -1, -2, -2, -2, -2, -1, -2, 1, -2]
-screaming	-1.6	0.8	[0, -1, -1, -2, -3, -1, -2, -2, -2, -2]
-screams	-1.2	0.9798	[-1, -2, -2, -1, -1, -2, 1, -2, 0, -2]
-screw	-0.4	0.91652	[-1, -2, -1, 0, 0, 1, 0, -1, 1, -1]
-screwball	-0.2	0.87178	[0, -1, 0, 0, 1, 1, -1, 0, -2, 0]
-screwballs	-0.3	1.00499	[-2, 0, -2, -1, 0, 1, 0, 1, 0, 0]
-screwbean	0.3	0.64031	[0, 0, 0, 0, 0, 1, 0, 2, 0, 0]
-screwdriver	0.3	0.45826	[1, 0, 0, 0, 0, 1, 0, 0, 1, 0]
-screwdrivers	0.1	0.53852	[-1, 0, 0, 1, 0, 0, 0, 1, 0, 0]
-screwed	-2.2	0.4	[-2, -2, -2, -2, -2, -3, -3, -2, -2, -2]
-screwed up	-1.5	0.67082	[-2, -2, -2, -1, -1, 0, -2, -1, -2, -2]
-screwer	-1.2	0.87178	[-1, -2, -1, -2, 0, 0, -2, 0, -2, -2]
-screwers	-0.5	1.5	[-2, -2, 0, -2, 0, 2, 2, -1, 0, -2]
-screwier	-0.6	1.2	[0, -1, 2, -2, -1, -2, -1, -1, 1, -1]
-screwiest	-2.0	0.89443	[-3, -2, -2, -4, -1, -2, -1, -1, -2, -2]
-screwiness	-0.5	1.80278	[-2, 0, -2, 3, -2, -1, -2, 1, 2, -2]
-screwing	-0.9	0.9434	[-1, 0, 0, 0, -1, -1, -3, -2, 0, -1]
-screwlike	0.1	1.04403	[2, -1, 0, 0, 0, 1, 0, 1, -2, 0]
-screws	-1.0	1.09545	[0, -3, 0, 0, -1, 0, -2, -2, -2, 0]
-screwup	-1.7	0.9	[-2, -2, -2, 1, -2, -2, -2, -2, -2, -2]
-screwups	-1.0	1.61245	[-2, -2, -2, -2, 0, 2, -2, -2, 2, -2]
-screwworm	-0.4	0.66332	[0, -1, 0, 0, 0, 0, -2, 0, -1, 0]
-screwworms	-0.1	1.22066	[-3, 0, -1, 0, 0, 0, 0, 2, 1, 0]
-screwy	-1.4	0.8	[-2, -2, -1, -1, -1, 0, -2, -1, -3, -1]
-scrumptious	2.1	1.22066	[3, 3, 0, 3, 2, 3, 1, 3, 0, 3]
-scrumptiously	1.5	1.43178	[2, 3, 3, -2, 1, 1, 2, 3, 1, 1]
-scumbag	-3.2	0.6	[-4, -3, -3, -2, -3, -4, -3, -3, -4, -3]
-secure	1.4	0.4899	[1, 2, 1, 1, 2, 1, 1, 2, 2, 1]
-secured	1.7	0.78102	[2, 2, 3, 1, 1, 2, 2, 0, 2, 2]
-securely	1.4	0.8	[2, 0, 1, 2, 1, 1, 1, 3, 2, 1]
-securement	1.1	0.7	[0, 2, 1, 1, 1, 0, 2, 2, 1, 1]
-secureness	1.4	0.66332	[2, 1, 1, 3, 1, 1, 1, 1, 2, 1]
-securer	1.5	0.67082	[1, 2, 2, 2, 1, 2, 1, 0, 2, 2]
-securers	0.6	0.91652	[1, 3, 0, 0, 1, 0, 0, 0, 0, 1]
-secures	1.3	0.64031	[1, 2, 2, 1, 1, 2, 1, 0, 2, 1]
-securest	2.6	0.8	[3, 3, 2, 3, 1, 4, 3, 2, 2, 3]
-securing	1.3	1.00499	[0, 3, 1, 1, 1, 3, 1, 1, 2, 0]
-securities	1.2	0.6	[1, 2, 2, 2, 1, 1, 1, 0, 1, 1]
-securitization	0.2	1.07703	[0, 0, 1, -1, 1, 0, -2, 0, 2, 1]
-securitizations	0.1	0.9434	[0, 0, 0, 0, 2, 0, -2, 0, 1, 0]
-securitize	0.3	1.34536	[2, 1, 0, 0, 2, 0, 1, 0, -3, 0]
-securitized	1.4	1.0198	[3, 0, 2, 2, 0, 1, 2, 2, 0, 2]
-securitizes	1.6	1.0198	[3, 0, 2, 2, 0, 1, 3, 2, 1, 2]
-securitizing	0.7	0.9	[2, 0, 0, 1, 2, 0, 2, 0, 0, 0]
-security	1.4	0.8	[1, 2, 3, 2, 1, 1, 2, 0, 1, 1]
-sedition	-1.8	1.249	[-3, -4, -2, -2, -2, -2, -1, -1, -2, 1]
-seditious	-1.7	0.64031	[-1, -2, -2, -1, -1, -1, -3, -2, -2, -2]
-seduced	-1.5	0.67082	[0, -1, -2, -2, -2, -2, -1, -1, -2, -2]
-self-confident	2.5	0.80623	[1, 3, 3, 3, 2, 3, 1, 3, 3, 3]
-selfish	-2.1	0.7	[-1, -2, -2, -3, -1, -2, -2, -2, -3, -3]
-selfishly	-1.4	0.91652	[-3, 0, -1, -1, -1, -2, -3, -1, -1, -1]
-selfishness	-1.7	0.64031	[-1, -1, -1, -2, -2, -1, -2, -2, -3, -2]
-selfishnesses	-2.0	1.94936	[-4, -3, -1, -3, -2, -4, 2, 1, -3, -3]
-sentence	0.3	0.64031	[0, 0, 0, 0, 1, 2, 0, 0, 0, 0]
-sentenced	-0.1	1.3	[0, -2, 2, -1, 0, -2, 2, 0, 0, 0]
-sentences	0.2	1.07703	[0, 0, 2, 0, 0, -2, 2, 0, 0, 0]
-sentencing	-0.6	1.8	[-2, 0, -3, -2, 2, 3, 0, -1, -1, -2]
-sentimental	1.3	0.64031	[2, 1, 1, 2, 1, 0, 1, 2, 2, 1]
-sentimentalise	1.2	0.87178	[2, 1, 0, 3, 2, 1, 1, 0, 1, 1]
-sentimentalised	0.8	1.16619	[2, 1, 1, 0, 0, 2, 3, -1, 0, 0]
-sentimentalising	0.4	0.91652	[0, 2, 0, 0, 0, -1, 1, 0, 2, 0]
-sentimentalism	1.0	0.63246	[2, 1, 0, 2, 1, 1, 1, 0, 1, 1]
-sentimentalisms	0.4	0.8	[0, 1, 1, 0, 0, 2, 1, 0, 0, -1]
-sentimentalist	0.8	0.87178	[2, 1, 0, 2, 0, 1, 2, 0, 0, 0]
-sentimentalists	0.7	0.78102	[0, 0, 1, 0, 0, 1, 1, 2, 0, 2]
-sentimentalities	0.9	0.83066	[2, 1, 1, 2, 1, 0, 0, 2, 0, 0]
-sentimentality	1.2	1.46969	[-2, 1, 1, 2, 2, 0, 4, 2, 1, 1]
-sentimentalization	1.2	0.87178	[0, 1, 2, 0, 1, 1, 3, 1, 2, 1]
-sentimentalizations	0.4	0.8	[0, 1, 0, 1, 0, 0, 0, 2, -1, 1]
-sentimentalize	0.8	1.07703	[2, 0, 0, 2, 0, 2, 1, -1, 2, 0]
-sentimentalized	1.1	1.22066	[3, 0, 2, 0, 1, 3, 2, 0, 0, 0]
-sentimentalizes	1.1	1.37477	[3, 0, 1, 0, 1, 4, 2, 0, 0, 0]
-sentimentalizing	0.8	0.87178	[1, 1, 1, 1, 2, 0, -1, 1, 0, 2]
-sentimentally	1.9	0.9434	[3, 2, 3, 1, 0, 2, 1, 2, 3, 2]
-serene	2.0	1.0	[1, 1, 3, 2, 2, 4, 3, 2, 1, 1]
-serious	-0.3	0.45826	[0, -1, 0, -1, -1, 0, 0, 0, 0, 0]
-seriously	-0.7	1.34536	[-3, -2, 0, 0, -1, -2, 2, -1, 0, 0]
-seriousness	-0.2	1.16619	[0, 2, 0, 0, 0, 0, -3, -1, 0, 0]
-severe	-1.6	1.8	[-3, -2, -4, 1, -2, -3, 2, -1, -1, -3]
-severed	-1.5	0.5	[-1, -1, -2, -1, -2, -1, -1, -2, -2, -2]
-severely	-2.0	0.89443	[-2, -1, -1, -2, -2, -1, -3, -2, -4, -2]
-severeness	-1.0	1.73205	[0, 0, -1, -4, 1, -2, 0, 1, -1, -4]
-severer	-1.6	1.49666	[-2, -3, -2, -1, -2, 2, -4, -1, -1, -2]
-severest	-1.5	1.85742	[-4, -1, 2, -2, -2, -3, -4, -1, 1, -1]
-sexy	2.4	0.8	[2, 3, 3, 4, 2, 2, 2, 2, 3, 1]
-shake	-0.7	0.9	[-2, 0, 0, -2, 1, -1, 0, -1, -1, -1]
-shakeable	-0.3	1.00499	[2, -1, 0, 0, -1, -2, 0, 0, -1, 0]
-shakedown	-1.2	0.4	[-2, -1, -1, -1, -2, -1, -1, -1, -1, -1]
-shakedowns	-1.4	0.8	[-2, -1, -1, -3, -1, -1, 0, -2, -2, -1]
-shaken	-0.3	0.9	[-1, -1, 1, -1, 1, 0, -1, 1, -1, -1]
-shakeout	-1.3	0.78102	[-1, -2, 0, -1, -1, -2, -2, -2, 0, -2]
-shakeouts	-0.8	1.16619	[-2, -1, 0, 0, -1, 2, -2, -1, -2, -1]
-shakers	0.3	1.00499	[2, 0, 0, -1, 2, 0, 1, -1, 0, 0]
-shakeup	-0.6	0.4899	[-1, 0, -1, -1, -1, 0, 0, 0, -1, -1]
-shakeups	-0.5	0.92195	[2, -1, 0, 0, -1, -1, -1, -1, -1, -1]
-shakier	-0.9	0.3	[-1, -1, 0, -1, -1, -1, -1, -1, -1, -1]
-shakiest	-1.2	0.74833	[-1, 0, 0, -1, -1, -1, -2, -2, -2, -2]
-shakily	-0.7	0.45826	[-1, -1, -1, -1, -1, 0, 0, 0, -1, -1]
-shakiness	-0.7	1.1	[2, -1, -1, -1, -2, -1, -1, -2, 0, 0]
-shaking	-0.7	0.45826	[-1, -1, -1, 0, -1, -1, 0, 0, -1, -1]
-shaky	-0.9	0.3	[-1, -1, -1, 0, -1, -1, -1, -1, -1, -1]
-shame	-2.1	0.53852	[-2, -2, -2, -3, -3, -1, -2, -2, -2, -2]
-shamed	-2.6	0.4899	[-2, -3, -3, -2, -3, -3, -3, -2, -2, -3]
-shamefaced	-2.3	0.64031	[-2, -2, -2, -3, -3, -3, -3, -1, -2, -2]
-shamefacedly	-1.9	0.3	[-2, -2, -2, -2, -2, -2, -2, -1, -2, -2]
-shamefacedness	-2.0	0.89443	[-1, -1, -2, -2, -2, -1, -2, -4, -2, -3]
-shamefast	-1.0	0.44721	[-1, -1, 0, -1, -1, -1, -1, -2, -1, -1]
-shameful	-2.2	0.6	[-3, -3, -2, -2, -2, -3, -1, -2, -2, -2]
-shamefully	-1.9	0.7	[-2, -3, -1, -3, -1, -2, -2, -1, -2, -2]
-shamefulness	-2.4	0.4899	[-2, -3, -3, -2, -3, -2, -3, -2, -2, -2]
-shamefulnesses	-2.3	0.78102	[-4, -2, -2, -2, -3, -1, -2, -2, -3, -2]
-shameless	-1.4	1.0198	[-1, -1, 1, -2, -3, -1, -2, -2, -1, -2]
-shamelessly	-1.4	1.0198	[-1, 0, -1, -2, 0, -1, -3, -3, -1, -2]
-shamelessness	-1.4	1.0198	[-1, -3, -2, 1, -2, -1, -2, -2, -1, -1]
-shamelessnesses	-2.0	1.0	[-2, 0, -2, -4, -2, -1, -2, -3, -2, -2]
-shames	-1.7	0.9	[-3, -3, -3, -1, -1, -1, -1, -1, -1, -2]
-share	1.2	0.74833	[0, 1, 1, 2, 2, 2, 1, 1, 0, 2]
-shared	1.4	0.4899	[2, 2, 2, 1, 2, 1, 1, 1, 1, 1]
-shares	1.2	0.87178	[0, 2, 1, 1, 0, 2, 2, 2, 2, 0]
-sharing	1.8	0.6	[2, 2, 1, 2, 2, 3, 1, 1, 2, 2]
-shattered	-2.1	0.7	[-1, -3, -3, -2, -2, -2, -3, -2, -1, -2]
-shit	-2.6	1.0198	[-2, -1, -4, -3, -4, -4, -2, -2, -2, -2]
-shitake	-0.3	1.26886	[-4, 0, 0, 0, 0, 0, 0, 0, 1, 0]
-shitakes	-1.1	1.7	[0, -4, 0, 0, 0, 0, -3, 0, -4, 0]
-shithead	-3.1	0.83066	[-3, -4, -4, -3, -4, -3, -1, -3, -3, -3]
-shitheads	-2.6	1.35647	[-2, -3, -4, -3, -3, -3, -2, -4, 1, -3]
-shits	-2.1	1.22066	[-3, 0, -3, 0, -2, -4, -2, -2, -2, -3]
-shittah	0.1	1.3	[-2, -2, 0, 2, 0, 0, 0, 0, 1, 2]
-shitted	-1.7	0.64031	[-2, -1, -2, -1, -2, -2, -3, -1, -2, -1]
-shittier	-2.1	0.83066	[-3, -3, -2, -1, -1, -1, -3, -2, -2, -3]
-shittiest	-3.4	0.66332	[-3, -4, -3, -4, -4, -4, -3, -3, -4, -2]
-shittim	-0.6	1.0198	[-3, 0, 0, 0, 0, -2, 0, 0, -1, 0]
-shittimwood	-0.3	0.9	[0, 0, -3, 0, 0, 0, 0, 0, 0, 0]
-shitting	-1.8	0.9798	[-1, -2, -2, -1, -3, -1, -1, -2, -4, -1]
-shitty	-2.6	0.8	[-3, -4, -2, -3, -3, -2, -3, -1, -2, -3]
-shock	-1.6	0.91652	[0, -3, -1, -2, -1, -2, -2, -1, -3, -1]
-shockable	-1.0	1.0	[-3, -1, -1, 0, 0, -2, -1, -2, 0, 0]
-shocked	-1.3	1.18743	[-2, -1, -1, 0, 0, -2, 0, -2, -1, -4]
-shocker	-0.6	1.49666	[-2, -1, 3, -1, 0, -3, -1, 0, -1, 0]
-shockers	-1.1	0.9434	[-1, -2, -2, -1, -1, 0, 0, -3, 0, -1]
-shocking	-1.7	1.34536	[-3, -3, 0, -1, 0, -3, 0, -1, -3, -3]
-shockingly	-0.7	1.48661	[-2, 0, -1, -3, -3, 0, 2, 0, 0, 0]
-shockproof	1.3	0.64031	[1, 0, 1, 1, 2, 2, 1, 2, 1, 2]
-shocks	-1.6	0.91652	[-3, -1, 0, -1, -2, -2, -1, -3, -2, -1]
-shook	-0.4	0.66332	[-1, -2, 0, 0, 0, 0, 0, 0, 0, -1]
-shoot	-1.4	1.11355	[-1, -4, -1, -1, -2, 0, -2, 0, -1, -2]
-short-sighted	-1.2	0.6	[0, -1, -2, -2, -1, -1, -1, -2, -1, -1]
-short-sightedness	-1.1	1.37477	[-1, -2, -2, -2, -3, -1, 0, 2, 0, -2]
-shortage	-1.0	1.09545	[-2, -2, -1, -2, -1, -1, 2, -1, -1, -1]
-shortages	-0.6	1.0198	[0, -2, -1, -1, 0, -2, 1, 1, -1, -1]
-shrew	-0.9	1.04403	[-2, -1, -2, -2, 1, 0, 0, 0, -1, -2]
-shy	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
-shyer	-0.8	0.6	[-1, -1, -1, -1, 0, -1, 0, 0, -2, -1]
-shying	-0.9	0.83066	[-1, -2, -1, 0, -2, 0, 0, 0, -2, -1]
-shylock	-2.1	1.13578	[-2, -2, -2, 0, -3, -3, -3, -3, 0, -3]
-shylocked	-0.7	1.00499	[0, -3, -1, 0, 0, -2, 0, -1, 0, 0]
-shylocking	-1.5	1.11803	[0, -2, -3, 0, -1, -3, -2, 0, -2, -2]
-shylocks	-1.4	1.11355	[0, -2, -1, -2, -3, 0, -3, -1, -2, 0]
-shyly	-0.7	0.45826	[-1, -1, -1, -1, 0, 0, -1, 0, -1, -1]
-shyness	-1.3	1.00499	[-2, 0, -3, 0, -1, -2, -2, -1, -2, 0]
-shynesses	-1.2	0.6	[-2, -1, -1, -2, -1, -2, 0, -1, -1, -1]
-shyster	-1.6	0.66332	[-2, -1, -2, -3, -2, -1, -1, -1, -1, -2]
-shysters	-0.9	0.7	[0, -2, 0, 0, -2, -1, -1, -1, -1, -1]
-sick	-2.3	0.78102	[-1, -2, -3, -2, -2, -4, -3, -2, -2, -2]
-sicken	-1.9	0.7	[-2, -3, -1, -3, -1, -1, -2, -2, -2, -2]
-sickened	-2.5	0.92195	[-3, -2, -4, -3, -1, -1, -3, -3, -2, -3]
-sickener	-2.2	0.87178	[-3, -1, -2, -3, -1, -1, -3, -3, -2, -3]
-sickeners	-2.2	0.6	[-3, -1, -2, -3, -2, -3, -2, -2, -2, -2]
-sickening	-2.4	0.91652	[-3, -4, -1, -3, -2, -2, -1, -3, -2, -3]
-sickeningly	-2.1	0.7	[-3, -3, -1, -2, -2, -1, -3, -2, -2, -2]
-sickens	-2.0	0.63246	[-2, -1, -2, -2, -3, -2, -1, -2, -3, -2]
-sigh	0.1	1.22066	[2, -1, -1, -1, 0, 2, 1, 1, -1, -1]
-significance	1.1	1.22066	[0, 0, 0, 1, 3, 2, 3, 2, 0, 0]
-significant	0.8	0.9798	[1, 0, 1, 3, 0, 1, 0, 0, 2, 0]
-silencing	-0.5	0.67082	[-2, -1, 0, 0, 0, 0, 0, -1, 0, -1]
-sillibub	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
-sillier	1.0	0.7746	[1, 1, 0, 2, 0, 1, 1, 2, 2, 0]
-sillies	0.8	0.74833	[2, 1, 0, 1, 0, 1, 0, 2, 1, 0]
-silliest	0.8	0.9798	[0, 1, 1, 1, 1, 0, 3, 1, -1, 1]
-sillily	-0.1	1.04403	[1, -1, -1, -1, 2, 1, -1, 0, 0, -1]
-sillimanite	0.1	0.3	[1, 0, 0, 0, 0, 0, 0, 0, 0, 0]
-sillimanites	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
-silliness	-0.9	1.22066	[1, -3, -1, 0, 1, -1, -2, -1, -2, -1]
-sillinesses	-1.2	1.46969	[-3, -2, -3, 0, -2, 0, 1, -2, -2, 1]
-silly	0.1	1.04403	[1, 1, 0, 0, 0, 2, -1, -2, 0, 0]
-sin	-2.6	0.8	[-2, -4, -3, -2, -2, -2, -4, -3, -2, -2]
-sincere	1.7	0.78102	[1, 2, 3, 0, 2, 2, 2, 2, 1, 2]
-sincerely	2.1	1.04403	[1, 3, 2, 4, 2, 3, 1, 1, 3, 1]
-sincereness	1.8	0.74833	[3, 1, 1, 2, 2, 3, 1, 2, 2, 1]
-sincerer	2.0	1.0	[1, 3, 3, 2, 3, 2, 1, 3, 0, 2]
-sincerest	2.0	1.34164	[0, 3, 1, 1, 4, 2, 1, 4, 1, 3]
-sincerities	1.5	0.67082	[2, 1, 1, 1, 1, 1, 3, 2, 2, 1]
-sinful	-2.6	0.8	[-4, -3, -3, -2, -1, -2, -3, -2, -3, -3]
-singleminded	1.2	0.87178	[1, 2, 0, 0, 3, 2, 1, 1, 1, 1]
-sinister	-2.9	1.13578	[-4, -4, -1, -3, -1, -4, -3, -3, -2, -4]
-sins	-2.0	1.0	[-2, -1, -2, -3, -1, -4, -3, -2, -1, -1]
-skeptic	-0.9	1.13578	[0, 0, -1, -1, -1, 0, -2, -2, 1, -3]
-skeptical	-1.3	0.9	[0, -3, -2, -2, -1, -2, 0, -1, -1, -1]
-skeptically	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -2]
-skepticism	-1.0	0.89443	[0, 0, -1, -1, -1, -1, 0, -1, -3, -2]
-skepticisms	-1.2	0.9798	[1, -2, 0, -1, -2, -1, -2, -2, -1, -2]
-skeptics	-0.4	0.91652	[-2, 0, 0, -1, -1, 1, -1, 0, 1, -1]
-slam	-1.6	1.11355	[-2, -1, -3, -1, -3, -2, -1, -2, 1, -2]
-slash	-1.1	1.22066	[-2, -3, -2, 0, -2, 0, -1, -2, 0, 1]
-slashed	-0.9	0.83066	[-2, -1, -2, -1, -1, 0, 1, -1, -1, -1]
-slashes	-0.8	0.6	[0, -1, -2, -1, 0, 0, -1, -1, -1, -1]
-slashing	-1.1	1.86815	[-3, -2, -3, -3, 3, 1, 0, -1, -2, -1]
-slavery	-3.8	0.4	[-4, -3, -4, -3, -4, -4, -4, -4, -4, -4]
-sleeplessness	-1.6	1.49666	[-3, -4, -2, -1, -2, -2, -2, 2, -1, -1]
-slicker	0.4	1.28062	[-2, 1, -1, 2, 0, 0, 2, 2, 0, 0]
-slickest	0.3	1.00499	[1, 0, -1, 0, -1, 0, 0, 0, 2, 2]
-sluggish	-1.7	0.64031	[-1, -2, -1, -3, -2, -2, -1, -2, -1, -2]
-slut	-2.8	0.87178	[-4, -2, -2, -1, -3, -3, -3, -3, -4, -3]
-sluts	-2.7	1.48661	[-3, -3, -4, -4, -3, -4, -1, -3, 1, -3]
-sluttier	-2.7	1.18743	[-2, -2, -4, -3, -4, -4, -1, -1, -2, -4]
-sluttiest	-3.1	0.83066	[-3, -4, -3, -4, -3, -4, -2, -2, -4, -2]
-sluttish	-2.2	0.87178	[-2, -3, -3, -2, -2, -4, -2, -1, -1, -2]
-sluttishly	-2.1	1.13578	[-2, 0, -2, -3, -1, -2, -3, -1, -3, -4]
-sluttishness	-2.5	0.92195	[-2, -1, -3, -4, -2, -1, -3, -3, -3, -3]
-sluttishnesses	-2.0	1.09545	[0, -2, -1, -3, -3, -1, -3, -1, -3, -3]
-slutty	-2.3	0.9	[-3, -1, -3, -3, -3, -2, -1, -3, -1, -3]
-smart	1.7	0.78102	[2, 2, 1, 2, 1, 3, 2, 0, 2, 2]
-smartass	-2.1	0.83066	[-1, -1, -2, -3, -2, -1, -2, -3, -3, -3]
-smartasses	-1.7	2.05183	[-1, -2, -3, -3, -3, -1, -2, -3, 4, -3]
-smarted	0.7	1.41774	[2, 1, -2, 1, 1, 2, 2, 2, -1, -1]
-smarten	1.9	0.7	[3, 1, 2, 1, 2, 2, 2, 3, 1, 2]
-smartened	1.5	0.67082	[2, 2, 1, 3, 1, 1, 1, 1, 2, 1]
-smartening	1.7	0.9	[1, 3, 3, 1, 1, 1, 2, 1, 1, 3]
-smartens	1.5	0.5	[2, 2, 1, 1, 1, 1, 2, 2, 2, 1]
-smarter	2.0	0.7746	[2, 2, 1, 1, 2, 2, 2, 2, 4, 2]
-smartest	3.0	1.0	[4, 3, 4, 3, 2, 2, 4, 3, 1, 4]
-smartie	1.3	0.9	[1, 4, 1, 1, 1, 1, 1, 1, 1, 1]
-smarties	1.7	0.9	[1, 1, 2, 4, 2, 2, 1, 2, 1, 1]
-smarting	-0.7	1.9	[2, 3, -1, -2, 1, -2, -1, -3, -2, -2]
-smartly	1.5	0.67082	[2, 1, 1, 1, 1, 2, 1, 3, 1, 2]
-smartness	2.0	0.89443	[1, 3, 3, 1, 2, 1, 2, 3, 1, 3]
-smartnesses	1.5	0.92195	[1, 0, 1, 1, 1, 2, 1, 2, 3, 3]
-smarts	1.6	0.66332	[2, 1, 3, 1, 2, 1, 2, 1, 2, 1]
-smartweed	0.2	0.6	[0, 0, 0, 0, 0, 2, 0, 0, 0, 0]
-smartweeds	0.1	0.53852	[0, 0, -1, 0, 0, 0, 1, 0, 0, 1]
-smarty	1.1	0.53852	[0, 2, 1, 2, 1, 1, 1, 1, 1, 1]
-smear	-1.5	1.20416	[-2, -1, -1, -2, -3, 0, 0, -4, -1, -1]
-smilax	0.6	0.66332	[0, 2, 1, 0, 0, 0, 1, 1, 1, 0]
-smilaxes	0.3	0.78102	[0, 0, 0, 0, 1, 2, 1, -1, 0, 0]
-smile	1.5	0.67082	[2, 1, 1, 1, 2, 2, 3, 1, 1, 1]
-smiled	2.5	0.80623	[3, 2, 3, 2, 1, 2, 3, 4, 3, 2]
-smileless	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -1, -2, -2]
-smiler	1.7	0.78102	[1, 1, 3, 1, 3, 2, 2, 2, 1, 1]
-smiles	2.1	1.04403	[2, 4, 2, 1, 3, 1, 1, 3, 1, 3]
-smiley	1.7	0.78102	[1, 2, 1, 2, 2, 0, 2, 3, 2, 2]
-smileys	1.5	0.92195	[1, 2, 1, 3, 1, 0, 1, 3, 1, 2]
-smiling	2.0	1.18322	[2, 1, 1, 1, 2, 3, 4, 1, 4, 1]
-smilingly	2.3	0.64031	[3, 2, 3, 2, 3, 1, 2, 2, 2, 3]
-smog	-1.2	0.6	[-1, -1, -2, -1, -1, -2, -2, -1, 0, -1]
-smother	-1.8	0.87178	[-2, -2, -3, -1, -2, -1, -2, -2, -3, 0]
-smothered	-0.9	1.7	[2, -4, 0, -1, -3, -2, 0, -1, 1, -1]
-smothering	-1.4	1.56205	[-2, -3, -1, -4, 0, -2, -1, 2, -1, -2]
-smothers	-1.9	1.04403	[-1, -1, -3, -1, -2, -3, 0, -2, -3, -3]
-smothery	-1.1	0.7	[-2, 0, -2, -1, -2, -1, 0, -1, -1, -1]
-smug	0.8	1.16619	[-1, 2, 0, 2, 1, -1, 2, 1, 0, 2]
-smugger	-1.0	0.89443	[1, -2, -1, -2, -1, -1, -1, 0, -2, -1]
-smuggest	-1.5	1.28452	[-1, -1, -1, 1, -1, -3, -4, -2, -1, -2]
-smuggle	-1.6	1.11355	[-2, -1, -1, -1, -2, 0, -1, -1, -3, -4]
-smuggled	-1.5	0.92195	[-1, -1, -2, -1, -1, -1, -2, -1, -1, -4]
-smuggler	-2.1	1.22066	[-1, -3, -3, -1, -1, -1, -4, -1, -2, -4]
-smugglers	-1.4	1.56205	[-2, -3, -4, 1, -2, 0, -2, 1, -1, -2]
-smuggles	-1.7	1.00499	[-1, -2, -2, -1, -1, -1, -3, -1, -1, -4]
-smuggling	-2.1	0.83066	[-3, -2, -2, -1, -2, -2, -1, -2, -4, -2]
-smugly	0.2	1.249	[-1, 2, -1, -1, 1, 1, -1, 1, 2, -1]
-smugness	-1.4	1.11355	[-1, -1, -1, -3, -3, -2, 1, -1, -2, -1]
-smugnesses	-1.7	0.78102	[-1, -1, -2, -1, -3, -1, -2, -2, -3, -1]
-sneaky	-0.9	0.7	[-1, -1, -1, -2, -1, -1, -1, 1, -1, -1]
-snob	-2.0	0.63246	[-2, -2, -2, -2, -2, -1, -3, -1, -3, -2]
-snobbery	-2.0	0.63246	[-1, -2, -2, -2, -2, -3, -2, -1, -3, -2]
-snobbier	-0.7	1.00499	[-1, 2, -1, -1, -1, -1, -1, 0, -2, -1]
-snobbiest	-0.5	1.11803	[-2, -2, 1, -1, 1, -1, 0, -1, 1, -1]
-snobbily	-1.6	1.11355	[-1, -2, -2, -2, -1, -3, -3, -1, 1, -2]
-snobbish	-0.9	1.37477	[-2, -1, 1, -1, 1, -2, -3, -2, 1, -1]
-snobbishly	-1.2	1.249	[-2, 1, -2, -1, -2, -3, -1, -2, -1, 1]
-snobbishness	-1.1	1.22066	[-1, -2, -2, -1, -3, -1, -1, -1, 2, -1]
-snobbishnesses	-1.7	0.78102	[-2, -1, -3, -2, -1, -1, -2, -1, -3, -1]
-snobbism	-1.0	1.41421	[-2, -1, 1, -1, 1, -2, -3, -2, 1, -2]
-snobbisms	-0.3	1.18743	[1, -1, -1, 0, -1, -1, 1, -2, 2, -1]
-snobby	-1.7	1.00499	[-1, -1, -1, -3, -2, -2, 0, -3, -3, -1]
-snobs	-1.4	1.0198	[-2, -1, -1, -2, -2, -3, -1, -2, 1, -1]
-snub	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -2, -1, -2]
-snubbed	-2.0	0.7746	[-2, -2, 0, -2, -3, -2, -2, -2, -3, -2]
-snubbing	-0.9	1.13578	[-2, -1, -1, -1, 1, -1, -3, 1, -1, -1]
-snubs	-2.1	0.9434	[-2, -1, -1, -1, -3, -2, -4, -3, -2, -2]
-sob	-1.0	1.34164	[-1, -2, -2, -2, -1, -1, 2, 1, -2, -2]
-sobbed	-1.9	1.3	[-2, -4, 1, -1, -3, -1, -3, -2, -2, -2]
-sobbing	-1.6	1.49666	[1, -2, -3, -1, -1, -3, 1, -2, -3, -3]
-sobering	-0.8	1.32665	[2, -2, 0, -2, -1, -1, -2, 1, -1, -2]
-sobs	-2.5	0.67082	[-3, -3, -2, -2, -3, -3, -3, -1, -2, -3]
-sociabilities	1.2	0.9798	[1, 3, 1, 2, 0, 1, 0, 2, 2, 0]
-sociability	1.1	0.9434	[0, 1, 1, 1, 0, 2, 1, 0, 2, 3]
-sociable	1.9	0.7	[1, 1, 2, 3, 1, 2, 2, 2, 3, 2]
-sociableness	1.5	0.5	[1, 1, 1, 2, 2, 2, 1, 2, 1, 2]
-sociably	1.6	0.91652	[3, 2, 0, 1, 3, 2, 1, 1, 2, 1]
-sok	1.3	1.1	[0, 1, 2, 1, 1, 0, 1, 4, 2, 1]
-solemn	-0.3	1.1	[-1, -2, -1, 0, -1, 2, 0, -1, 1, 0]
-solemnified	-0.5	0.67082	[0, 0, 0, 0, -1, -1, -1, 0, -2, 0]
-solemnifies	-0.5	0.67082	[0, 0, 0, 0, -1, -2, -1, 0, -1, 0]
-solemnify	0.3	1.18743	[2, 1, 2, 1, 0, 0, -2, -1, 0, 0]
-solemnifying	0.1	1.3	[2, -1, 0, -3, 0, 1, 1, 1, 0, 0]
-solemnities	0.3	0.78102	[0, 1, -1, 0, 0, 0, 2, 1, 0, 0]
-solemnity	-1.1	0.9434	[0, -2, 0, -2, -2, -1, -2, 0, 0, -2]
-solemnization	0.7	1.34536	[-1, -1, 0, 2, 2, 0, 3, 2, 0, 0]
-solemnize	0.3	0.78102	[1, -1, 0, 2, 0, 0, 1, 0, 0, 0]
-solemnized	-0.7	0.9	[0, 0, 0, -1, -1, -1, -1, 0, 0, -3]
-solemnizes	0.6	0.91652	[0, 0, 0, 0, 0, 0, 2, 2, 2, 0]
-solemnizing	-0.6	0.8	[0, 0, -1, -1, 0, 0, -2, -2, 0, 0]
-solemnly	0.8	0.9798	[0, 2, 0, 1, 1, 2, -1, 2, 1, 0]
-solid	0.6	0.8	[0, 2, 1, 2, 0, 1, 0, 0, 0, 0]
-solidarity	1.2	0.6	[1, 1, 1, 1, 2, 0, 1, 2, 2, 1]
-solution	1.3	0.64031	[1, 2, 1, 2, 1, 1, 2, 2, 0, 1]
-solutions	0.7	0.78102	[1, 1, 2, 0, 1, 0, 2, 0, 0, 0]
-solve	0.8	0.4	[0, 1, 1, 1, 1, 0, 1, 1, 1, 1]
-solved	1.1	0.53852	[1, 2, 1, 0, 1, 1, 1, 2, 1, 1]
-solves	1.1	0.7	[2, 0, 1, 0, 1, 2, 1, 2, 1, 1]
-solving	1.4	0.8	[0, 3, 1, 2, 1, 1, 2, 1, 2, 1]
-somber	-1.8	0.6	[-1, -2, -2, -3, -2, -1, -2, -1, -2, -2]
-son-of-a-bitch	-2.7	0.64031	[-3, -3, -3, -1, -2, -3, -3, -3, -3, -3]
-soothe	1.5	0.92195	[3, 2, 2, 1, 2, 0, 2, 0, 2, 1]
-soothed	0.5	1.43178	[2, -3, 1, 1, 0, 1, 1, 1, 2, -1]
-soothing	1.3	0.64031	[2, 1, 2, 1, 1, 1, 2, 0, 2, 1]
-sophisticated	2.6	0.91652	[3, 4, 3, 3, 3, 1, 2, 1, 3, 3]
-sore	-1.5	0.5	[-2, -2, -2, -1, -1, -1, -2, -1, -1, -2]
-sorrow	-2.4	0.8	[-2, -2, -2, -1, -2, -3, -2, -4, -3, -3]
-sorrowed	-2.4	0.8	[-1, -2, -3, -3, -2, -3, -2, -4, -2, -2]
-sorrower	-2.3	0.78102	[-1, -2, -1, -3, -3, -2, -2, -3, -3, -3]
-sorrowful	-2.2	0.6	[-3, -3, -2, -2, -2, -2, -3, -1, -2, -2]
-sorrowfully	-2.3	0.64031	[-3, -3, -2, -1, -2, -2, -3, -2, -2, -3]
-sorrowfulness	-2.5	0.67082	[-4, -3, -2, -3, -2, -3, -2, -2, -2, -2]
-sorrowing	-1.7	1.26886	[-2, -2, 1, -1, -1, -2, -4, -3, -2, -1]
-sorrows	-1.6	0.66332	[-1, -1, -2, -1, -2, -2, -1, -2, -1, -3]
-sorry	-0.3	1.61555	[-1, 0, -1, -2, -1, -1, 4, 1, -1, -1]
-soulmate	2.9	0.83066	[4, 2, 2, 2, 3, 4, 3, 3, 2, 4]
-spam	-1.5	1.0247	[-1, -1, -1, -2, 1, -2, -3, -2, -2, -2]
-spammer	-2.2	0.6	[-3, -2, -2, -1, -2, -3, -2, -2, -3, -2]
-spammers	-1.6	1.11355	[-2, -1, -2, -3, -2, -1, -2, -1, 1, -3]
-spamming	-2.1	0.83066	[-3, -3, -1, -3, -2, -1, -2, -2, -1, -3]
-spark	0.9	1.04403	[0, 2, 1, 1, 0, 1, 3, -1, 1, 1]
-sparkle	1.8	0.74833	[0, 2, 2, 2, 1, 2, 3, 2, 2, 2]
-sparkles	1.3	1.18743	[3, 2, 0, 0, 3, 0, 2, 0, 1, 2]
-sparkling	1.2	0.4	[1, 1, 1, 2, 1, 1, 1, 2, 1, 1]
-special	1.7	0.78102	[3, 1, 3, 2, 2, 1, 1, 2, 1, 1]
-speculative	0.4	1.11355	[1, -1, 1, 0, -1, -1, 1, 2, 2, 0]
-spirit	0.7	1.00499	[0, 0, 1, 2, 3, 1, 0, 0, 0, 0]
-spirited	1.3	1.00499	[1, 1, 0, 1, 1, 3, 2, 3, 0, 1]
-spiritless	-1.3	0.64031	[-2, -1, -1, -2, -2, -1, 0, -1, -2, -1]
-spite	-2.4	0.8	[-2, -2, -3, -2, -3, -2, -4, -1, -3, -2]
-spited	-2.4	0.91652	[-2, -3, -3, -4, -2, -1, -2, -1, -3, -3]
-spiteful	-1.9	1.75784	[-2, 3, -2, -3, -2, -3, -2, -2, -4, -2]
-spitefully	-2.3	0.78102	[-2, -2, -1, -3, -3, -2, -2, -2, -4, -2]
-spitefulness	-1.5	1.74642	[-3, -2, 1, -3, -3, -3, -2, 2, 0, -2]
-spitefulnesses	-2.3	0.9	[-1, -4, -2, -3, -3, -2, -2, -3, -1, -2]
-spites	-1.4	1.28062	[0, -2, -2, -3, -2, -1, 1, 0, -3, -2]
-splendent	2.7	0.78102	[3, 2, 1, 3, 2, 3, 4, 3, 3, 3]
-splendid	2.8	0.9798	[4, 2, 3, 4, 2, 2, 3, 1, 3, 4]
-splendidly	2.1	1.22066	[1, 4, 1, 3, 3, 4, 1, 2, 1, 1]
-splendidness	2.3	0.9	[2, 1, 3, 3, 4, 2, 1, 3, 2, 2]
-splendiferous	2.6	1.95959	[4, 4, 3, -3, 3, 3, 4, 2, 3, 3]
-splendiferously	1.9	1.3	[2, 4, 4, 3, 0, 1, 1, 1, 2, 1]
-splendiferousness	1.7	1.18743	[1, 2, 3, 1, 2, 3, 3, 2, -1, 1]
-splendor	3.0	0.63246	[3, 3, 3, 3, 3, 2, 4, 4, 3, 2]
-splendorous	2.2	0.87178	[4, 2, 1, 2, 2, 3, 3, 1, 2, 2]
-splendors	2.0	0.44721	[2, 2, 2, 2, 3, 2, 2, 2, 1, 2]
-splendour	2.2	0.6	[2, 2, 2, 3, 3, 1, 2, 3, 2, 2]
-splendours	2.2	1.249	[3, 0, 2, 1, 4, 3, 2, 4, 1, 2]
-splendrous	2.2	1.16619	[4, 4, 3, 2, 1, 1, 3, 1, 2, 1]
-sprightly	2.0	0.89443	[0, 2, 3, 2, 2, 1, 2, 3, 3, 2]
-squelched	-1.0	0.63246	[-1, -1, -1, -1, 0, -2, -1, 0, -1, -2]
-stab	-2.8	0.6	[-3, -2, -2, -3, -3, -3, -3, -2, -4, -3]
-stabbed	-1.9	1.22066	[-2, -1, -3, -2, -2, 1, -3, -3, -1, -3]
-stable	1.2	0.74833	[1, 2, 2, 0, 1, 2, 1, 1, 2, 0]
-stabs	-1.9	1.13578	[-3, -3, -4, 0, -1, -2, -2, -2, -1, -1]
-stall	-0.8	0.74833	[-1, 0, -1, 0, -1, 0, -2, 0, -2, -1]
-stalled	-0.8	0.87178	[-2, -1, 0, -1, -1, 0, 1, -2, -1, -1]
-stalling	-0.8	1.4	[-3, -2, -1, -1, 0, 2, 1, -2, -1, -1]
-stamina	1.2	0.9798	[1, 0, 3, 0, 1, 2, 2, 1, 2, 0]
-stammer	-0.9	0.3	[-1, 0, -1, -1, -1, -1, -1, -1, -1, -1]
-stammered	-0.9	0.7	[-2, -1, -1, -1, 1, -1, -1, -1, -1, -1]
-stammerer	-1.1	0.3	[-1, -2, -1, -1, -1, -1, -1, -1, -1, -1]
-stammerers	-0.8	0.4	[-1, -1, -1, -1, -1, 0, 0, -1, -1, -1]
-stammering	-1.0	0.63246	[-2, -1, 0, -1, -1, -2, 0, -1, -1, -1]
-stammers	-0.8	0.4	[-1, -1, -1, 0, -1, -1, -1, 0, -1, -1]
-stampede	-1.8	1.07703	[-2, -3, -2, -3, 0, 0, -2, -1, -2, -3]
-stank	-1.9	1.04403	[-2, -2, -2, -1, -2, -4, -3, 0, -1, -2]
-startle	-1.3	0.64031	[-1, -1, -1, -1, -1, -2, -1, -1, -3, -1]
-startled	-0.7	0.78102	[-2, -1, -1, 0, 1, -1, -1, 0, -1, -1]
-startlement	-0.5	1.20416	[-1, 0, 0, 1, -1, -1, 2, -2, -1, -2]
-startlements	0.2	1.32665	[2, 2, 0, 0, -1, 2, 0, -2, -1, 0]
-startler	-0.8	0.74833	[-2, -1, -1, 0, 1, -1, -1, -1, -1, -1]
-startlers	-0.5	0.80623	[0, 0, 0, 0, -1, -1, -1, 1, -1, -2]
-startles	-0.5	1.36015	[-2, 2, -1, 0, 2, -1, -1, -2, -1, -1]
-startling	0.3	1.41774	[-2, 2, -1, 0, -1, 2, -1, 1, 1, 2]
-startlingly	-0.3	0.9	[-1, -1, 0, -2, 1, 0, 1, 0, -1, 0]
-starve	-1.9	2.02237	[2, -3, -4, -1, -3, -4, -1, -2, 1, -4]
-starved	-2.6	1.11355	[-3, -4, -1, -3, -3, -4, -1, -1, -3, -3]
-starves	-2.3	0.78102	[-3, -2, -2, -3, -2, -3, -1, -1, -3, -3]
-starving	-1.8	2.03961	[-2, -2, -4, -4, -3, -3, 2, 2, -2, -2]
-steadfast	1.0	1.0	[0, 0, 2, 1, 1, 2, 3, 0, 1, 0]
-steal	-2.2	0.6	[-2, -2, -2, -3, -3, -3, -1, -2, -2, -2]
-stealable	-1.7	1.00499	[-3, -1, -2, -1, -2, -1, -1, -1, -4, -1]
-stealer	-1.7	0.78102	[-2, -2, -1, -2, -3, -1, -2, -2, -2, 0]
-stealers	-2.2	0.74833	[-2, -2, -2, -4, -2, -2, -3, -1, -2, -2]
-stealing	-2.7	0.9	[-3, -2, -2, -4, -4, -3, -1, -3, -2, -3]
-stealings	-1.9	0.9434	[-2, -2, -1, -1, -1, -3, -4, -2, -1, -2]
-steals	-2.3	0.64031	[-4, -2, -2, -3, -2, -2, -2, -2, -2, -2]
-stealth	-0.3	1.34536	[-2, 1, 1, -1, 0, -3, 0, 1, -1, 1]
-stealthier	-0.3	1.00499	[0, 0, -3, 0, 0, 1, 0, -1, 0, 0]
-stealthiest	0.4	2.10713	[-1, 2, 1, 1, 3, 4, -1, 0, -2, -3]
-stealthily	0.1	1.37477	[2, 0, 0, -1, 1, 0, -3, 2, 0, 0]
-stealthiness	0.2	0.74833	[1, 0, 0, -1, 1, 0, -1, 0, 1, 1]
-stealths	-0.3	0.78102	[-2, 0, 0, -1, 0, 1, -1, 0, 0, 0]
-stealthy	-0.1	0.7	[0, 0, 0, -1, 1, -1, -1, 0, 1, 0]
-stench	-2.3	0.64031	[-3, -2, -2, -3, -3, -1, -3, -2, -2, -2]
-stenches	-1.5	1.11803	[-2, -2, -1, -3, 0, 0, -3, -2, 0, -2]
-stenchful	-2.4	0.91652	[-3, -1, -3, -1, -2, -2, -3, -4, -2, -3]
-stenchy	-2.3	1.00499	[-4, -1, -2, -3, -1, -1, -2, -3, -3, -3]
-stereotype	-1.3	0.78102	[-1, -1, -2, 0, -2, 0, -2, -1, -2, -2]
-stereotyped	-1.2	0.4	[-1, -1, -2, -1, -2, -1, -1, -1, -1, -1]
-stifled	-1.4	0.66332	[-1, -1, -1, -1, -3, -1, -2, -2, -1, -1]
-stimulate	0.9	0.83066	[1, 0, 1, 1, 1, 2, -1, 2, 1, 1]
-stimulated	0.9	0.7	[1, 0, 0, 0, 1, 1, 2, 1, 2, 1]
-stimulates	1.0	0.89443	[1, 0, 0, 0, 1, 1, 2, 1, 3, 1]
-stimulating	1.9	0.7	[2, 3, 2, 1, 3, 2, 1, 2, 1, 2]
-stingy	-1.6	0.8	[-1, 0, -2, -2, -1, -1, -2, -2, -3, -2]
-stink	-1.7	0.64031	[-2, -2, -1, -3, -2, -1, -1, -2, -1, -2]
-stinkard	-2.3	0.9	[-2, -3, -3, -2, -3, -2, -3, -3, 0, -2]
-stinkards	-1.0	1.26491	[-2, -1, 2, -2, -1, -1, 0, -3, -1, -1]
-stinkbug	-0.2	0.4	[-1, 0, 0, 0, 0, 0, 0, 0, -1, 0]
-stinkbugs	-1.0	1.26491	[0, 0, 0, -4, -1, -2, -1, 0, -2, 0]
-stinker	-1.5	0.80623	[-3, -1, -3, -1, -1, -2, -1, -1, -1, -1]
-stinkers	-1.2	1.07703	[-3, 1, -1, -2, -2, -1, -1, -2, 0, -1]
-stinkhorn	-0.2	1.16619	[-2, -2, 0, 0, -1, 0, 1, 2, 0, 0]
-stinkhorns	-0.8	0.9798	[0, -3, 0, -2, 0, 0, -1, -1, -1, 0]
-stinkier	-1.5	1.0247	[-2, -1, -2, -2, -1, 1, -2, -1, -3, -2]
-stinkiest	-2.1	1.57797	[-1, -2, -3, -4, -2, -1, 1, -4, -1, -4]
-stinking	-2.4	0.91652	[-2, -4, -2, -3, -3, -1, -2, -1, -3, -3]
-stinkingly	-1.3	1.55242	[-2, -3, -3, -2, -2, 1, -2, 2, -1, -1]
-stinko	-1.5	0.80623	[-1, -2, -2, -2, 0, -1, -2, -1, -1, -3]
-stinkpot	-2.5	0.92195	[-4, -1, -3, -4, -2, -2, -3, -2, -2, -2]
-stinkpots	-0.7	1.26886	[-1, -3, -2, -1, 0, 2, 0, -1, 0, -1]
-stinks	-1.0	1.34164	[-2, -2, -1, -2, 2, -1, -2, 1, -1, -2]
-stinkweed	-0.4	1.0198	[-2, 0, -1, 0, 2, 0, -1, -1, 0, -1]
-stinkwood	-0.1	1.13578	[0, -2, 0, 0, 0, -2, 1, 0, 2, 0]
-stinky	-1.5	0.5	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -2]
-stolen	-2.2	0.9798	[-3, -2, -2, -1, -3, -2, -3, 0, -3, -3]
-stop	-1.2	0.87178	[-1, 0, -2, -2, 0, -1, -2, -2, 0, -2]
-stopped	-0.9	0.53852	[-1, -1, -1, -1, -2, -1, -1, -1, 0, 0]
-stopping	-0.6	0.66332	[-1, 0, 0, -1, 0, 0, 0, -1, -2, -1]
-stops	-0.6	0.8	[-1, -1, 0, 0, -2, 0, -2, 0, 0, 0]
-stout	0.7	1.34536	[2, 0, 3, 1, 2, 1, 0, 0, -2, 0]
-straight	0.9	1.04403	[2, 0, 1, 0, 0, 0, 1, 2, 3, 0]
-strain	-0.2	0.9798	[0, 0, -2, 0, -1, 2, 0, -1, 0, 0]
-strained	-1.7	0.78102	[0, -2, -1, -1, -2, -2, -2, -3, -2, -2]
-strainer	-0.8	1.249	[2, -2, -1, 0, -1, 0, -2, 0, -2, -2]
-strainers	-0.3	0.45826	[0, 0, 0, 0, -1, -1, 0, -1, 0, 0]
-straining	-1.3	0.78102	[0, -3, -2, -1, -1, -1, -1, -1, -2, -1]
-strains	-1.2	0.4	[-1, -1, -1, -2, -1, -2, -1, -1, -1, -1]
-strange	-0.8	0.74833	[0, -1, -1, 0, -2, 0, -1, -2, 0, -1]
-strangely	-1.2	0.87178	[0, -1, -2, -2, 0, -3, -1, -1, -1, -1]
-strangled	-2.5	1.0247	[-1, -1, -3, -3, -3, -3, -1, -4, -3, -3]
-strength	2.2	0.6	[1, 2, 2, 3, 2, 3, 3, 2, 2, 2]
-strengthen	1.3	0.64031	[1, 1, 2, 1, 2, 1, 2, 0, 2, 1]
-strengthened	1.8	0.4	[2, 2, 2, 2, 1, 2, 2, 1, 2, 2]
-strengthener	1.8	0.6	[2, 0, 2, 2, 2, 2, 2, 2, 2, 2]
-strengtheners	1.4	0.91652	[1, 2, 1, 2, 3, 0, 2, 0, 2, 1]
-strengthening	2.2	0.74833	[3, 3, 1, 1, 2, 2, 2, 2, 3, 3]
-strengthens	2.0	0.63246	[3, 2, 1, 2, 2, 3, 2, 1, 2, 2]
-strengths	1.7	0.64031	[2, 1, 3, 1, 2, 1, 2, 1, 2, 2]
-stress	-1.8	0.6	[-1, -2, -2, -1, -2, -1, -2, -3, -2, -2]
-stressed	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -1]
-stresses	-2.0	1.0	[-3, -3, -2, -1, -2, 0, -2, -1, -3, -3]
-stressful	-2.3	0.45826	[-2, -2, -2, -2, -3, -3, -2, -3, -2, -2]
-stressfully	-2.6	0.66332	[-2, -3, -1, -3, -3, -3, -3, -2, -3, -3]
-stressing	-1.5	0.67082	[-1, -2, -1, -1, -3, -1, -2, -2, -1, -1]
-stressless	1.6	0.4899	[1, 2, 1, 2, 1, 2, 1, 2, 2, 2]
-stresslessness	1.6	0.8	[1, 3, 1, 3, 2, 1, 2, 1, 1, 1]
-stressor	-1.8	0.74833	[-2, -1, -1, -2, -3, -2, -1, -2, -3, -1]
-stressors	-2.1	0.83066	[-3, -2, -2, -2, -3, -1, -3, -1, -1, -3]
-stricken	-2.3	0.9	[0, -2, -2, -2, -2, -3, -3, -3, -3, -3]
-strike	-0.5	1.11803	[0, 0, 0, -2, -2, 1, 1, -2, -1, 0]
-strikers	-0.6	1.0198	[0, 0, -2, -3, 0, 0, -1, 0, 0, 0]
-strikes	-1.5	0.92195	[0, -2, -2, -2, -3, -1, -2, -1, 0, -2]
-strong	2.3	0.78102	[3, 2, 3, 3, 1, 1, 3, 2, 2, 3]
-strongbox	0.7	0.78102	[2, 1, 0, 0, 0, 1, 2, 1, 0, 0]
-strongboxes	0.3	0.64031	[0, 0, 0, 0, 0, 1, 0, 2, 0, 0]
-stronger	1.6	0.66332	[2, 1, 1, 1, 2, 3, 2, 1, 2, 1]
-strongest	1.9	0.9434	[2, 3, 2, 1, 2, 2, 0, 3, 1, 3]
-stronghold	0.5	0.80623	[0, 2, 0, 0, 2, 0, 0, 0, 0, 1]
-strongholds	1.0	0.89443	[2, 2, 0, 1, 2, 2, 1, 0, 0, 0]
-strongish	1.7	0.78102	[1, 1, 2, 3, 1, 2, 1, 3, 2, 1]
-strongly	1.1	0.83066	[0, 0, 2, 2, 0, 1, 2, 2, 1, 1]
-strongman	0.7	1.00499	[0, 1, 3, 0, 1, -1, 1, 1, 0, 1]
-strongmen	0.5	1.11803	[-1, 0, 0, 3, 0, 1, 0, 2, 0, 0]
-strongyl	0.6	1.0198	[0, 1, 0, 0, 0, 0, 0, 2, 3, 0]
-strongyles	0.2	1.07703	[0, -2, 1, 1, -1, 1, 0, 0, 2, 0]
-strongyloidosis	-0.8	1.66132	[-2, -3, 0, 0, -2, -2, 2, -2, 2, -1]
-strongyls	0.1	0.3	[0, 0, 1, 0, 0, 0, 0, 0, 0, 0]
-struck	-1.0	0.89443	[-1, -2, -1, 0, -2, -2, -1, -1, 1, -1]
-struggle	-1.3	0.45826	[-2, -1, -2, -1, -2, -1, -1, -1, -1, -1]
-struggled	-1.4	0.66332	[-2, -2, -1, -1, -1, -1, -2, -2, 0, -2]
-struggler	-1.1	0.7	[-1, -1, -1, -1, 0, -1, -2, -2, 0, -2]
-strugglers	-1.4	0.4899	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -1]
-struggles	-1.5	0.5	[-2, -2, -1, -1, -1, -1, -2, -2, -1, -2]
-struggling	-1.8	0.6	[-2, -2, -2, -2, -1, -1, -2, -2, -3, -1]
-stubborn	-1.7	1.00499	[0, -1, -2, -2, -2, -4, -1, -2, -1, -2]
-stubborner	-1.5	1.20416	[-2, -3, -1, -1, -2, 1, -3, -2, 0, -2]
-stubbornest	-0.6	1.62481	[-2, 4, -2, -1, -1, 0, -1, -1, -1, -1]
-stubbornly	-1.4	0.4899	[-2, -2, -1, -2, -1, -1, -2, -1, -1, -1]
-stubbornness	-1.1	0.53852	[-1, -1, 0, -2, -1, -1, -1, -2, -1, -1]
-stubbornnesses	-1.5	0.80623	[-1, -2, -3, -1, -1, -3, -1, -1, -1, -1]
-stuck	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -1, -1, -2]
-stunk	-1.6	1.68523	[-2, -2, -3, 2, -2, -3, -3, 1, -1, -3]
-stunned	-0.4	1.28062	[-1, -3, -1, 0, -1, -1, 0, 2, 1, 0]
-stunning	1.6	1.42829	[0, 0, 3, 2, 2, 4, 3, 0, 2, 0]
-stuns	0.1	1.04403	[1, 0, -1, -2, 0, 1, 1, -1, 1, 1]
-stupid	-2.4	0.66332	[-2, -3, -3, -2, -3, -3, -2, -1, -2, -3]
-stupider	-2.5	0.5	[-3, -2, -3, -3, -2, -2, -3, -2, -3, -2]
-stupidest	-2.4	0.66332	[-2, -3, -2, -3, -1, -3, -3, -2, -2, -3]
-stupidities	-2.0	0.7746	[-2, -3, -2, -1, -3, -1, -3, -1, -2, -2]
-stupidity	-1.9	0.3	[-2, -2, -2, -2, -2, -2, -1, -2, -2, -2]
-stupidly	-2.0	0.7746	[-1, -2, -3, -3, -1, -3, -2, -1, -2, -2]
-stupidness	-1.7	0.64031	[-3, -1, -2, -1, -2, -1, -2, -2, -1, -2]
-stupidnesses	-2.6	0.8	[-2, -2, -2, -4, -4, -3, -3, -2, -2, -2]
-stupids	-2.3	0.64031	[-2, -3, -1, -3, -2, -3, -3, -2, -2, -2]
-stutter	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
-stuttered	-0.9	1.04403	[-1, -1, 2, -1, -1, -1, -2, -2, -1, -1]
-stutterer	-1.0	1.18322	[-1, -1, 2, -1, -1, -1, -3, -2, -1, -1]
-stutterers	-1.1	0.53852	[-1, -1, -1, 0, -1, -1, -2, -2, -1, -1]
-stuttering	-1.3	0.9	[-1, -1, -1, 0, -3, -1, -1, -1, -3, -1]
-stutters	-1.0	0.63246	[-1, -1, -1, -2, 0, -2, 0, -1, -1, -1]
-suave	2.0	0.44721	[2, 3, 2, 2, 2, 1, 2, 2, 2, 2]
-submissive	-1.3	0.9	[-1, 0, -1, -3, -1, 0, -1, -2, -2, -2]
-submissively	-1.0	1.18322	[-1, -1, -1, -1, 2, -1, -1, -2, -3, -1]
-submissiveness	-0.7	0.78102	[-2, 0, -1, 0, -1, 0, -2, 0, -1, 0]
-substantial	0.8	0.6	[2, 0, 1, 1, 0, 0, 1, 1, 1, 1]
-subversive	-0.9	1.81384	[-3, 0, -4, -1, -2, -1, 2, -1, 2, -1]
-succeed	2.2	0.74833	[2, 3, 2, 2, 2, 1, 2, 4, 2, 2]
-succeeded	1.8	0.87178	[2, 2, 1, 2, 2, 0, 2, 3, 3, 1]
-succeeder	1.2	1.07703	[1, 0, 0, 2, 2, 0, 0, 3, 2, 2]
-succeeders	1.3	0.64031	[2, 0, 2, 1, 2, 1, 1, 1, 1, 2]
-succeeding	2.2	1.16619	[2, 3, 0, 3, 4, 3, 1, 1, 2, 3]
-succeeds	2.2	0.9798	[4, 1, 4, 1, 2, 2, 2, 2, 2, 2]
-success	2.7	0.64031	[4, 3, 2, 2, 3, 2, 3, 3, 2, 3]
-successes	2.6	0.66332	[2, 4, 3, 3, 2, 3, 2, 2, 3, 2]
-successful	2.8	0.6	[3, 3, 2, 3, 4, 3, 3, 3, 2, 2]
-successfully	2.2	0.6	[2, 2, 1, 2, 2, 2, 3, 3, 2, 3]
-successfulness	2.7	0.78102	[3, 3, 4, 3, 3, 2, 3, 2, 1, 3]
-succession	0.8	0.87178	[2, 0, 1, 2, 0, 2, 1, 0, 0, 0]
-successional	0.9	1.04403	[0, 1, 0, 2, 3, 0, 0, 1, 2, 0]
-successionally	1.1	1.13578	[2, 2, 0, 0, 0, 0, 2, 3, 0, 2]
-successions	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
-successive	1.1	1.13578	[3, 0, 0, 1, 3, 2, 1, 0, 1, 0]
-successively	0.9	1.04403	[1, 0, 0, 1, 3, 0, 2, 0, 2, 0]
-successiveness	1.0	1.0	[0, 1, 2, 0, 3, 1, 1, 2, 0, 0]
-successor	0.9	0.83066	[0, 2, 0, 0, 1, 2, 2, 1, 1, 0]
-successors	1.1	1.04403	[2, 0, 1, 2, 0, 1, 3, 0, 2, 0]
-suck	-1.9	1.04403	[-1, -1, -1, -2, -1, -1, -3, -4, -3, -2]
-sucked	-2.0	0.89443	[-2, -2, -1, -1, -1, -3, -4, -2, -2, -2]
-sucker	-2.4	1.2	[-3, -1, -1, -2, -1, -4, -4, -2, -4, -2]
-suckered	-2.0	1.0	[-2, -1, -1, -3, -3, -1, -1, -2, -2, -4]
-suckering	-2.1	0.7	[-2, -3, -2, -1, -2, -3, -3, -2, -1, -2]
-suckers	-2.3	1.00499	[-2, -1, -2, -4, -1, -2, -3, -2, -4, -2]
-sucks	-1.5	1.28452	[-1, -2, -2, -1, -3, -4, -1, 1, -1, -1]
-sucky	-1.9	0.9434	[-1, -2, -2, -1, -2, -4, -1, -1, -3, -2]
-suffer	-2.5	0.67082	[-3, -3, -2, -2, -3, -3, -3, -2, -1, -3]
-suffered	-2.2	0.74833	[-3, -2, -1, -3, -2, -3, -1, -3, -2, -2]
-sufferer	-2.0	0.63246	[-3, -2, -2, -2, -2, -3, -1, -2, -2, -1]
-sufferers	-2.4	0.8	[-1, -3, -3, -2, -1, -2, -3, -3, -3, -3]
-suffering	-2.1	0.83066	[-2, -1, -3, -2, -1, -2, -3, -3, -1, -3]
-suffers	-2.1	0.7	[-3, -2, -1, -2, -2, -2, -3, -1, -3, -2]
-suicidal	-3.5	0.67082	[-4, -4, -4, -4, -3, -4, -3, -3, -2, -4]
-suicide	-3.5	0.67082	[-4, -3, -4, -4, -4, -2, -3, -4, -4, -3]
-suing	-1.1	1.13578	[1, -1, -1, 0, -1, -3, -1, -1, -3, -1]
-sulking	-1.5	0.67082	[-2, -1, -3, -1, -1, -2, -1, -2, -1, -1]
-sulky	-0.8	1.77764	[-3, 3, -2, -3, 0, -2, 0, -1, 1, -1]
-sullen	-1.7	1.00499	[0, -2, -2, -1, -1, -4, -2, -1, -2, -2]
-sunnier	2.3	0.64031	[3, 2, 3, 2, 3, 2, 2, 1, 3, 2]
-sunniest	2.4	1.28062	[2, 0, 4, 2, 1, 3, 2, 4, 4, 2]
-sunny	1.8	0.87178	[2, 2, 1, 2, 0, 2, 3, 3, 2, 1]
-sunshine	2.2	0.6	[3, 1, 2, 2, 2, 2, 2, 3, 3, 2]
-sunshiny	1.9	0.7	[2, 2, 3, 1, 2, 2, 1, 3, 1, 2]
-super	2.9	0.7	[4, 2, 4, 3, 3, 3, 2, 3, 2, 3]
-superb	3.1	0.9434	[3, 4, 2, 4, 3, 1, 3, 3, 4, 4]
-superior	2.5	1.11803	[2, 3, 1, 3, 3, 0, 3, 3, 4, 3]
-superiorities	0.8	1.6	[-1, 1, 3, -1, -1, 2, 2, 1, 3, -1]
-superiority	1.4	1.2	[0, 1, -1, 3, 1, 2, 2, 2, 3, 1]
-superiorly	2.2	1.4	[4, 3, 1, 2, 3, -1, 2, 4, 2, 2]
-superiors	1.0	1.0	[3, 0, 0, 1, 2, 1, 1, 2, 0, 0]
-support	1.7	0.9	[1, 1, 1, 2, 1, 3, 3, 3, 1, 1]
-supported	1.3	0.45826	[2, 1, 2, 1, 1, 2, 1, 1, 1, 1]
-supporter	1.1	0.3	[1, 1, 1, 1, 1, 2, 1, 1, 1, 1]
-supporters	1.9	0.7	[1, 1, 1, 2, 2, 3, 2, 2, 3, 2]
-supporting	1.9	0.9434	[3, 2, 1, 1, 3, 3, 1, 1, 3, 1]
-supportive	1.2	0.4	[1, 1, 1, 1, 1, 2, 2, 1, 1, 1]
-supportiveness	1.5	1.11803	[3, 1, 2, 1, 3, 2, 2, 1, -1, 1]
-supports	1.5	0.67082	[2, 1, 2, 0, 2, 2, 2, 1, 1, 2]
-supremacies	0.8	1.72047	[3, -2, 3, 0, 0, 2, -1, 3, 0, 0]
-supremacist	0.5	2.15639	[3, 2, -3, 1, 2, 2, 2, -2, 1, -3]
-supremacists	-1.0	1.89737	[-4, -2, -1, -3, -2, 2, 2, 0, 0, -2]
-supremacy	0.2	1.77764	[-1, -2, 0, 3, 2, 0, -3, 0, 1, 2]
-suprematists	0.4	1.56205	[2, 1, 0, 0, 2, 2, 2, -2, -1, -2]
-supreme	2.6	1.11355	[2, 3, 2, 1, 4, 2, 1, 3, 4, 4]
-supremely	2.7	1.00499	[2, 4, 1, 4, 2, 4, 2, 3, 2, 3]
-supremeness	2.3	0.64031	[1, 2, 2, 3, 3, 2, 2, 3, 3, 2]
-supremer	2.3	1.1	[4, 3, 3, 0, 1, 2, 3, 2, 3, 2]
-supremest	2.2	1.98997	[4, 3, 1, 0, 4, 4, -2, 3, 1, 4]
-supremo	1.9	1.3	[1, 0, 3, 0, 4, 3, 1, 3, 2, 2]
-supremos	1.3	0.78102	[0, 2, 2, 1, 0, 2, 2, 1, 2, 1]
-sure	1.3	0.64031	[1, 1, 3, 1, 1, 2, 1, 1, 1, 1]
-surefire	1.0	0.7746	[1, 1, 0, 2, 2, 1, 0, 1, 2, 0]
-surefooted	1.9	0.83066	[0, 3, 2, 2, 2, 2, 1, 2, 3, 2]
-surefootedly	1.6	0.91652	[1, 1, 2, 0, 2, 1, 3, 3, 1, 2]
-surefootedness	1.5	1.20416	[2, 1, 4, 1, 0, 3, 2, 1, 1, 0]
-surely	1.9	0.7	[2, 2, 2, 1, 1, 1, 3, 2, 3, 2]
-sureness	2.0	0.7746	[2, 3, 2, 1, 2, 1, 3, 3, 2, 1]
-surer	1.2	1.32665	[1, 1, 3, 1, 3, 2, 1, -2, 1, 1]
-surest	1.3	0.78102	[2, 0, 2, 2, 2, 1, 0, 1, 1, 2]
-sureties	1.3	0.9	[2, 0, 2, 0, 2, 2, 1, 2, 0, 2]
-surety	1.0	0.44721	[1, 1, 1, 1, 1, 0, 1, 1, 2, 1]
-suretyship	-0.1	1.51327	[-1, 0, 0, -2, -1, 2, -2, 3, 0, 0]
-suretyships	0.4	0.66332	[0, 0, 0, 1, 0, 0, 1, 0, 0, 2]
-surprisal	1.5	0.80623	[3, 1, 1, 2, 1, 2, 2, 1, 2, 0]
-surprisals	0.7	1.1	[0, 0, 0, 0, 0, 0, 0, 2, 2, 3]
-surprise	1.1	1.04403	[0, 2, 0, 2, 3, 0, 1, 1, 2, 0]
-surprised	0.9	0.9434	[2, 0, 0, 0, 0, 2, 2, 1, 2, 0]
-surpriser	0.6	0.66332	[2, 0, 0, 0, 0, 1, 1, 1, 1, 0]
-surprisers	0.3	1.00499	[2, 0, 1, 1, 0, 0, -2, 1, 0, 0]
-surprises	0.9	0.7	[2, 0, 0, 0, 1, 1, 2, 1, 1, 1]
-surprising	1.1	0.9434	[1, 1, 1, 0, 0, 2, 0, 1, 3, 2]
-surprisingly	1.2	0.87178	[1, 0, 2, 0, 0, 2, 2, 1, 2, 2]
-survived	2.3	0.78102	[3, 4, 2, 2, 2, 1, 2, 3, 2, 2]
-surviving	1.2	0.87178	[1, 3, 1, 0, 2, 0, 1, 1, 1, 2]
-survivor	1.5	1.0247	[1, 3, 2, 3, 1, 0, 0, 1, 2, 2]
-suspect	-1.2	0.9798	[0, -1, -1, -2, -2, -2, 1, -1, -2, -2]
-suspected	-0.9	1.13578	[-1, 0, -1, -2, -1, -1, -2, 2, -2, -1]
-suspecting	-0.7	1.34536	[-1, 2, -1, -1, -1, 1, -2, -1, -3, 0]
-suspects	-1.4	0.91652	[-2, -2, -2, -1, -2, -1, -2, -2, 1, -1]
-suspend	-1.3	0.64031	[0, -2, -1, -2, -1, -1, -2, -1, -2, -1]
-suspended	-2.1	0.83066	[-2, -1, -2, -3, -3, -1, -3, -1, -2, -3]
-suspicion	-1.6	0.91652	[-2, -2, -1, -2, 1, -2, -2, -2, -2, -2]
-suspicions	-1.5	0.67082	[-1, -2, -1, -2, -1, -1, -3, -1, -2, -1]
-suspicious	-1.5	0.67082	[-1, -2, -1, -1, -2, -1, -2, -1, -3, -1]
-suspiciously	-1.7	0.45826	[-2, -2, -1, -2, -1, -2, -2, -1, -2, -2]
-suspiciousness	-1.2	1.46969	[-2, -3, -2, -1, -1, 1, 2, -2, -2, -2]
-sux	-1.5	0.92195	[-1, -1, -2, -1, -2, -1, -3, 0, -3, -1]
-swear	-0.2	1.53623	[-2, 2, -1, 1, 1, 0, -1, -2, 2, -2]
-swearing	-1.0	1.09545	[0, -2, -1, -1, -2, 0, 1, -3, -1, -1]
-swears	0.2	1.4	[1, -2, 2, 0, 1, -2, -1, 2, 1, 0]
-sweet	2.0	0.63246	[1, 2, 2, 2, 3, 3, 2, 1, 2, 2]
-sweet<3	3.0	0.44721	[3, 3, 3, 3, 4, 2, 3, 3, 3, 3]
-sweetheart	3.3	1.00499	[4, 1, 3, 4, 4, 4, 2, 3, 4, 4]
-sweethearts	2.8	0.87178	[2, 2, 2, 4, 3, 2, 4, 3, 4, 2]
-sweetie	2.2	0.6	[2, 3, 3, 2, 1, 3, 2, 2, 2, 2]
-sweeties	2.1	0.9434	[1, 2, 2, 3, 2, 1, 2, 4, 3, 1]
-sweetly	2.1	0.7	[1, 2, 2, 2, 2, 2, 1, 3, 3, 3]
-sweetness	2.2	0.74833	[3, 2, 3, 1, 2, 2, 3, 3, 2, 1]
-sweets	2.2	0.6	[2, 1, 3, 2, 2, 2, 3, 2, 3, 2]
-swift	0.8	0.6	[1, 0, 1, 1, 0, 2, 0, 1, 1, 1]
-swiftly	1.2	0.9798	[0, 3, 1, 0, 1, 1, 1, 3, 1, 1]
-swindle	-2.4	1.0198	[-1, -4, -1, -3, -3, -2, -2, -2, -4, -2]
-swindles	-1.5	0.92195	[0, -2, -2, -3, -2, -1, -1, 0, -2, -2]
-swindling	-2.0	1.0	[-2, -2, -2, -4, -1, 0, -3, -2, -2, -2]
-sympathetic	2.3	0.64031	[3, 3, 2, 2, 3, 3, 2, 2, 1, 2]
-sympathy	1.5	1.11803	[-1, 2, 3, 2, 1, 1, 1, 2, 1, 3]
-talent	1.8	1.07703	[3, 1, 2, 2, 0, 3, 3, 2, 2, 0]
-talented	2.3	0.64031	[1, 2, 2, 3, 2, 3, 3, 2, 3, 2]
-talentless	-1.6	0.4899	[-2, -2, -2, -1, -2, -1, -1, -1, -2, -2]
-talents	2.0	1.18322	[2, 4, 1, 2, 0, 2, 4, 2, 2, 1]
-tantrum	-1.8	1.16619	[-3, -2, -2, -3, -1, 0, -1, 0, -3, -3]
-tantrums	-1.5	1.36015	[-1, -2, -4, -2, -2, -1, -1, 0, 1, -3]
-tard	-2.5	0.92195	[-3, -3, -3, -2, -2, -3, -1, -4, -1, -3]
-tears	-0.9	1.13578	[0, -2, -2, -1, -1, -2, -2, 1, 1, -1]
-teas	0.3	0.45826	[1, 0, 0, 0, 0, 1, 0, 1, 0, 0]
-tease	-1.3	0.9	[0, -1, -1, -2, -1, 0, -3, -2, -1, -2]
-teased	-1.2	0.87178	[0, -2, -2, -1, -1, -1, 0, -3, -1, -1]
-teasel	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
-teaseled	-0.8	0.74833	[-1, 0, -1, 0, 0, -1, -2, -1, -2, 0]
-teaseler	-0.8	0.87178	[0, 0, -2, 0, 0, -1, -2, -1, -2, 0]
-teaselers	-1.2	1.249	[0, -3, 0, 0, 0, -3, -2, -2, -2, 0]
-teaseling	-0.4	0.91652	[-1, 0, -3, 0, 0, 0, 0, 0, 0, 0]
-teaselled	-0.4	0.91652	[0, -3, 0, 0, 0, 0, -1, 0, 0, 0]
-teaselling	-0.2	0.4	[0, 0, 0, 0, -1, 0, -1, 0, 0, 0]
-teasels	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, -1, 0]
-teaser	-1.0	1.18322	[0, -1, -3, -1, -1, -1, 0, -3, -1, 1]
-teasers	-0.7	1.1	[-1, -2, -3, -1, 0, 0, -1, 1, 0, 0]
-teases	-1.2	0.74833	[-1, -1, 0, -1, -2, -1, -3, -1, -1, -1]
-teashops	0.2	0.4	[0, 1, 0, 1, 0, 0, 0, 0, 0, 0]
-teasing	-0.3	1.1	[0, 0, 1, 1, -1, 0, 0, 0, -1, -3]
-teasingly	-0.4	1.11355	[0, 1, 1, 0, -2, 0, -2, 0, -2, 0]
-teaspoon	0.2	0.4	[0, 0, 0, 0, 0, 0, 1, 0, 1, 0]
-teaspoonful	0.2	0.4	[0, 0, 0, 1, 0, 0, 1, 0, 0, 0]
-teaspoonfuls	0.4	0.8	[2, 0, 0, 0, 0, 0, 0, 0, 2, 0]
-teaspoons	0.5	0.80623	[0, 0, 0, 2, 0, 0, 1, 2, 0, 0]
-teaspoonsful	0.3	0.9	[2, 0, 0, 0, 0, 2, 0, -1, 0, 0]
-temper	-1.8	0.4	[-1, -2, -2, -2, -2, -2, -2, -2, -1, -2]
-tempers	-1.3	0.64031	[-1, -1, 0, -1, -1, -2, -2, -2, -1, -2]
-tendered	0.5	0.92195	[0, 0, 2, 1, -1, -1, 1, 1, 1, 1]
-tenderer	0.6	0.66332	[0, 1, 1, 0, 0, 0, 2, 1, 1, 0]
-tenderers	1.2	0.9798	[2, 0, 0, 1, 0, 2, 3, 1, 1, 2]
-tenderest	1.4	1.56205	[2, 1, 3, -1, 0, 2, 2, 2, -1, 4]
-tenderfeet	-0.4	0.91652	[-1, -1, 0, 0, -1, 0, -1, -2, 1, 1]
-tenderfoot	-0.1	0.53852	[-1, 1, 0, 0, 0, 0, 0, -1, 0, 0]
-tenderfoots	-0.5	1.11803	[1, -1, 0, 0, 0, -1, -1, 1, -3, -1]
-tenderhearted	1.5	1.0247	[2, 2, 1, 2, 3, 1, 1, -1, 2, 2]
-tenderheartedly	2.7	0.64031	[2, 2, 2, 3, 3, 3, 3, 4, 3, 2]
-tenderheartedness	0.7	1.48661	[1, 3, 2, 2, -1, -1, 1, -2, 1, 1]
-tenderheartednesses	2.8	0.74833	[2, 3, 3, 2, 3, 3, 4, 4, 2, 2]
-tendering	0.6	0.66332	[0, 0, 1, 1, 1, 0, 0, 1, 2, 0]
-tenderization	0.2	0.74833	[-1, 2, 0, 0, 0, 1, 0, 0, 0, 0]
-tenderize	0.1	0.53852	[0, 0, 0, 0, 0, -1, 0, 1, 0, 1]
-tenderized	0.1	0.53852	[0, 1, 0, 1, 0, 0, -1, 0, 0, 0]
-tenderizer	0.4	0.66332	[0, 1, 0, 1, 0, 0, 2, 0, 0, 0]
-tenderizes	0.3	0.45826	[0, 1, 0, 1, 0, 0, 1, 0, 0, 0]
-tenderizing	0.3	0.45826	[1, 1, 0, 0, 0, 1, 0, 0, 0, 0]
-tenderloin	-0.2	0.74833	[0, 0, 0, 0, -2, 0, 1, 0, -1, 0]
-tenderloins	0.4	0.66332	[1, 0, 0, 0, 2, 0, 0, 1, 0, 0]
-tenderly	1.8	0.74833	[2, 1, 2, 1, 3, 2, 1, 2, 3, 1]
-tenderness	1.8	0.4	[2, 2, 1, 2, 2, 2, 2, 1, 2, 2]
-tendernesses	0.9	1.44568	[1, 2, 1, 1, 3, -1, -2, 2, 2, 0]
-tenderometer	0.2	0.4	[1, 0, 0, 0, 0, 1, 0, 0, 0, 0]
-tenderometers	0.2	0.4	[0, 0, 1, 0, 0, 0, 0, 0, 1, 0]
-tenders	0.6	0.8	[0, 2, 0, 1, 1, 1, -1, 0, 1, 1]
-tense	-1.4	0.4899	[-1, -1, -1, -1, -1, -2, -1, -2, -2, -2]
-tensed	-1.0	0.44721	[-1, 0, -1, -1, -1, -1, -2, -1, -1, -1]
-tensely	-1.2	0.6	[-1, -2, -2, -2, -1, 0, -1, -1, -1, -1]
-tenseness	-1.5	0.67082	[-1, -1, -1, -1, -1, -2, -2, -1, -2, -3]
-tenser	-1.5	0.67082	[-2, -2, -1, -2, -1, -1, -3, -1, -1, -1]
-tenses	-0.9	1.04403	[-1, -3, 0, 0, 0, -1, 0, -2, -2, 0]
-tensest	-1.2	1.07703	[-2, 0, -2, -2, -2, 0, 1, -1, -2, -2]
-tensing	-1.0	0.44721	[-1, -2, -1, 0, -1, -1, -1, -1, -1, -1]
-tension	-1.3	1.00499	[-2, -1, -1, -1, -1, -2, -2, -3, 1, -1]
-tensional	-0.8	0.74833	[-1, 0, -1, -1, -1, -2, 1, -1, -1, -1]
-tensioned	-0.4	1.11355	[-2, 0, -1, 2, -1, 0, -1, -1, -1, 1]
-tensioner	-1.6	0.8	[-1, -3, -2, -2, -2, 0, -1, -2, -1, -2]
-tensioners	-0.9	1.04403	[-1, 0, -2, -2, -1, 1, -2, 0, 0, -2]
-tensioning	-1.4	1.0198	[-1, -1, -1, -1, 0, -2, -3, -3, 0, -2]
-tensionless	0.6	0.8	[1, 1, 1, -1, 0, 0, 0, 2, 1, 1]
-tensions	-1.7	0.78102	[-1, -3, -1, -1, -2, -2, -3, -1, -2, -1]
-terrible	-2.1	0.9434	[-1, -3, -2, -1, -3, -1, -2, -2, -4, -2]
-terribleness	-1.9	1.81384	[3, -3, -3, -3, -3, -1, -2, -1, -3, -3]
-terriblenesses	-2.6	0.4899	[-2, -3, -3, -2, -3, -2, -2, -3, -3, -3]
-terribly	-2.6	0.4899	[-3, -3, -3, -2, -2, -3, -3, -2, -2, -3]
-terrific	2.1	1.81384	[4, 3, 4, 1, -1, -1, 4, 2, 2, 3]
-terrifically	1.7	1.95192	[2, 2, 4, 2, 3, 3, -2, 3, -2, 2]
-terrified	-3.0	0.63246	[-2, -3, -3, -3, -4, -3, -4, -2, -3, -3]
-terrifies	-2.6	1.0198	[-2, -4, -3, -3, -4, -1, -2, -3, -1, -3]
-terrify	-2.3	0.78102	[-3, -3, -2, -2, -1, -4, -2, -2, -2, -2]
-terrifying	-2.7	0.78102	[-4, -3, -3, -2, -2, -2, -4, -2, -3, -2]
-terror	-2.4	1.2	[-3, -4, -2, -1, 0, -4, -3, -2, -2, -3]
-terrorise	-3.1	0.83066	[-2, -3, -4, -4, -3, -3, -2, -4, -2, -4]
-terrorised	-3.3	0.64031	[-3, -3, -4, -3, -2, -4, -4, -3, -4, -3]
-terrorises	-3.3	0.45826	[-3, -3, -4, -3, -3, -4, -4, -3, -3, -3]
-terrorising	-3.0	0.44721	[-3, -3, -3, -3, -2, -3, -4, -3, -3, -3]
-terrorism	-3.6	0.4899	[-4, -3, -4, -4, -4, -3, -3, -4, -3, -4]
-terrorisms	-3.2	0.6	[-4, -4, -4, -3, -3, -3, -2, -3, -3, -3]
-terrorist	-3.7	0.45826	[-4, -3, -4, -4, -4, -3, -4, -4, -3, -4]
-terroristic	-3.3	0.78102	[-4, -3, -2, -3, -4, -3, -4, -2, -4, -4]
-terrorists	-3.1	0.9434	[-3, -4, -2, -2, -4, -2, -2, -4, -4, -4]
-terrorization	-2.7	0.9	[-4, -4, -3, -2, -2, -4, -2, -2, -2, -2]
-terrorize	-3.3	0.78102	[-4, -4, -3, -3, -4, -2, -2, -4, -3, -4]
-terrorized	-3.1	0.7	[-2, -3, -2, -4, -4, -4, -3, -3, -3, -3]
-terrorizes	-3.1	0.53852	[-2, -3, -3, -4, -3, -4, -3, -3, -3, -3]
-terrorizing	-3.0	1.0	[-3, -1, -4, -4, -4, -3, -2, -3, -2, -4]
-terrorless	0.9	1.04403	[-2, 2, 1, 2, 1, 1, 1, 1, 1, 1]
-terrors	-2.6	0.4899	[-2, -3, -3, -3, -2, -2, -3, -2, -3, -3]
-thank	1.5	0.92195	[3, 1, 1, 0, 1, 1, 2, 3, 1, 2]
-thanked	1.9	1.22066	[1, 3, 1, 1, 1, 1, 4, 4, 2, 1]
-thankful	2.7	0.78102	[4, 2, 2, 3, 2, 4, 3, 3, 2, 2]
-thankfuller	1.9	0.53852	[2, 2, 1, 2, 2, 2, 1, 2, 3, 2]
-thankfullest	2.0	1.0	[3, 1, 1, 4, 1, 2, 2, 2, 3, 1]
-thankfully	1.8	0.6	[2, 1, 2, 1, 2, 3, 2, 2, 1, 2]
-thankfulness	2.1	1.44568	[3, 3, 4, 2, 2, 1, -1, 1, 2, 4]
-thanks	1.9	1.04403	[1, 1, 1, 1, 3, 2, 1, 4, 3, 2]
-thief	-2.4	0.66332	[-3, -2, -2, -2, -2, -4, -2, -2, -3, -2]
-thieve	-2.2	0.4	[-2, -2, -2, -3, -2, -2, -3, -2, -2, -2]
-thieved	-1.4	1.28062	[-1, -2, -3, -1, -2, 2, -2, -1, -2, -2]
-thieveries	-2.1	0.53852	[-2, -3, -2, -3, -1, -2, -2, -2, -2, -2]
-thievery	-2.0	0.89443	[-2, -2, -2, -1, -1, -3, -1, -2, -4, -2]
-thieves	-2.3	0.78102	[-3, -2, -2, -4, -1, -2, -2, -2, -3, -2]
-thorny	-1.1	0.83066	[1, -1, -1, -1, -1, -1, -1, -2, -2, -2]
-thoughtful	1.6	0.4899	[2, 2, 1, 1, 1, 1, 2, 2, 2, 2]
-thoughtfully	1.7	0.64031	[2, 1, 1, 3, 1, 2, 1, 2, 2, 2]
-thoughtfulness	1.9	0.53852	[1, 2, 1, 2, 2, 3, 2, 2, 2, 2]
-thoughtless	-2.0	0.63246	[-2, -1, -3, -3, -2, -1, -2, -2, -2, -2]
-threat	-2.4	0.66332	[-2, -3, -2, -2, -2, -4, -3, -2, -2, -2]
-threaten	-1.6	1.56205	[-4, -1, -3, -2, 1, -3, -1, 1, -2, -2]
-threatened	-2.0	0.63246	[-2, -2, -3, -2, -2, -1, -2, -3, -1, -2]
-threatener	-1.4	1.68523	[-2, -2, -3, -2, 3, 0, -2, -3, -1, -2]
-threateners	-1.8	0.74833	[-3, -1, -2, -1, -1, -3, -2, -2, -2, -1]
-threatening	-2.4	0.8	[-3, -3, -2, -3, -2, -1, -3, -1, -3, -3]
-threateningly	-2.2	0.6	[-2, -2, -2, -2, -2, -2, -2, -2, -4, -2]
-threatens	-1.6	1.56205	[-2, -2, -2, 1, -4, -3, -3, -1, 1, -1]
-threating	-2.0	0.44721	[-3, -2, -2, -2, -1, -2, -2, -2, -2, -2]
-threats	-1.8	0.74833	[-1, -1, -1, -2, -2, -2, -3, -3, -2, -1]
-thrill	1.5	1.11803	[2, 2, 2, 0, 1, -1, 2, 3, 2, 2]
-thrilled	1.9	1.81384	[3, -1, 3, 3, 1, -2, 3, 3, 3, 3]
-thriller	0.4	1.2	[0, 0, 3, 1, 1, -2, 0, 1, 0, 0]
-thrillers	0.1	0.83066	[0, 2, 0, 0, 0, -1, 0, -1, 0, 1]
-thrilling	2.1	1.04403	[3, 0, 2, 3, 1, 3, 3, 2, 1, 3]
-thrillingly	2.0	0.7746	[0, 2, 2, 3, 3, 2, 2, 2, 2, 2]
-thrills	1.5	0.92195	[2, 3, 1, 2, 0, 2, 1, 0, 2, 2]
-thwarted	-0.1	1.75784	[1, -2, -3, 0, 2, 0, 2, -2, -1, 2]
-thwarting	-0.7	0.78102	[0, 0, -1, -1, -1, -2, 1, -1, -1, -1]
-thwarts	-0.4	1.28062	[-2, 0, 0, -2, 0, 1, 2, 0, -1, -2]
-ticked	-1.8	0.6	[-2, -1, -1, -2, -2, -1, -2, -2, -3, -2]
-timid	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -2, -1, -1, -1]
-timider	-1.0	0.44721	[-1, -2, -1, -1, -1, 0, -1, -1, -1, -1]
-timidest	-0.9	0.7	[0, -1, 0, -1, 0, -1, -1, -2, -1, -2]
-timidities	-0.7	0.64031	[-1, -1, -1, 0, -2, 0, -1, 0, 0, -1]
-timidity	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -2, -1, -1]
-timidly	-0.7	0.78102	[0, -1, -1, -1, -1, 1, 0, -1, -2, -1]
-timidness	-1.0	0.89443	[-1, -2, -1, 0, -1, -2, 1, -2, -1, -1]
-timorous	-0.8	0.9798	[-2, -1, -1, -1, -1, -2, -1, 1, 1, -1]
-tired	-1.9	0.7	[-2, -1, -2, -3, -2, -3, -1, -1, -2, -2]
-tits	-0.9	0.53852	[-1, -1, -2, -1, -1, -1, 0, -1, 0, -1]
-tolerance	1.2	1.53623	[2, 3, 2, 2, -2, 1, 1, 3, -1, 1]
-tolerances	0.3	0.9	[-1, 1, 0, 0, 1, 2, 0, -1, 1, 0]
-tolerant	1.1	0.53852	[1, 2, 1, 1, 1, 1, 1, 1, 0, 2]
-tolerantly	0.4	1.2	[0, 1, 1, 1, 0, -3, 1, 1, 1, 1]
-toothless	-1.4	1.0198	[-1, -4, -1, -2, -1, 0, -1, -2, -1, -1]
-top	0.8	0.87178	[1, 3, 1, 1, 1, 0, 0, 1, 0, 0]
-tops	2.3	1.00499	[3, 3, 3, 0, 2, 2, 3, 3, 1, 3]
-torn	-1.0	1.0	[-1, -1, -1, 0, -1, -1, -3, -2, 1, -1]
-torture	-2.9	1.51327	[-4, -4, -3, -4, 1, -2, -3, -2, -4, -4]
-tortured	-2.6	1.0198	[-4, -1, -2, -2, -4, -3, -2, -2, -4, -2]
-torturer	-2.3	1.18743	[-4, -1, -1, -2, -4, -1, -2, -2, -4, -2]
-torturers	-3.5	0.67082	[-4, -4, -3, -3, -4, -4, -4, -2, -3, -4]
-tortures	-2.5	0.92195	[-2, -3, -2, -4, -1, -3, -2, -4, -2, -2]
-torturing	-3.0	0.89443	[-4, -4, -4, -2, -3, -2, -4, -2, -2, -3]
-torturous	-2.7	0.78102	[-3, -3, -1, -3, -4, -2, -2, -3, -3, -3]
-torturously	-2.2	1.6	[2, -3, -3, -2, -3, -2, -4, -3, -1, -3]
-totalitarian	-2.1	1.3	[0, -4, -3, 0, -3, -2, -3, -1, -2, -3]
-totalitarianism	-2.7	1.18743	[-2, -3, 0, -4, -2, -4, -4, -2, -3, -3]
-tough	-0.5	1.43178	[0, -2, 0, 0, 1, 2, -1, -2, -3, 0]
-toughed	0.7	0.64031	[1, 1, 0, 1, 1, 0, 2, 1, 0, 0]
-toughen	0.1	1.04403	[0, 0, 1, 0, 1, 0, 2, 0, -2, -1]
-toughened	0.1	0.53852	[1, 0, 0, 0, 0, -1, 1, 0, 0, 0]
-toughening	0.9	0.83066	[0, 2, 2, 1, 1, 0, 1, 0, 0, 2]
-toughens	-0.2	1.16619	[1, -1, 0, 1, 0, -2, -2, 1, -1, 1]
-tougher	0.7	1.00499	[1, 1, -1, 0, 2, 0, 2, 2, 0, 0]
-toughest	-0.3	1.84662	[2, 1, -1, -3, 0, -2, 2, -2, 2, -2]
-toughie	-0.7	0.64031	[-1, 1, 0, -1, -1, -1, -1, -1, -1, -1]
-toughies	-0.6	0.66332	[-1, -1, -1, 0, 0, -1, 1, -1, -1, -1]
-toughing	-0.5	1.20416	[-1, 0, -2, 0, 0, -2, 2, 0, -2, 0]
-toughish	-1.0	1.0	[0, -1, 0, -2, -2, -1, 1, -2, -2, -1]
-toughly	-1.1	0.83066	[-1, 0, 0, -1, 0, -1, -2, -2, -2, -2]
-toughness	-0.2	1.07703	[0, 0, -1, -2, 0, 1, 1, 1, -2, 0]
-toughnesses	0.3	1.18743	[1, 2, -1, 0, 1, 1, -2, 1, -1, 1]
-toughs	-0.8	1.16619	[0, 0, -1, 0, -1, -3, -2, 1, 0, -2]
-toughy	-0.5	1.11803	[-1, -2, -1, 0, -1, -1, 1, -1, 2, -1]
-tout	-0.5	0.67082	[-1, 0, -2, -1, 0, 0, -1, 0, 0, 0]
-touted	-0.2	0.9798	[-1, 2, 0, -2, -1, 0, 0, 0, 0, 0]
-touting	-0.7	0.64031	[0, 0, -1, -1, -1, -1, 0, -2, 0, -1]
-touts	-0.1	0.7	[1, 1, 0, -1, 0, -1, -1, 0, 0, 0]
-tragedian	-0.5	0.67082	[-2, 0, -1, 0, 0, -1, 0, -1, 0, 0]
-tragedians	-1.0	1.18322	[-1, 0, -2, -1, 0, -3, 0, 0, 0, -3]
-tragedienne	-0.4	0.4899	[0, 0, -1, -1, 0, 0, -1, -1, 0, 0]
-tragediennes	-1.4	1.28062	[0, -3, 0, -1, -3, 0, -2, -3, 0, -2]
-tragedies	-1.9	1.86815	[-3, -4, -2, 2, -3, -4, -2, 1, -2, -2]
-tragedy	-3.4	1.0198	[-4, -4, -4, -4, -2, -3, -1, -4, -4, -4]
-tragic	-2.0	1.94936	[-1, -3, -4, -3, -3, -4, -2, 1, 2, -3]
-tragical	-2.4	1.11355	[-3, -3, -3, -2, -1, -3, -4, -3, 0, -2]
-tragically	-2.7	1.48661	[-4, -4, -4, -2, -1, -4, -1, 0, -3, -4]
-tragicomedy	0.2	0.9798	[0, -2, 0, 0, 0, 2, 1, 1, 0, 0]
-tragicomic	-0.2	0.74833	[0, -1, 1, 0, 0, 0, -2, 0, 0, 0]
-tragics	-2.2	0.74833	[-3, -2, -4, -1, -2, -2, -2, -2, -2, -2]
-tranquil	0.2	1.77764	[2, 1, -1, 2, -3, 3, -1, 1, -1, -1]
-tranquiler	1.9	0.7	[2, 1, 2, 2, 3, 3, 2, 2, 1, 1]
-tranquilest	1.6	1.35647	[1, 2, 2, 2, 0, 2, -1, 4, 3, 1]
-tranquilities	1.5	1.36015	[3, 2, 4, -1, 1, 0, 2, 2, 1, 1]
-tranquility	1.8	1.16619	[3, 2, 1, 2, 3, 4, 1, 1, 1, 0]
-tranquilize	0.3	1.00499	[0, -2, 1, -1, 1, 1, 1, 0, 1, 1]
-tranquilized	-0.2	1.32665	[-2, 0, 1, 0, 1, 2, 0, -2, -2, 0]
-tranquilizer	-0.1	0.9434	[0, 1, -1, 0, -1, 0, -2, 1, 1, 0]
-tranquilizers	-0.4	0.8	[0, 0, 0, -2, -1, -1, -1, 1, 0, 0]
-tranquilizes	-0.1	0.9434	[-2, 0, 1, 0, 1, 1, 0, -1, -1, 0]
-tranquilizing	-0.5	0.67082	[-1, 0, 0, -1, -1, -1, 1, 0, -1, -1]
-tranquillest	0.8	1.4	[1, 1, 2, 3, 1, 1, 0, -1, -2, 2]
-tranquillities	0.5	1.20416	[-2, 1, 2, 0, 2, 1, 0, -1, 1, 1]
-tranquillity	1.8	1.07703	[1, 2, 2, 2, 3, 3, 2, -1, 2, 2]
-tranquillized	-0.2	1.07703	[0, 1, 0, 0, -3, 0, 1, 0, -1, 0]
-tranquillizer	-0.1	0.7	[0, 1, 0, 0, -1, 0, 1, 0, -1, -1]
-tranquillizers	-0.2	0.74833	[0, 0, 0, -2, 1, 0, 0, 0, -1, 0]
-tranquillizes	0.1	0.7	[-1, -1, 0, 0, 1, 1, 1, 0, 0, 0]
-tranquillizing	0.8	0.87178	[1, 2, 0, 2, 0, 0, 2, 0, 0, 1]
-tranquilly	1.2	0.87178	[2, 2, 1, 2, -1, 2, 1, 1, 1, 1]
-tranquilness	1.5	1.20416	[3, 3, 1, 2, 2, 2, 0, -1, 1, 2]
-trap	-1.3	0.78102	[-1, -1, -2, 0, -1, -1, -2, -1, -1, -3]
-trapped	-2.4	0.91652	[-3, -2, -3, -1, -3, -1, -2, -2, -4, -3]
-trauma	-1.8	1.249	[-2, -2, -3, -1, -2, 1, -2, -4, -1, -2]
-traumas	-2.2	1.6	[-3, -3, -2, -4, 0, -1, -4, -3, 1, -3]
-traumata	-1.7	1.34536	[-2, -3, -2, 0, -2, 1, -4, -2, -1, -2]
-traumatic	-2.7	1.00499	[-2, -4, -2, -1, -4, -3, -2, -3, -4, -2]
-traumatically	-2.8	0.6	[-4, -2, -3, -2, -2, -3, -3, -3, -3, -3]
-traumatise	-2.8	0.6	[-4, -3, -3, -2, -2, -3, -2, -3, -3, -3]
-traumatised	-2.4	0.91652	[-4, -4, -2, -2, -1, -2, -3, -2, -2, -2]
-traumatises	-2.2	0.87178	[-3, -4, -2, -2, -1, -2, -3, -1, -2, -2]
-traumatising	-1.9	1.86815	[-3, -3, -3, -1, -3, 1, -4, -2, 2, -3]
-traumatism	-2.4	0.4899	[-3, -2, -3, -2, -2, -2, -2, -3, -3, -2]
-traumatization	-3.0	1.0	[-4, -4, -4, -2, -2, -2, -4, -4, -2, -2]
-traumatizations	-2.2	1.16619	[-3, -2, -4, 0, -1, -2, -4, -2, -2, -2]
-traumatize	-2.4	0.66332	[-3, -3, -2, -4, -2, -2, -2, -2, -2, -2]
-traumatized	-1.7	1.41774	[-1, -2, -2, -2, 2, -4, -2, -2, -2, -2]
-traumatizes	-1.4	1.42829	[-2, -1, -2, -2, 2, -4, -1, -2, -1, -1]
-traumatizing	-2.3	1.61555	[-4, -2, -2, -3, -2, -4, -4, 1, 0, -3]
-travesty	-2.7	1.48661	[-3, -4, 0, -2, -4, -3, -4, 0, -3, -4]
-treason	-1.9	1.75784	[-3, -3, -2, -3, -3, 1, -2, -3, -3, 2]
-treasonous	-2.7	1.34536	[-3, -3, -3, -4, -3, -4, -2, 1, -3, -3]
-treasurable	2.5	0.67082	[2, 3, 3, 3, 2, 4, 2, 2, 2, 2]
-treasure	1.2	1.16619	[3, 1, 3, 2, 0, 2, 1, 0, 0, 0]
-treasured	2.6	0.66332	[3, 3, 2, 3, 3, 2, 1, 3, 3, 3]
-treasurer	0.5	0.67082	[1, 0, 0, 0, 1, 0, 0, 0, 1, 2]
-treasurers	0.4	0.66332	[0, 0, 0, 0, 1, 1, 2, 0, 0, 0]
-treasurership	0.4	0.66332	[0, 0, 2, 0, 1, 0, 1, 0, 0, 0]
-treasurerships	1.2	0.87178	[2, 0, 2, 0, 2, 1, 2, 2, 1, 0]
-treasures	1.8	1.32665	[3, 3, 0, 1, 1, 4, 0, 3, 2, 1]
-treasuries	0.9	1.04403	[0, 0, 1, 3, 2, 2, 0, 1, 0, 0]
-treasuring	2.1	0.7	[2, 1, 3, 1, 3, 2, 2, 2, 2, 3]
-treasury	0.8	1.07703	[2, 3, 0, 0, 0, 0, 0, 1, 2, 0]
-treat	1.7	0.78102	[2, 2, 2, 0, 2, 1, 3, 2, 1, 2]
-tremble	-1.1	1.3	[-2, 0, -1, -2, -2, -2, 2, 0, -2, -2]
-trembled	-1.1	1.22066	[-1, 1, -1, -2, -2, -1, -3, -2, 1, -1]
-trembler	-0.6	1.28062	[-2, -2, -1, 0, -1, 2, 1, -2, -1, 0]
-tremblers	-1.0	0.63246	[-2, 0, -1, -1, 0, -2, -1, -1, -1, -1]
-trembles	-0.1	1.51327	[-1, -2, -1, 0, -1, 2, 2, -2, 2, 0]
-trembling	-1.5	0.92195	[-3, 0, -1, -3, -1, -1, -1, -2, -1, -2]
-trembly	-1.2	0.87178	[-2, 0, -1, -2, -2, -1, 0, 0, -2, -2]
-tremulous	-1.0	1.09545	[-1, -2, -1, -1, -1, -1, 2, -2, -2, -1]
-trick	-0.2	1.32665	[-1, 1, -2, -2, -1, 2, 0, 1, 1, -1]
-tricked	-0.6	0.91652	[-1, -1, -1, -1, 2, 0, -1, -1, -1, -1]
-tricker	-0.9	0.83066	[-2, 0, -1, -1, 1, -2, -1, -1, -1, -1]
-trickeries	-1.2	1.46969	[-2, -2, -1, -2, -1, 2, 1, -2, -3, -2]
-trickers	-1.4	0.66332	[-1, -3, -1, -2, -2, -1, -1, -1, -1, -1]
-trickery	-1.1	1.51327	[1, -1, -1, -2, -3, -2, -3, 2, -1, -1]
-trickie	-0.4	1.0198	[1, -1, 0, -1, -1, 1, -2, -1, 1, -1]
-trickier	-0.7	0.78102	[-1, -1, -1, 0, 1, -1, -1, -1, 0, -2]
-trickiest	-1.2	0.6	[-2, -2, 0, -1, -2, -1, -1, -1, -1, -1]
-trickily	-0.8	0.74833	[0, 1, -1, -1, -1, -1, -1, -1, -2, -1]
-trickiness	-1.2	0.9798	[-2, -1, -1, -2, -1, -2, 1, 0, -2, -2]
-trickinesses	-0.4	1.0198	[0, 2, 0, -2, -1, -1, 0, 0, -1, -1]
-tricking	0.1	1.37477	[0, -2, 2, -1, 2, -2, 0, 1, 1, 0]
-trickish	-1.0	0.44721	[-1, -2, 0, -1, -1, -1, -1, -1, -1, -1]
-trickishly	-0.7	1.55242	[-3, -2, -1, 2, -1, 2, -2, -1, 0, -1]
-trickishness	-0.4	1.28062	[-1, 1, -2, -1, -1, -1, 0, -2, 1, 2]
-trickled	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
-trickledown	-0.7	0.64031	[0, -1, 0, -1, -2, 0, 0, -1, -1, -1]
-trickles	0.2	0.4	[0, 0, 0, 1, 0, 0, 0, 0, 1, 0]
-trickling	-0.2	0.9798	[0, 0, -1, -2, -1, 2, 0, 0, 0, 0]
-trickly	-0.3	0.45826	[0, 0, -1, 0, 0, 0, 0, -1, 0, -1]
-tricks	-0.5	0.67082	[0, 0, -1, -1, 1, -1, -1, 0, -1, -1]
-tricksier	-0.5	0.67082	[-1, -1, 1, 0, -1, 0, 0, -1, -1, -1]
-tricksiness	-1.0	0.89443	[0, 0, -1, -1, -1, 0, -1, -2, -3, -1]
-trickster	-0.9	0.83066	[-1, -2, 0, -1, -2, -1, -1, 1, -1, -1]
-tricksters	-1.3	0.9	[-1, -2, -1, -2, 1, -2, -2, -1, -1, -2]
-tricksy	-0.8	0.9798	[-1, -1, -2, -1, 2, -1, -1, -1, -1, -1]
-tricky	-0.6	0.66332	[0, 0, -1, -1, 1, -1, -1, -1, -1, -1]
-trite	-0.8	0.4	[-1, -1, 0, 0, -1, -1, -1, -1, -1, -1]
-triumph	2.1	1.04403	[2, 4, 3, 3, 1, 3, 1, 2, 1, 1]
-triumphal	2.0	0.63246	[2, 3, 3, 2, 1, 2, 1, 2, 2, 2]
-triumphalisms	1.9	0.9434	[2, 1, 2, 2, 2, 0, 2, 2, 4, 2]
-triumphalist	0.5	1.20416	[1, 1, 2, 2, -1, -2, 0, 1, 0, 1]
-triumphalists	0.9	1.64012	[1, -1, 0, 0, 1, 3, -2, 3, 1, 3]
-triumphant	2.4	0.91652	[2, 3, 3, 3, 4, 1, 2, 1, 3, 2]
-triumphantly	2.3	1.00499	[3, 3, 3, 3, 1, 0, 3, 2, 2, 3]
-triumphed	2.2	1.4	[2, 3, 3, 3, 4, 3, 1, 1, -1, 3]
-triumphing	2.3	0.64031	[2, 2, 3, 2, 2, 3, 2, 3, 1, 3]
-triumphs	2.0	1.41421	[3, 2, 3, 3, 3, 1, -1, 1, 1, 4]
-trivial	-0.1	0.83066	[0, -1, -1, 0, 1, 0, 1, -1, 1, -1]
-trivialise	-0.8	1.16619	[-3, -1, -2, 0, 1, -1, -1, 1, -1, -1]
-trivialised	-0.8	1.6	[-2, 0, -2, 1, -1, 0, 1, 1, -4, -2]
-trivialises	-1.1	0.53852	[-1, -1, -1, 0, -1, -1, -1, -2, -2, -1]
-trivialising	-1.4	0.66332	[-2, -1, -2, -1, 0, -1, -2, -1, -2, -2]
-trivialities	-1.0	0.63246	[-2, -2, -1, -1, -1, 0, 0, -1, -1, -1]
-triviality	-0.5	1.11803	[-1, -1, -2, 0, -1, -1, 2, -1, 1, -1]
-trivialization	-0.9	1.04403	[-1, 2, -1, -1, -2, -2, -1, -1, -1, -1]
-trivializations	-0.7	1.18743	[-2, -1, -1, -2, 1, -1, -1, -1, 2, -1]
-trivialize	-1.1	0.53852	[0, -2, -2, -1, -1, -1, -1, -1, -1, -1]
-trivialized	-0.6	0.8	[-1, -1, 0, 0, -1, -1, 1, -1, 0, -2]
-trivializes	-1.0	0.7746	[-1, -1, -1, 0, -1, 0, -1, -1, -1, -3]
-trivializing	-0.6	1.95959	[-1, -1, -2, -1, -1, 2, -2, -4, 1, 3]
-trivially	0.4	1.56205	[-1, -1, -1, -1, 0, 3, 0, 2, 3, 0]
-trivium	-0.3	0.64031	[0, 0, -2, 0, 0, 0, 0, -1, 0, 0]
-trouble	-1.7	0.64031	[-2, -2, -1, -1, -3, -2, -1, -2, -1, -2]
-troubled	-2.0	0.44721	[-2, -2, -2, -1, -2, -3, -2, -2, -2, -2]
-troublemaker	-2.0	0.63246	[-3, -2, -3, -2, -2, -1, -1, -2, -2, -2]
-troublemakers	-2.2	0.74833	[-3, -3, -3, -1, -3, -1, -2, -2, -2, -2]
-troublemaking	-1.8	0.6	[-2, -1, -1, -2, -2, -2, -3, -2, -1, -2]
-troubler	-1.4	0.4899	[-1, -1, -2, -1, -1, -1, -2, -2, -2, -1]
-troublers	-1.9	0.3	[-2, -2, -2, -2, -1, -2, -2, -2, -2, -2]
-troubles	-2.0	0.44721	[-2, -2, -2, -1, -2, -3, -2, -2, -2, -2]
-troubleshoot	0.8	0.9798	[0, 0, 0, 2, 2, 2, 2, 0, 0, 0]
-troubleshooter	1.0	0.89443	[0, 0, 0, 1, 2, 2, 0, 1, 2, 2]
-troubleshooters	0.8	0.87178	[0, 0, 1, 2, 0, 1, 0, 2, 2, 0]
-troubleshooting	0.7	1.34536	[0, 2, 1, 1, -1, 2, 0, 2, -2, 2]
-troubleshoots	0.5	0.92195	[1, -1, 0, 0, 0, 0, 1, 0, 2, 2]
-troublesome	-2.3	0.78102	[-3, -2, -3, -2, -3, -3, -1, -2, -1, -3]
-troublesomely	-1.8	0.6	[-3, -1, -2, -2, -1, -2, -2, -2, -2, -1]
-troublesomeness	-1.9	0.7	[-2, -1, -2, -3, -2, -3, -1, -2, -1, -2]
-troubling	-2.5	0.67082	[-3, -3, -3, -3, -1, -2, -3, -2, -3, -2]
-troublous	-2.1	0.53852	[-2, -2, -2, -2, -2, -3, -2, -3, -1, -2]
-troublously	-2.1	1.22066	[-2, -3, -3, -3, -2, -1, 1, -2, -3, -3]
-trueness	2.1	0.9434	[2, 1, 1, 3, 3, 4, 2, 1, 2, 2]
-truer	1.5	0.67082	[1, 2, 1, 2, 1, 1, 2, 1, 3, 1]
-truest	1.9	0.83066	[2, 2, 2, 3, 3, 0, 2, 1, 2, 2]
-truly	1.9	0.9434	[4, 3, 1, 2, 2, 1, 1, 1, 2, 2]
-trust	2.3	1.26886	[0, 4, 3, 3, 4, 1, 2, 2, 1, 3]
-trustability	2.1	0.7	[1, 3, 3, 2, 2, 2, 1, 3, 2, 2]
-trustable	2.3	0.45826	[2, 2, 3, 2, 2, 3, 3, 2, 2, 2]
-trustbuster	-0.5	1.28452	[-3, -1, 0, 0, 0, 0, -2, 0, 2, -1]
-trusted	2.1	0.9434	[3, 2, 2, 1, 4, 1, 2, 2, 3, 1]
-trustee	1.0	0.89443	[2, 2, 0, 1, 1, 0, 2, 0, 2, 0]
-trustees	0.3	0.64031	[0, 1, 0, 0, 2, 0, 0, 0, 0, 0]
-trusteeship	0.5	0.67082	[0, 1, 1, 0, 0, 1, 0, 0, 2, 0]
-trusteeships	0.6	1.0198	[3, 0, 0, 0, 0, 0, 0, 2, 1, 0]
-truster	1.9	1.3	[2, 2, 1, 1, 4, 0, 3, 1, 4, 1]
-trustful	2.1	0.9434	[1, 2, 2, 1, 2, 2, 1, 3, 3, 4]
-trustfully	1.5	0.67082	[2, 1, 2, 1, 1, 3, 1, 2, 1, 1]
-trustfulness	2.1	0.83066	[3, 2, 3, 2, 3, 2, 2, 2, 0, 2]
-trustier	1.3	1.1	[1, 1, 1, 2, 0, 0, 3, 0, 3, 2]
-trusties	1.0	0.7746	[1, 1, 0, 2, 1, 0, 2, 0, 1, 2]
-trustiest	2.2	0.87178	[3, 2, 2, 3, 2, 2, 4, 1, 1, 2]
-trustily	1.6	0.91652	[2, 0, 3, 1, 2, 1, 1, 1, 2, 3]
-trustiness	1.6	0.91652	[2, 3, 0, 1, 2, 2, 2, 2, 0, 2]
-trusting	1.7	1.00499	[3, 0, 1, 2, 3, 0, 2, 2, 2, 2]
-trustingly	1.6	0.91652	[3, 1, 2, 3, 2, 2, 0, 1, 1, 1]
-trustingness	1.6	1.2	[1, 2, 1, 3, 2, 1, 4, 2, 0, 0]
-trustless	-2.3	0.78102	[-2, -4, -3, -2, -2, -3, -2, -2, -1, -2]
-trustor	0.4	0.66332	[2, 0, 0, 1, 0, 0, 0, 1, 0, 0]
-trustors	1.2	0.87178	[0, 0, 2, 1, 1, 2, 2, 2, 0, 2]
-trusts	2.1	0.53852	[2, 2, 2, 2, 1, 2, 2, 3, 2, 3]
-trustworthily	2.3	0.9	[3, 1, 2, 2, 2, 1, 3, 4, 3, 2]
-trustworthiness	1.8	0.74833	[2, 1, 3, 1, 2, 2, 1, 2, 3, 1]
-trustworthy	2.6	0.91652	[3, 2, 3, 4, 2, 4, 2, 3, 1, 2]
-trusty	2.2	0.74833	[3, 2, 3, 1, 2, 2, 3, 2, 1, 3]
-truth	1.3	1.00499	[2, 1, 0, 1, 1, 0, 3, 3, 1, 1]
-truthful	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
-truthfully	1.9	1.04403	[3, 1, 3, 0, 2, 1, 3, 2, 1, 3]
-truthfulness	1.7	1.1	[3, 2, 2, 2, 1, -1, 3, 2, 2, 1]
-truths	1.8	0.87178	[0, 1, 1, 3, 2, 2, 3, 2, 2, 2]
-tumor	-1.6	1.49666	[-3, -2, -2, -1, -2, 1, -4, 1, -2, -2]
-turmoil	-1.5	0.92195	[-1, -1, -3, -3, -2, -2, -1, -1, 0, -1]
-twat	-3.4	0.91652	[-3, -4, -4, -4, -3, -1, -4, -4, -3, -4]
-ugh	-1.8	0.9798	[-1, -1, -1, -1, -1, -2, -4, -2, -3, -2]
-uglier	-2.2	0.87178	[-2, -2, -1, -3, -4, -1, -3, -2, -2, -2]
-uglies	-2.0	0.89443	[-2, -2, -1, -3, -4, -1, -2, -2, -1, -2]
-ugliest	-2.8	0.74833	[-3, -3, -4, -3, -3, -3, -3, -3, -1, -2]
-uglification	-2.2	0.87178	[-3, -1, -2, -2, -1, -2, -4, -3, -2, -2]
-uglified	-1.5	0.67082	[-1, -1, -3, -2, -2, -1, -1, -1, -2, -1]
-uglifies	-1.8	0.74833	[-1, -1, -3, -2, -3, -1, -2, -2, -2, -1]
-uglify	-2.1	0.9434	[-3, -3, -1, -4, -2, -2, -1, -2, -1, -2]
-uglifying	-2.2	0.4	[-3, -2, -2, -2, -2, -2, -2, -2, -3, -2]
-uglily	-2.1	0.3	[-3, -2, -2, -2, -2, -2, -2, -2, -2, -2]
-ugliness	-2.7	0.9	[-4, -2, -3, -2, -4, -2, -4, -2, -2, -2]
-uglinesses	-2.5	1.0247	[-3, -3, -2, -1, -1, -3, -2, -2, -4, -4]
-ugly	-2.3	0.9	[-3, -2, -1, -2, -4, -1, -3, -2, -2, -3]
-unacceptable	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -3, -2, -2]
-unappreciated	-1.7	0.78102	[-1, -3, -2, -1, -1, -1, -2, -1, -2, -3]
-unapproved	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -1]
-unattractive	-1.9	0.53852	[-1, -2, -3, -2, -1, -2, -2, -2, -2, -2]
-unaware	-0.8	0.4	[-1, -1, -1, 0, -1, -1, 0, -1, -1, -1]
-unbelievable	0.8	1.6	[0, 0, 1, -2, 1, 3, 1, 0, 4, 0]
-unbelieving	-0.8	0.4	[0, -1, -1, -1, -1, -1, -1, 0, -1, -1]
-unbiased	-0.1	1.22066	[-2, -1, 2, 1, 0, -1, -1, 1, 1, -1]
-uncertain	-1.2	0.6	[-2, -1, -2, -1, -1, -1, 0, -1, -2, -1]
-uncertainly	-1.4	0.4899	[-2, -1, -1, -1, -2, -1, -1, -2, -2, -1]
-uncertainness	-1.3	0.45826	[-2, -2, -1, -1, -1, -1, -1, -2, -1, -1]
-uncertainties	-1.4	0.66332	[-3, -2, -1, -1, -1, -1, -1, -2, -1, -1]
-uncertainty	-1.4	0.4899	[-1, -1, -2, -1, -2, -1, -2, -1, -2, -1]
-unclear	-1.0	0.44721	[-2, -1, 0, -1, -1, -1, -1, -1, -1, -1]
-uncomfortable	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -2]
-uncomfortably	-1.7	0.64031	[-2, -1, -3, -1, -1, -2, -2, -1, -2, -2]
-uncompelling	-0.9	0.7	[0, -2, -1, 0, -1, -1, -1, 0, -1, -2]
-unconcerned	-0.9	0.83066	[-2, -2, -1, 1, -1, -1, -1, 0, -1, -1]
-unconfirmed	-0.5	0.67082	[0, -1, 0, -1, 0, -1, 0, 0, -2, 0]
-uncontrollability	-1.7	0.45826	[-1, -1, -2, -2, -2, -2, -1, -2, -2, -2]
-uncontrollable	-1.5	1.11803	[-2, -1, -1, -2, -1, -1, 1, -2, -3, -3]
-uncontrollably	-1.5	0.67082	[-2, -1, 0, -2, -1, -1, -2, -2, -2, -2]
-uncontrolled	-1.0	0.7746	[-1, 0, -1, -2, -1, 0, -1, -2, -2, 0]
-unconvinced	-1.6	0.8	[-2, -3, -1, -2, -1, 0, -2, -2, -1, -2]
-uncredited	-1.0	1.09545	[-1, -2, -2, 2, -1, -2, -1, -1, -1, -1]
-undecided	-0.9	0.9434	[-1, 0, -1, 0, -1, -1, -2, 0, -3, 0]
-underestimate	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -1]
-underestimated	-1.1	0.53852	[-1, -1, -1, -2, 0, -1, -2, -1, -1, -1]
-underestimates	-1.1	1.64012	[-2, -4, -1, -1, -1, -1, 3, -1, -2, -1]
-undermine	-1.2	1.16619	[-2, -2, -1, -1, -1, -1, 2, -2, -2, -2]
-undermined	-1.5	0.67082	[-1, -2, -1, -3, -1, -1, -1, -2, -2, -1]
-undermines	-1.4	0.4899	[-1, -2, -1, -2, -1, -1, -1, -2, -2, -1]
-undermining	-1.5	0.67082	[-1, -3, -1, -2, -2, -1, -1, -1, -2, -1]
-undeserving	-1.9	0.3	[-2, -2, -1, -2, -2, -2, -2, -2, -2, -2]
-undesirable	-1.9	0.7	[-1, -2, -3, -1, -3, -2, -1, -2, -2, -2]
-unease	-1.7	0.64031	[-2, -2, -2, -1, -1, -2, -1, -3, -1, -2]
-uneasier	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -1]
-uneasiest	-2.1	0.83066	[-1, -4, -3, -2, -2, -2, -2, -2, -1, -2]
-uneasily	-1.4	1.0198	[-2, -2, -1, -1, -2, 1, -3, -1, -2, -1]
-uneasiness	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -1, -2]
-uneasinesses	-1.8	0.87178	[-2, -1, -4, -1, -1, -2, -2, -2, -1, -2]
-uneasy	-1.6	0.4899	[-1, -2, -2, -1, -1, -2, -2, -1, -2, -2]
-unemployment	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -1, -2, -2, -3]
-unequal	-1.4	0.66332	[-1, -2, -2, -2, -1, -1, -2, 0, -2, -1]
-unequaled	0.5	1.80278	[-2, 3, 0, 3, 3, 0, 0, 0, -2, 0]
-unethical	-2.3	0.78102	[-3, -3, -1, -2, -2, -2, -3, -1, -3, -3]
-unfair	-2.1	0.83066	[-1, -3, -3, -2, -3, -1, -2, -3, -1, -2]
-unfocused	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -3, -2, -1, -2]
-unfortunate	-2.0	0.63246	[-2, -2, -2, -3, -3, -1, -2, -1, -2, -2]
-unfortunately	-1.4	0.91652	[-2, -1, -2, -2, 1, -2, -1, -1, -2, -2]
-unfortunates	-1.9	0.7	[-2, -3, -1, -1, -2, -2, -2, -1, -3, -2]
-unfriendly	-1.5	0.5	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -1]
-unfulfilled	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -1, -2, -2]
-ungrateful	-2.0	0.0	[-2, -2, -2, -2, -2, -2, -2, -2, -2, -2]
-ungratefully	-1.8	0.6	[-2, -2, -1, -2, -2, -1, -3, -1, -2, -2]
-ungratefulness	-1.6	0.4899	[-2, -2, -2, -2, -1, -1, -1, -2, -2, -1]
-unhappier	-2.4	0.8	[-2, -2, -1, -4, -3, -3, -2, -2, -2, -3]
-unhappiest	-2.5	0.80623	[-3, -4, -3, -2, -1, -3, -2, -2, -2, -3]
-unhappily	-1.9	0.53852	[-2, -1, -2, -2, -3, -2, -1, -2, -2, -2]
-unhappiness	-2.4	0.66332	[-3, -2, -2, -3, -2, -2, -3, -1, -3, -3]
-unhappinesses	-2.2	0.87178	[-3, -4, -2, -2, -2, -2, -1, -2, -1, -3]
-unhappy	-1.8	0.6	[-2, -2, -1, -3, -2, -2, -2, -1, -2, -1]
-unhealthy	-2.4	0.66332	[-1, -2, -3, -3, -2, -3, -3, -2, -2, -3]
-unified	1.6	0.66332	[1, 2, 2, 1, 2, 1, 2, 1, 3, 1]
-unimportant	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -1, -2, -1]
-unimpressed	-1.4	0.66332	[-1, -1, -1, -2, -1, -2, -1, -1, -3, -1]
-unimpressive	-1.4	0.4899	[-1, -2, -2, -1, -1, -2, -2, -1, -1, -1]
-unintelligent	-2.0	1.18322	[-1, -2, -3, -1, -1, -4, -1, -1, -4, -2]
-uninvolved	-2.2	0.9798	[-2, -1, -3, -2, -1, -3, -1, -2, -4, -3]
-uninvolving	-2.0	1.18322	[-4, -1, -3, -2, -1, -4, -1, -1, -2, -1]
-united	1.8	0.6	[1, 2, 2, 2, 1, 2, 2, 1, 2, 3]
-unjust	-2.3	0.45826	[-3, -3, -2, -2, -2, -2, -3, -2, -2, -2]
-unkind	-1.6	0.66332	[-2, -2, -1, -1, -1, -2, -3, -1, -1, -2]
-unlovable	-2.7	0.9	[-4, -2, -1, -3, -3, -3, -4, -2, -3, -2]
-unloved	-1.9	0.53852	[-1, -2, -2, -1, -2, -2, -3, -2, -2, -2]
-unlovelier	-1.9	0.7	[-2, -2, -1, -3, -1, -2, -1, -3, -2, -2]
-unloveliest	-1.9	0.83066	[-2, -4, -2, -2, -1, -1, -1, -2, -2, -2]
-unloveliness	-2.0	0.89443	[-2, -3, -1, -1, -3, -1, -3, -2, -3, -1]
-unlovely	-2.1	0.53852	[-2, -3, -2, -3, -1, -2, -2, -2, -2, -2]
-unloving	-2.3	0.45826	[-2, -3, -2, -3, -2, -2, -2, -3, -2, -2]
-unmatched	-0.3	2.0025	[0, -1, 2, 3, 0, -1, -3, 0, -4, 1]
-unmotivated	-1.4	0.4899	[-2, -2, -1, -1, -1, -2, -2, -1, -1, -1]
-unpleasant	-2.1	0.53852	[-2, -2, -3, -3, -2, -2, -2, -2, -1, -2]
-unprofessional	-2.3	0.78102	[-2, -1, -3, -3, -2, -1, -3, -2, -3, -3]
-unprotected	-1.5	0.67082	[-2, -2, -1, -1, -3, -1, -1, -2, -1, -1]
-unresearched	-1.1	0.7	[-2, -1, -1, -1, -1, -2, -2, 0, 0, -1]
-unsatisfied	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -3, -1, -2, -2]
-unsavory	-1.9	0.53852	[-2, -1, -2, -2, -2, -3, -1, -2, -2, -2]
-unsecured	-1.6	0.4899	[-1, -2, -2, -1, -1, -2, -1, -2, -2, -2]
-unsettled	-1.3	0.45826	[-1, -1, -1, -2, -2, -1, -2, -1, -1, -1]
-unsophisticated	-1.2	0.87178	[-1, -1, -1, -2, -2, -2, -1, -2, 1, -1]
-unstable	-1.5	0.5	[-2, -2, -1, -2, -1, -1, -1, -2, -2, -1]
-unstoppable	-0.8	1.77764	[0, -4, 2, 0, 1, -2, -2, 0, -3, 0]
-unsuccessful	-1.5	0.5	[-2, -1, -1, -2, -2, -1, -1, -1, -2, -2]
-unsuccessfully	-1.7	0.78102	[-2, -2, -1, -1, -1, -2, -3, -3, -1, -1]
-unsupported	-1.7	0.78102	[-2, 0, -3, -2, -2, -1, -2, -2, -1, -2]
-unsure	-1.0	0.44721	[-1, -1, -1, -1, 0, -2, -1, -1, -1, -1]
-unsurely	-1.3	0.78102	[-1, 0, -1, -1, -1, -3, -1, -2, -2, -1]
-untarnished	1.6	1.35647	[3, 2, 2, 1, 1, 2, -2, 3, 2, 2]
-unwanted	-0.9	1.3	[-1, -2, -2, -1, -2, 1, 2, -1, -2, -1]
-unwelcome	-1.7	0.45826	[-2, -2, -2, -1, -1, -2, -2, -1, -2, -2]
-unworthy	-2.0	0.44721	[-3, -2, -2, -2, -2, -2, -1, -2, -2, -2]
-upset	-1.6	0.4899	[-1, -1, -2, -2, -1, -1, -2, -2, -2, -2]
-upsets	-1.5	0.67082	[-2, -3, -1, -1, -1, -1, -2, -2, -1, -1]
-upsetter	-1.9	0.7	[-2, -2, -1, -1, -3, -2, -3, -1, -2, -2]
-upsetters	-2.0	0.63246	[-3, -3, -1, -2, -2, -2, -2, -2, -1, -2]
-upsetting	-2.1	0.53852	[-2, -3, -2, -3, -2, -1, -2, -2, -2, -2]
-uptight	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -2]
-uptightness	-1.2	0.4	[-1, -2, -1, -2, -1, -1, -1, -1, -1, -1]
-urgent	0.8	1.16619	[3, -1, 0, 1, 1, 0, 0, 0, 2, 2]
-useful	1.9	0.83066	[2, 1, 1, 2, 2, 4, 2, 1, 2, 2]
-usefully	1.8	0.6	[2, 2, 1, 3, 1, 2, 1, 2, 2, 2]
-usefulness	1.2	1.32665	[3, 1, 3, -1, 2, 2, 1, 1, -1, 1]
-useless	-1.8	0.4	[-2, -1, -2, -2, -1, -2, -2, -2, -2, -2]
-uselessly	-1.5	0.67082	[-2, -3, -1, -1, -1, -1, -2, -2, -1, -1]
-uselessness	-1.6	0.8	[-3, -2, -2, -2, -1, -2, 0, -1, -1, -2]
-v.v	-2.9	0.9434	[-3, -3, -4, -3, -1, -3, -4, -2, -4, -2]
-vague	-0.4	0.8	[0, -1, -1, -1, 0, -1, 1, -1, 1, -1]
-vain	-1.8	0.6	[-2, -1, -2, -3, -2, -1, -1, -2, -2, -2]
-validate	1.5	0.92195	[1, 2, 1, 1, 1, 3, 1, 3, 0, 2]
-validated	0.9	0.83066	[2, 1, 0, 1, 1, 0, 2, 0, 0, 2]
-validates	1.4	0.66332	[1, 1, 1, 2, 3, 1, 2, 1, 1, 1]
-validating	1.4	0.8	[2, 2, 1, 3, 0, 2, 1, 1, 1, 1]
-valuable	2.1	0.83066	[3, 2, 4, 2, 2, 2, 2, 1, 1, 2]
-valuableness	1.7	0.78102	[2, 2, 1, 3, 3, 2, 1, 1, 1, 1]
-valuables	2.1	0.83066	[4, 1, 2, 2, 3, 2, 1, 2, 2, 2]
-valuably	2.3	1.00499	[3, 4, 4, 1, 2, 2, 2, 2, 1, 2]
-value	1.4	1.11355	[2, 3, 0, 1, 1, 3, 0, 2, 0, 2]
-valued	1.9	0.7	[3, 1, 2, 1, 2, 2, 2, 3, 2, 1]
-values	1.7	1.18743	[2, 2, 2, 4, 0, 1, 0, 1, 3, 2]
-valuing	1.4	0.91652	[1, 0, 3, 2, 2, 2, 2, 0, 1, 1]
-vanity	-0.9	1.7	[-2, -3, -3, 0, -2, -1, 2, 2, -1, -1]
-verdict	0.6	0.91652	[0, 0, 0, 0, 0, 0, 0, 2, 2, 2]
-verdicts	0.3	1.1	[0, 0, 0, 0, 2, 2, 0, -2, 1, 0]
-vested	0.6	1.28062	[2, -2, 1, 3, 1, 0, 0, 1, 0, 0]
-vexation	-1.9	1.04403	[0, -2, -3, -3, -2, -2, -2, -3, 0, -2]
-vexing	-2.0	0.44721	[-2, -2, -2, -1, -2, -2, -2, -3, -2, -2]
-vibrant	2.4	0.8	[2, 3, 1, 1, 3, 3, 3, 2, 3, 3]
-vicious	-1.5	1.5	[1, -2, -3, -1, -1, -3, 1, -3, -1, -3]
-viciously	-1.3	1.26886	[-2, -3, -1, -2, -2, -1, -1, 2, -1, -2]
-viciousness	-2.4	1.35647	[-3, -1, -4, -2, -3, -3, 1, -3, -3, -3]
-viciousnesses	-0.6	1.62481	[0, -1, -1, -3, 0, -3, 2, 1, 1, -2]
-victim	-1.1	1.92094	[-1, -2, 2, -3, -3, -2, -3, 1, 2, -2]
-victimhood	-2.0	0.44721	[-2, -2, -2, -2, -2, -1, -3, -2, -2, -2]
-victimhoods	-0.9	1.37477	[-1, 0, -1, 1, -2, -1, -4, 1, -1, -1]
-victimise	-1.1	1.92094	[-3, -3, -2, -2, -1, 2, -2, 1, -3, 2]
-victimised	-1.5	1.56525	[-2, -2, -2, 1, -3, 2, -2, -3, -2, -2]
-victimises	-1.2	2.31517	[-3, -3, -4, 2, -2, -2, 1, 2, 1, -4]
-victimising	-2.5	0.67082	[-3, -1, -3, -2, -2, -3, -3, -2, -3, -3]
-victimization	-2.3	0.78102	[-1, -3, -3, -2, -3, -1, -3, -2, -3, -2]
-victimizations	-1.5	1.85742	[-2, -3, -3, -1, -2, 2, 2, -2, -3, -3]
-victimize	-2.5	0.67082	[-3, -2, -4, -2, -2, -2, -2, -3, -3, -2]
-victimized	-1.8	1.53623	[-2, -1, -3, -3, -3, 1, 1, -2, -3, -3]
-victimizer	-1.8	1.72047	[-3, -2, -3, -3, -2, 2, 1, -2, -3, -3]
-victimizers	-1.6	1.68523	[-3, -2, -3, 1, -3, -1, -2, 2, -2, -3]
-victimizes	-1.5	1.9105	[-2, -1, -4, -3, -2, 2, 2, -2, -3, -2]
-victimizing	-2.6	0.4899	[-2, -3, -3, -3, -2, -3, -2, -3, -2, -3]
-victimless	0.6	0.4899	[0, 1, 0, 1, 1, 0, 0, 1, 1, 1]
-victimologies	-0.6	1.35647	[-2, 0, -2, -1, 0, 2, 1, 0, -2, -2]
-victimologist	-0.5	0.67082	[0, -1, -1, 0, 0, 0, 0, -1, -2, 0]
-victimologists	-0.4	0.91652	[0, 1, 0, -2, -2, 0, 0, 0, -1, 0]
-victimology	0.3	1.00499	[0, 0, 0, -1, 0, 1, 0, 0, 3, 0]
-victims	-1.3	2.05183	[-3, -1, -3, -3, -3, 2, 1, -2, 2, -3]
-vigilant	0.7	0.9	[0, 2, 0, 2, 0, -1, 1, 1, 1, 1]
-vigor	1.1	1.37477	[0, 3, 2, 1, 2, 2, 0, 1, -2, 2]
-vigorish	-0.4	1.2	[0, -3, -1, -1, 0, -1, 0, 0, 2, 0]
-vigorishes	0.4	1.56205	[0, 0, 2, 1, 2, 0, -2, -2, 0, 3]
-vigoroso	1.5	0.67082	[2, 0, 1, 2, 2, 1, 2, 1, 2, 2]
-vigorously	0.5	0.92195	[0, 0, 0, 1, 2, 0, 2, -1, 1, 0]
-vigorousness	0.4	1.11355	[0, 3, 0, -1, -1, 0, 0, 1, 1, 1]
-vigors	1.0	1.0	[0, 1, 0, 1, 0, 0, 1, 3, 2, 2]
-vigour	0.9	0.9434	[0, 2, 2, 2, 1, 1, 0, 1, -1, 1]
-vigours	0.4	1.68523	[-4, 1, 1, 1, -1, 1, 2, 2, 0, 1]
-vile	-3.1	0.83066	[-4, -2, -4, -4, -2, -3, -3, -3, -2, -4]
-villain	-2.6	0.4899	[-3, -2, -2, -3, -2, -2, -3, -3, -3, -3]
-villainess	-2.9	0.53852	[-3, -2, -3, -4, -3, -2, -3, -3, -3, -3]
-villainesses	-2.0	1.18322	[-2, -3, -2, -2, -2, -3, 1, -3, -1, -3]
-villainies	-2.3	1.00499	[-3, -2, -3, -3, -3, -1, -3, -2, -3, 0]
-villainous	-2.0	0.63246	[-3, -2, -1, -2, -2, -2, -2, -1, -2, -3]
-villainously	-2.9	0.53852	[-3, -3, -3, -3, -3, -4, -2, -3, -2, -3]
-villainousness	-2.7	0.9	[-4, -3, -4, -3, -1, -3, -2, -2, -2, -3]
-villains	-3.4	0.91652	[-4, -3, -4, -3, -4, -3, -4, -4, -1, -4]
-villainy	-2.6	0.4899	[-3, -2, -3, -3, -2, -2, -2, -3, -3, -3]
-vindicate	0.3	1.95192	[2, -1, -2, -3, -1, 3, 0, 3, 1, 1]
-vindicated	1.8	1.16619	[1, 3, -1, 2, 2, 1, 3, 2, 2, 3]
-vindicates	1.6	0.66332	[2, 3, 2, 2, 2, 1, 1, 1, 1, 1]
-vindicating	-1.1	1.97231	[-3, -2, 2, -3, -2, 1, 1, 1, -3, -3]
-violate	-2.2	0.6	[-3, -3, -2, -3, -2, -2, -1, -2, -2, -2]
-violated	-2.4	0.66332	[-3, -3, -3, -3, -2, -3, -1, -2, -2, -2]
-violater	-2.6	0.91652	[-3, -3, -4, -4, -2, -3, -2, -2, -2, -1]
-violaters	-2.4	0.8	[-1, -3, -1, -2, -3, -3, -3, -2, -3, -3]
-violates	-2.3	0.9	[-3, -2, -4, -3, -2, -3, -2, -2, -1, -1]
-violating	-2.5	0.92195	[-2, -3, -3, -1, -3, -2, -4, -1, -3, -3]
-violation	-2.2	0.9798	[-3, -1, -1, -3, -3, -2, -1, -2, -2, -4]
-violations	-2.4	0.66332	[-2, -2, -2, -3, -2, -4, -2, -2, -2, -3]
-violative	-2.4	0.66332	[-2, -3, -3, -3, -1, -3, -2, -2, -2, -3]
-violator	-2.4	1.0198	[-1, -4, -3, -2, -3, -2, -2, -1, -4, -2]
-violators	-1.9	1.51327	[-2, 2, -3, -4, -1, -2, -3, -2, -2, -2]
-violence	-3.1	0.53852	[-2, -3, -3, -3, -3, -4, -4, -3, -3, -3]
-violent	-2.9	0.53852	[-3, -3, -3, -3, -3, -4, -3, -2, -2, -3]
-violently	-2.8	0.74833	[-3, -3, -2, -3, -3, -3, -4, -1, -3, -3]
-virtue	1.8	0.74833	[1, 2, 3, 2, 2, 2, 3, 1, 1, 1]
-virtueless	-1.4	1.0198	[-2, 0, -2, -3, -1, -3, -1, -1, -1, 0]
-virtues	1.5	0.80623	[2, 2, 2, 1, 0, 1, 3, 1, 2, 1]
-virtuosa	1.7	1.48661	[0, 4, 2, 3, 2, 3, 0, 2, -1, 2]
-virtuosas	1.8	0.87178	[2, 3, 1, 2, 1, 0, 3, 2, 2, 2]
-virtuose	1.0	1.41421	[2, 1, 0, 2, 1, -1, 1, 1, -1, 4]
-virtuosi	0.9	1.37477	[2, 0, 0, 2, 1, 0, 0, 1, -1, 4]
-virtuosic	2.2	1.07703	[2, 2, 4, 1, 0, 3, 3, 2, 2, 3]
-virtuosity	2.1	0.83066	[3, 3, 3, 2, 1, 3, 2, 2, 1, 1]
-virtuoso	2.0	1.0	[2, 2, 3, 2, 1, 0, 3, 3, 3, 1]
-virtuosos	1.8	1.16619	[2, 3, 1, -1, 2, 1, 3, 3, 2, 2]
-virtuous	2.4	1.2	[0, 3, 2, 1, 3, 4, 2, 2, 4, 3]
-virtuously	1.8	1.16619	[3, 2, 3, 1, 3, 1, -1, 2, 2, 2]
-virtuousness	2.0	1.09545	[3, 4, 2, 2, 0, 1, 2, 3, 2, 1]
-virulent	-2.7	0.64031	[-3, -2, -4, -2, -3, -3, -2, -3, -2, -3]
-vision	1.0	1.0	[0, 0, 0, 2, 1, 3, 2, 1, 1, 0]
-visionary	2.4	1.0198	[1, 3, 1, 2, 4, 1, 3, 3, 3, 3]
-visioning	1.1	0.9434	[1, 2, 0, 0, 3, 0, 1, 1, 2, 1]
-visions	0.9	0.9434	[2, 0, 0, 0, 0, 1, 2, 2, 0, 2]
-vital	1.2	1.46969	[-3, 2, 1, 1, 2, 2, 1, 2, 2, 2]
-vitalise	1.1	0.9434	[1, 2, 0, 2, 2, 0, 2, 0, 2, 0]
-vitalised	0.6	1.49666	[1, -2, 2, 0, 2, 1, -2, 2, 0, 2]
-vitalises	1.1	1.3	[1, 2, 2, 0, 2, 2, -2, 2, 0, 2]
-vitalising	2.1	0.53852	[2, 2, 3, 2, 3, 2, 2, 1, 2, 2]
-vitalism	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
-vitalist	0.3	0.64031	[0, 0, 0, 0, 0, 0, 1, 0, 2, 0]
-vitalists	0.3	1.34536	[2, -3, 1, 0, 0, 0, 1, 0, 2, 0]
-vitalities	1.2	0.87178	[2, 1, 3, 1, 1, 0, 2, 1, 0, 1]
-vitality	1.3	0.9	[3, 2, 0, 1, 1, 1, 2, 0, 2, 1]
-vitalization	1.6	0.91652	[2, 3, 3, 1, 2, 1, 0, 2, 1, 1]
-vitalizations	0.8	0.74833	[0, 1, 1, 2, 0, 0, 0, 2, 1, 1]
-vitalize	1.6	0.66332	[3, 2, 2, 1, 2, 1, 1, 1, 2, 1]
-vitalized	1.5	0.67082	[1, 1, 2, 2, 0, 2, 1, 2, 2, 2]
-vitalizes	1.4	0.4899	[2, 1, 1, 2, 1, 2, 1, 2, 1, 1]
-vitalizing	1.3	0.9	[3, 1, 0, 0, 1, 1, 2, 2, 2, 1]
-vitally	1.1	0.53852	[0, 2, 1, 1, 1, 1, 2, 1, 1, 1]
-vitals	1.1	0.7	[1, 0, 1, 2, 2, 0, 2, 1, 1, 1]
-vitamin	1.2	0.87178	[3, 1, 0, 0, 1, 2, 1, 2, 1, 1]
-vitriolic	-2.1	0.83066	[-2, -2, -2, -4, -3, -2, -1, -1, -2, -2]
-vivacious	1.8	0.9798	[0, 1, 3, 3, 3, 2, 2, 2, 1, 1]
-vociferous	-0.8	0.9798	[1, -2, -1, -2, -1, -1, 1, -1, -1, -1]
-vulnerabilities	-0.6	1.49666	[0, -3, -1, -1, -1, 2, -2, 2, -1, -1]
-vulnerability	-0.9	1.75784	[1, -1, -1, -2, 1, -3, -1, 2, -4, -1]
-vulnerable	-0.9	1.37477	[-2, -2, 2, -1, -3, -1, 1, -1, -1, -1]
-vulnerableness	-1.1	1.04403	[-1, -1, -2, -3, -1, 1, 0, -2, -1, -1]
-vulnerably	-1.2	1.46969	[-2, -2, 2, -1, -2, -3, 1, -1, -2, -2]
-vulture	-2.0	0.89443	[-2, -3, -1, -2, -1, -1, -1, -3, -3, -3]
-vultures	-1.3	1.55242	[-2, -3, -2, 2, -2, -2, -3, -1, -1, 1]
-w00t	2.2	1.32665	[3, 2, 3, 2, 0, 4, 0, 4, 2, 2]
-walkout	-1.3	0.9	[-1, -2, -2, -1, -1, -2, -1, 1, -2, -2]
-walkouts	-0.7	1.00499	[-2, -2, -1, 0, -1, -1, -1, 1, -1, 1]
-wanker	-2.5	0.67082	[-2, -3, -3, -2, -3, -3, -2, -1, -3, -3]
-want	0.3	1.18743	[0, -2, 0, 1, 2, -1, 2, 1, 0, 0]
-war	-2.9	1.13578	[-1, -3, -4, -4, -3, -1, -2, -3, -4, -4]
-warfare	-1.2	1.16619	[-2, 0, -1, -2, 0, -3, 1, -2, -2, -1]
-warfares	-1.8	0.87178	[-2, -1, -2, -2, -3, -1, -3, 0, -2, -2]
-warm	0.9	0.7	[1, 0, 0, 1, 1, 2, 1, 2, 1, 0]
-warmblooded	0.2	0.6	[0, 0, 2, 0, 0, 0, 0, 0, 0, 0]
-warmed	1.1	0.53852	[2, 0, 1, 1, 1, 2, 1, 1, 1, 1]
-warmer	1.2	0.9798	[2, 2, 2, 1, -1, 0, 2, 1, 1, 2]
-warmers	1.0	0.44721	[1, 1, 1, 2, 1, 1, 1, 0, 1, 1]
-warmest	1.7	1.34536	[3, 2, 1, 2, 3, 2, 2, 2, -2, 2]
-warmhearted	1.8	0.6	[3, 2, 2, 2, 2, 1, 2, 1, 1, 2]
-warmheartedness	2.7	0.64031	[2, 4, 3, 2, 3, 3, 3, 2, 2, 3]
-warming	0.6	0.8	[0, 0, 2, 2, 1, 1, 0, 0, 0, 0]
-warmish	1.4	0.66332	[1, 3, 2, 1, 1, 1, 1, 2, 1, 1]
-warmly	1.7	0.64031	[2, 1, 2, 1, 2, 1, 2, 1, 2, 3]
-warmness	1.5	0.92195	[3, 1, 2, 1, 0, 1, 3, 2, 1, 1]
-warmonger	-2.9	1.13578	[-3, 0, -4, -4, -2, -3, -4, -3, -3, -3]
-warmongering	-2.5	0.67082	[-2, -3, -3, -1, -2, -3, -3, -2, -3, -3]
-warmongers	-2.8	0.87178	[-2, -3, -4, -4, -3, -1, -2, -3, -3, -3]
-warmouth	0.4	0.66332	[0, 0, 2, 0, 0, 0, 0, 1, 1, 0]
-warmouths	-0.8	1.32665	[-1, -1, -2, -1, -2, -2, 0, 2, 1, -2]
-warms	1.1	0.7	[2, 2, 1, 2, 1, 0, 1, 1, 0, 1]
-warmth	2.0	0.44721	[2, 2, 2, 2, 1, 2, 2, 3, 2, 2]
-warmup	0.4	0.66332	[0, 2, 0, 1, 1, 0, 0, 0, 0, 0]
-warmups	0.8	0.9798	[0, 2, 0, 0, 0, 2, 2, 0, 2, 0]
-warn	-0.4	1.35647	[0, -1, 0, -2, -1, 2, 1, -2, 1, -2]
-warned	-1.1	0.53852	[-1, -1, -2, 0, -1, -1, -1, -2, -1, -1]
-warning	-1.4	1.0198	[-2, -1, -1, -1, -2, 0, -4, -1, -1, -1]
-warnings	-1.2	0.9798	[-2, -1, 0, -1, -2, 0, 0, -1, -3, -2]
-warns	-0.4	1.0198	[1, -1, -1, 1, -1, -1, -2, 1, 0, -1]
-warred	-2.4	0.8	[-2, -2, -4, -1, -3, -2, -3, -2, -3, -2]
-warring	-1.9	1.04403	[-3, -3, 0, -1, -2, -2, -3, -1, -1, -3]
-wars	-2.6	0.8	[-2, -3, -1, -3, -2, -4, -3, -3, -2, -3]
-warsaw	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
-warsaws	-0.2	0.4	[0, 0, 0, -1, 0, 0, 0, 0, -1, 0]
-warship	-0.7	0.9	[0, 0, 0, 0, 0, -2, -1, 0, -2, -2]
-warships	-0.5	0.80623	[0, -1, 0, 0, -2, 0, 0, -2, 0, 0]
-warstle	0.1	0.7	[0, 0, 0, 0, 0, 0, 0, 0, 2, -1]
-waste	-1.8	0.9798	[-2, -2, -1, -3, -2, -1, -1, -4, -1, -1]
-wasted	-2.2	0.6	[-2, -3, -2, -3, -1, -3, -2, -2, -2, -2]
-wasting	-1.7	0.9	[-3, -1, -2, -2, -1, -2, -3, 0, -1, -2]
-wavering	-0.6	1.0198	[-1, -1, 0, 0, -1, -1, -1, 2, -1, -2]
-weak	-1.9	0.7	[-1, -3, -2, -2, -3, -2, -2, -1, -2, -1]
-weaken	-1.8	0.6	[-2, -2, -2, -1, -1, -3, -2, -2, -1, -2]
-weakened	-1.3	0.9	[-2, -1, -1, -1, -1, -2, -2, -2, 1, -2]
-weakener	-1.6	1.11355	[-2, -1, -1, -1, -2, -2, -3, -3, 1, -2]
-weakeners	-1.3	0.45826	[-1, -2, -1, -2, -1, -1, -2, -1, -1, -1]
-weakening	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -1, -2, -2, -1]
-weakens	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -1, -2, -1, -2]
-weaker	-1.9	0.83066	[-2, -2, -2, -2, -2, -1, -4, -1, -1, -2]
-weakest	-2.3	0.64031	[-2, -4, -2, -3, -2, -2, -2, -2, -2, -2]
-weakfish	-0.2	1.07703	[0, -2, 0, 0, 0, 0, -2, 0, 2, 0]
-weakfishes	-0.6	0.8	[0, -1, 0, -2, 0, 0, -1, 0, -2, 0]
-weakhearted	-1.6	0.8	[-1, -3, -1, -1, -2, -1, -3, -2, -1, -1]
-weakish	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
-weaklier	-1.5	0.67082	[-1, -2, -1, -3, -2, -1, -1, -2, -1, -1]
-weakliest	-2.1	0.83066	[-2, -2, -2, -2, -3, -1, -2, -1, -4, -2]
-weakling	-1.3	1.00499	[-1, -2, -1, -3, -2, -2, -1, -1, 1, -1]
-weaklings	-1.4	0.66332	[-2, -1, -1, -1, -1, -2, -2, 0, -2, -2]
-weakly	-1.8	0.87178	[-2, -2, -2, -2, -4, -1, -1, -1, -1, -2]
-weakness	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -1, -3, -2, -2]
-weaknesses	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -1, -2]
-weakside	-1.1	1.37477	[-3, -2, -3, -1, -2, -1, 1, 1, -1, 0]
-wealth	2.2	0.4	[2, 3, 2, 2, 2, 3, 2, 2, 2, 2]
-wealthier	2.2	0.6	[3, 2, 1, 3, 2, 2, 2, 3, 2, 2]
-wealthiest	2.2	0.9798	[2, 4, 4, 1, 2, 1, 2, 2, 2, 2]
-wealthily	2.0	0.89443	[2, 3, 1, 4, 2, 1, 1, 2, 2, 2]
-wealthiness	2.4	1.11355	[2, 4, 2, 4, 1, 2, 4, 1, 2, 2]
-wealthy	1.5	1.0247	[1, 2, 1, 4, 1, 0, 2, 1, 2, 1]
-weapon	-1.2	0.87178	[0, -2, -2, -1, 0, -2, -1, -2, 0, -2]
-weaponed	-1.4	0.91652	[-2, -2, -3, -1, -1, 0, 0, -2, -1, -2]
-weaponless	0.1	1.13578	[2, -1, 0, 0, -1, 1, -1, 0, 2, -1]
-weaponry	-0.9	0.7	[-2, -2, 0, -1, 0, -1, -1, -1, 0, -1]
-weapons	-1.9	0.9434	[-2, -1, -2, -2, -1, -3, -3, -3, -2, 0]
-weary	-1.1	1.13578	[-2, -1, -2, -3, 0, -1, -1, -2, 0, 1]
-weep	-2.7	0.9	[-2, -4, -4, -3, -3, -3, -3, -2, -1, -2]
-weeper	-1.9	0.53852	[-2, -2, -2, -3, -1, -1, -2, -2, -2, -2]
-weepers	-1.1	1.13578	[-2, -2, -1, -2, -1, 1, -2, 1, -1, -2]
-weepie	-0.4	0.91652	[0, 1, -1, 0, -1, -2, 0, -1, -1, 1]
-weepier	-1.8	0.87178	[-3, -3, -2, -1, -2, -2, -2, 0, -1, -2]
-weepies	-1.6	0.8	[-2, -3, -2, -1, -1, -2, -2, 0, -1, -2]
-weepiest	-2.4	0.91652	[-4, -2, -2, -2, -2, -1, -2, -2, -4, -3]
-weeping	-1.9	0.9434	[-2, -2, -1, -1, -1, -1, -4, -2, -2, -3]
-weepings	-1.9	0.9434	[-2, -2, -3, 0, -1, -2, -2, -3, -1, -3]
-weeps	-1.4	1.35647	[-2, -3, -1, -2, -1, -3, 1, -2, 1, -2]
-weepy	-1.3	1.55242	[-2, -3, -1, -2, 2, -3, -1, -2, 1, -2]
-weird	-0.7	0.64031	[-1, 0, 0, -1, -1, -1, 0, 0, -2, -1]
-weirder	-0.5	0.80623	[1, -1, -1, -1, -1, 1, -1, -1, 0, -1]
-weirdest	-0.9	1.22066	[-2, 0, -2, -1, -1, -1, -3, 1, 1, -1]
-weirdie	-1.3	0.45826	[-1, -2, -1, -2, -1, -1, -2, -1, -1, -1]
-weirdies	-1.0	0.63246	[0, -1, -1, -1, -1, 0, -2, -2, -1, -1]
-weirdly	-1.2	0.74833	[0, -1, -1, -2, -3, -1, -1, -1, -1, -1]
-weirdness	-0.9	1.64012	[-3, -2, -1, -1, 2, -1, 1, -3, 1, -2]
-weirdnesses	-0.7	1.00499	[-1, -2, 0, -1, -2, 1, -1, -1, -1, 1]
-weirdo	-1.8	0.6	[-2, -2, -2, -2, -2, -2, -1, -1, -3, -1]
-weirdoes	-1.3	0.64031	[-2, -1, -2, -1, -1, -2, -1, 0, -1, -2]
-weirdos	-1.1	0.9434	[-1, -1, -1, -2, 1, -3, -1, -1, -1, -1]
-weirds	-0.6	0.4899	[-1, -1, -1, 0, -1, 0, 0, -1, 0, -1]
-weirdy	-0.9	0.83066	[-1, -1, 0, 0, -1, 0, -2, -2, 0, -2]
-welcome	2.0	0.63246	[1, 3, 2, 1, 2, 2, 2, 2, 3, 2]
-welcomed	1.4	0.4899	[1, 1, 2, 2, 1, 2, 1, 2, 1, 1]
-welcomely	1.9	0.53852	[2, 2, 2, 2, 1, 3, 2, 1, 2, 2]
-welcomeness	2.0	0.89443	[2, 3, 1, 2, 3, 0, 2, 3, 2, 2]
-welcomer	1.4	0.4899	[1, 1, 2, 2, 2, 2, 1, 1, 1, 1]
-welcomers	1.9	0.7	[2, 2, 3, 2, 2, 1, 1, 3, 1, 2]
-welcomes	1.7	0.78102	[1, 1, 2, 2, 3, 3, 1, 2, 1, 1]
-welcoming	1.9	0.7	[2, 2, 1, 1, 2, 2, 2, 3, 3, 1]
-well	1.1	1.04403	[0, 0, 2, 0, 2, 0, 1, 1, 3, 2]
-welladay	0.3	1.18743	[2, -2, 0, 0, -1, 1, 0, 1, 2, 0]
-wellaway	-0.8	1.98997	[3, -2, -3, -3, -1, -2, 1, -2, -1, 2]
-wellborn	1.8	0.74833	[2, 1, 2, 1, 2, 2, 1, 3, 1, 3]
-welldoer	2.5	0.67082	[2, 2, 2, 3, 2, 3, 4, 3, 2, 2]
-welldoers	1.6	0.8	[3, 1, 1, 0, 2, 1, 2, 2, 2, 2]
-welled	0.4	0.8	[0, 0, 2, 0, 0, 0, 0, 0, 2, 0]
-wellhead	0.1	0.3	[0, 0, 1, 0, 0, 0, 0, 0, 0, 0]
-wellheads	0.5	0.92195	[0, 2, 0, 2, -1, 0, 1, 1, 0, 0]
-wellhole	-0.1	0.3	[0, 0, 0, -1, 0, 0, 0, 0, 0, 0]
-wellies	0.4	0.4899	[0, 1, 0, 0, 0, 1, 0, 0, 1, 1]
-welling	1.6	0.8	[2, 0, 1, 2, 2, 1, 3, 2, 2, 1]
-wellness	1.9	0.9434	[1, 2, 2, 1, 2, 1, 1, 3, 4, 2]
-wells	1.0	1.0	[2, 0, 3, 0, 1, 0, 2, 1, 1, 0]
-wellsite	0.5	0.67082	[0, 0, 1, 2, 0, 0, 0, 0, 1, 1]
-wellspring	1.5	0.92195	[3, 1, 1, 1, 0, 2, 2, 3, 1, 1]
-wellsprings	1.4	0.8	[1, 0, 0, 2, 2, 2, 1, 2, 2, 2]
-welly	0.2	0.4	[0, 0, 0, 1, 0, 1, 0, 0, 0, 0]
-wept	-2.0	1.09545	[-3, -2, -3, -3, -1, -3, 0, -1, -1, -3]
-whimsical	0.3	1.61555	[2, 1, 1, 2, -1, 1, -3, -2, 1, 1]
-whine	-1.5	1.11803	[-1, -4, -1, -1, -1, -3, 0, -2, -1, -1]
-whined	-0.9	1.04403	[-2, -1, -2, -1, -1, -1, -2, 1, 1, -1]
-whiner	-1.2	0.4	[-1, -2, -1, -1, -1, -2, -1, -1, -1, -1]
-whiners	-0.6	1.95959	[-2, 0, -2, -2, 4, 1, 1, -2, -2, -2]
-whines	-1.8	0.6	[-2, -2, -2, -1, -2, -2, -3, -1, -2, -1]
-whiney	-1.3	0.45826	[-1, -2, -1, -1, -1, -2, -2, -1, -1, -1]
-whining	-0.9	1.51327	[-3, 0, -1, -1, -3, -1, 1, 2, -2, -1]
-whitewash	0.1	0.7	[-1, 0, 1, -1, 0, 0, 0, 1, 1, 0]
-whore	-3.3	0.64031	[-4, -4, -3, -2, -3, -4, -3, -3, -4, -3]
-whored	-2.8	0.87178	[-2, -3, -4, -2, -2, -3, -4, -4, -2, -2]
-whoredom	-2.1	2.02237	[-4, -2, -4, -3, -3, -3, -4, -1, 2, 1]
-whoredoms	-2.4	1.11355	[-1, -3, 0, -3, -2, -3, -3, -4, -2, -3]
-whorehouse	-1.1	2.11896	[-2, -2, -2, 3, 3, -3, -3, -2, -1, -2]
-whorehouses	-1.9	1.92094	[-4, -3, -4, -3, 0, 0, -3, 2, -1, -3]
-whoremaster	-1.9	1.22066	[-1, -3, -3, -2, -1, -3, 0, 0, -3, -3]
-whoremasters	-1.5	1.85742	[-3, -1, -1, -4, -2, 2, -1, 1, -2, -4]
-whoremonger	-2.6	0.91652	[-3, -1, -3, -3, -3, -3, -3, -1, -4, -2]
-whoremongers	-2.0	1.78885	[-4, -3, 0, -3, -3, -3, -3, 1, 1, -3]
-whores	-3.0	1.0	[-3, -3, -4, -2, -1, -3, -4, -4, -2, -4]
-whoreson	-2.2	1.46969	[-2, -3, -4, -4, -3, -1, -1, 1, -3, -2]
-whoresons	-2.5	1.20416	[-3, -3, -2, -2, 0, -4, -3, -1, -3, -4]
-wicked	-2.4	0.8	[-3, -4, -3, -3, -2, -2, -2, -1, -2, -2]
-wickeder	-2.2	1.32665	[-2, -3, -1, -4, 1, -3, -3, -3, -2, -2]
-wickedest	-2.9	1.04403	[-3, -1, -3, -3, -3, -3, -1, -4, -4, -4]
-wickedly	-2.1	0.83066	[-2, -2, -1, -3, -2, -3, -1, -3, -1, -3]
-wickedness	-2.1	0.83066	[-2, -1, -2, -2, -3, -1, -2, -4, -2, -2]
-wickednesses	-2.2	1.16619	[-1, -2, -4, -2, -3, -1, -3, -4, -1, -1]
-widowed	-2.1	1.22066	[0, -4, -2, -4, -3, -2, -2, -2, -1, -1]
-willingness	1.1	0.7	[0, 2, 1, 1, 2, 2, 1, 0, 1, 1]
-wimp	-1.4	1.28062	[-2, -3, -1, -2, -1, -2, -2, -1, 2, -2]
-wimpier	-1.0	1.18322	[-1, -2, -2, -1, -2, 0, 1, -2, 1, -2]
-wimpiest	-0.9	1.22066	[-3, -1, -2, -1, -2, -1, 1, 1, 0, -1]
-wimpiness	-1.2	0.9798	[1, -1, -3, -1, -2, -1, -1, -1, -2, -1]
-wimpish	-1.6	0.4899	[-2, -1, -2, -1, -2, -2, -1, -2, -2, -1]
-wimpishness	-0.2	1.249	[-3, -1, 0, -1, -1, 1, 1, 1, 1, 0]
-wimple	-0.2	0.74833	[0, -1, 0, 0, 0, 0, -2, 0, 0, 1]
-wimples	-0.3	0.78102	[-2, 0, 0, 0, 0, -1, 0, -1, 1, 0]
-wimps	-1.0	1.18322	[-2, -2, -1, -1, 0, -2, -2, 1, -2, 1]
-wimpy	-0.9	1.04403	[-2, -1, -1, -1, -1, -2, -1, 1, -2, 1]
-win	2.8	0.87178	[3, 2, 4, 3, 2, 4, 3, 1, 3, 3]
-winnable	1.8	0.6	[3, 2, 2, 2, 2, 1, 1, 1, 2, 2]
-winned	1.8	0.6	[2, 2, 2, 2, 1, 2, 1, 1, 3, 2]
-winner	2.8	0.87178	[2, 2, 2, 3, 4, 2, 3, 4, 2, 4]
-winners	2.1	1.44568	[3, 3, 2, 3, 3, 2, 2, -2, 3, 2]
-winning	2.4	0.4899	[2, 3, 3, 2, 2, 2, 3, 3, 2, 2]
-winningly	2.3	1.48661	[1, 3, 4, 3, 3, 1, 2, 3, -1, 4]
-winnings	2.5	0.92195	[3, 4, 3, 2, 2, 3, 1, 1, 3, 3]
-winnow	-0.3	1.00499	[0, -1, 0, -2, 1, 1, -2, 0, 0, 0]
-winnower	-0.1	0.3	[0, 0, 0, 0, 0, -1, 0, 0, 0, 0]
-winnowers	-0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, -2, 0]
-winnowing	-0.1	0.53852	[0, 0, -1, 0, 0, 0, 0, 1, -1, 0]
-winnows	-0.2	0.4	[0, 0, -1, -1, 0, 0, 0, 0, 0, 0]
-wins	2.7	0.78102	[2, 2, 3, 3, 4, 4, 3, 2, 2, 2]
-wisdom	2.4	0.66332	[2, 3, 4, 2, 3, 2, 2, 2, 2, 2]
-wise	2.1	0.83066	[2, 3, 1, 4, 2, 2, 1, 2, 2, 2]
-wiseacre	-1.2	1.16619	[-2, -1, -2, -2, -2, -1, -2, 1, 1, -2]
-wiseacres	-0.1	0.9434	[-2, 1, 0, -1, 0, 1, 1, -1, 0, 0]
-wiseass	-1.8	0.6	[-2, -2, -1, -1, -2, -2, -3, -2, -1, -2]
-wiseasses	-1.5	1.36015	[-1, -2, 2, -2, -1, -3, -2, -3, -1, -2]
-wisecrack	-0.1	1.22066	[-1, -1, -1, -2, 2, 1, -1, 1, 1, 0]
-wisecracked	-0.5	0.92195	[1, 1, -1, -1, 0, -1, -2, 0, -1, -1]
-wisecracker	-0.1	0.7	[-1, 1, -1, -1, 0, 0, 0, 0, 1, 0]
-wisecrackers	0.1	1.04403	[-1, 0, 1, 1, 0, 2, 1, -1, -1, -1]
-wisecracking	-0.6	0.4899	[0, 0, -1, 0, -1, 0, -1, -1, -1, -1]
-wisecracks	-0.3	1.55242	[1, 2, -1, 2, -3, 0, 0, -2, -1, -1]
-wised	1.5	0.67082	[2, 2, 2, 1, 1, 2, 0, 1, 2, 2]
-wiseguys	0.3	1.9	[4, -1, 1, -1, 1, 2, 2, -2, -2, -1]
-wiselier	0.9	1.3	[1, 2, 2, -2, 0, 1, 3, 1, 0, 1]
-wiseliest	1.6	1.49666	[1, 4, 2, 2, 1, 2, 2, 3, -2, 1]
-wisely	1.8	0.6	[1, 2, 3, 2, 1, 2, 2, 1, 2, 2]
-wiseness	1.9	0.7	[2, 3, 2, 2, 3, 1, 1, 1, 2, 2]
-wisenheimer	-1.0	1.18322	[-1, 1, -1, -1, -1, 0, -1, -3, 0, -3]
-wisenheimers	-1.4	0.91652	[-3, -3, -2, -1, -1, -1, 0, -1, -1, -1]
-wisents	0.4	0.91652	[0, 0, 0, 0, 1, 0, 0, 0, 3, 0]
-wiser	1.2	0.87178	[1, 3, 0, 1, 1, 2, 0, 2, 1, 1]
-wises	1.3	1.48661	[3, 3, 2, -2, 2, 0, 0, 2, 2, 1]
-wisest	2.1	1.51327	[1, 3, 3, 3, 3, 2, 2, 3, -2, 3]
-wisewomen	1.3	0.9	[2, 2, 0, 0, 2, 0, 1, 2, 2, 2]
-wish	1.7	1.1	[2, 1, 1, 0, 2, 1, 3, 2, 4, 1]
-wishes	0.6	0.8	[0, 0, 1, 0, 1, 0, 2, 0, 2, 0]
-wishing	0.9	0.7	[2, 1, 1, 0, 0, 0, 1, 1, 2, 1]
-witch	-1.5	0.80623	[-1, -2, -2, -1, -3, 0, -2, -2, -1, -1]
-withdrawal	0.1	1.57797	[1, -1, 0, -2, -2, 2, -1, 1, 0, 3]
-woe	-1.8	0.6	[-3, -2, -2, -2, -1, -1, -2, -1, -2, -2]
-woebegone	-2.6	0.66332	[-3, -2, -3, -2, -2, -4, -3, -2, -2, -3]
-woebegoneness	-1.1	1.37477	[-3, 0, -1, 1, -1, -4, 0, -1, -1, -1]
-woeful	-1.9	0.83066	[-1, -2, -2, -1, -3, -3, -1, -2, -1, -3]
-woefully	-1.7	1.48661	[-1, -3, -2, 1, -3, -3, -2, -2, 1, -3]
-woefulness	-2.1	0.7	[-3, -2, -2, -1, -2, -3, -3, -1, -2, -2]
-woes	-1.9	0.83066	[-2, -2, -2, -1, -2, -3, -3, 0, -2, -2]
-woesome	-1.2	1.6	[-2, -3, -2, -1, 0, 3, -2, -2, -1, -2]
-won	2.7	0.9	[3, 4, 2, 2, 2, 4, 4, 2, 2, 2]
-wonderful	2.7	0.78102	[2, 3, 3, 2, 4, 2, 2, 3, 4, 2]
-wonderfully	2.9	0.83066	[1, 3, 3, 4, 3, 2, 3, 3, 4, 3]
-wonderfulness	2.9	0.53852	[3, 2, 3, 3, 3, 3, 3, 2, 4, 3]
-woo	2.1	1.37477	[4, 2, 1, 3, 2, 2, -1, 2, 2, 4]
-woohoo	2.3	1.1	[3, 3, 1, 4, 4, 2, 1, 1, 2, 2]
-woot	1.8	1.07703	[2, 0, 2, 2, 2, 2, 0, 4, 2, 2]
-worn	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -2, -1]
-worried	-1.2	0.74833	[-1, -1, -1, -1, -1, -2, -3, 0, -1, -1]
-worriedly	-2.0	0.44721	[-2, -2, -3, -2, -2, -2, -2, -1, -2, -2]
-worrier	-1.8	0.6	[-2, -2, -1, -2, -1, -3, -2, -2, -1, -2]
-worriers	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -1, -2, -1, -2]
-worries	-1.8	0.6	[-2, -2, -1, -2, -1, -2, -2, -3, -1, -2]
-worriment	-1.5	0.67082	[-1, -2, -1, -1, -1, -2, -1, -3, -1, -2]
-worriments	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -3, -1, -2, -2]
-worrisome	-1.7	0.64031	[-1, -1, -1, -2, -1, -2, -3, -2, -2, -2]
-worrisomely	-2.0	0.63246	[-1, -2, -1, -2, -2, -3, -2, -2, -3, -2]
-worrisomeness	-1.9	0.53852	[-2, -2, -3, -1, -2, -2, -2, -1, -2, -2]
-worrit	-2.1	0.53852	[-2, -2, -1, -2, -2, -3, -3, -2, -2, -2]
-worrits	-1.2	0.9798	[-1, -2, -2, -1, 0, 0, -1, -3, 0, -2]
-worry	-1.9	0.7	[-2, -3, -1, -3, -1, -2, -1, -2, -2, -2]
-worrying	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -1, -1, -2, -2]
-worrywart	-1.8	0.9798	[-2, -2, -2, -1, -1, -1, -1, -3, -1, -4]
-worrywarts	-1.5	0.5	[-2, -1, -2, -2, -2, -1, -1, -1, -2, -1]
-worse	-2.1	0.83066	[-2, -2, -1, -3, -4, -2, -1, -2, -2, -2]
-worsen	-2.3	0.78102	[-4, -3, -1, -2, -2, -2, -2, -3, -2, -2]
-worsened	-1.9	1.22066	[-2, -2, -2, -1, -2, -2, -4, 1, -3, -2]
-worsening	-2.0	0.44721	[-2, -3, -2, -2, -2, -2, -1, -2, -2, -2]
-worsens	-2.1	0.53852	[-2, -2, -2, -2, -1, -2, -2, -3, -3, -2]
-worser	-2.0	0.89443	[-2, -2, -4, -1, -2, -2, -2, -3, -1, -1]
-worship	1.2	1.07703	[1, 0, 0, 1, 3, 0, 2, 3, 1, 1]
-worshiped	2.4	1.0198	[1, 2, 4, 3, 4, 1, 2, 3, 2, 2]
-worshiper	1.0	1.0	[0, 0, 2, 3, 0, 2, 1, 1, 1, 0]
-worshipers	0.9	0.83066	[0, 0, 0, 2, 1, 1, 1, 2, 2, 0]
-worshipful	0.7	1.00499	[1, -1, 3, 1, 1, 1, 0, 0, 0, 1]
-worshipfully	1.1	1.3	[0, 0, 0, 1, 3, 0, 3, 3, 1, 0]
-worshipfulness	1.6	0.8	[3, 1, 2, 2, 1, 1, 3, 1, 1, 1]
-worshiping	1.0	1.18322	[0, 3, 0, 3, 0, 1, 1, 2, 0, 0]
-worshipless	-0.6	1.0198	[0, -1, -3, -1, -1, -1, 0, 0, 0, 1]
-worshipped	2.7	0.78102	[3, 2, 3, 3, 1, 4, 2, 3, 3, 3]
-worshipper	0.6	0.66332	[1, 1, 0, 0, 1, 0, 0, 2, 1, 0]
-worshippers	0.8	0.87178	[0, 1, 0, 0, 3, 1, 1, 1, 0, 1]
-worshipping	1.6	1.28062	[1, 3, 3, 3, 0, 3, 1, 0, 2, 0]
-worships	1.4	1.11355	[2, 0, 1, 3, 2, 1, 0, 3, 2, 0]
-worst	-3.1	1.04403	[-4, -4, -3, -1, -3, -4, -2, -2, -4, -4]
-worth	0.9	0.9434	[0, 0, 1, 1, 2, 1, 1, 3, 0, 0]
-worthless	-1.9	1.13578	[-3, -1, -3, -4, -1, -3, -1, -1, -1, -1]
-worthwhile	1.4	0.4899	[1, 1, 1, 2, 1, 1, 2, 1, 2, 2]
-worthy	1.9	0.53852	[2, 2, 2, 1, 1, 2, 2, 2, 3, 2]
-wow	2.8	0.9798	[2, 3, 2, 4, 4, 3, 3, 2, 1, 4]
-wowed	2.6	0.8	[3, 3, 4, 3, 2, 1, 3, 3, 2, 2]
-wowing	2.5	0.67082	[2, 2, 3, 3, 2, 3, 4, 2, 2, 2]
-wows	2.0	1.61245	[2, 3, 3, 3, 2, 1, -2, 1, 4, 3]
-wowser	-1.1	2.02237	[-3, 3, 0, 2, -2, -1, -3, -2, -2, -3]
-wowsers	1.0	2.14476	[0, -2, 4, 2, 3, 0, 1, 2, -3, 3]
-wrathful	-2.7	0.64031	[-3, -2, -2, -3, -3, -2, -4, -2, -3, -3]
-wreck	-1.9	0.7	[-1, -2, -3, -3, -2, -2, -2, -1, -1, -2]
-wrong	-2.1	1.04403	[-2, -2, -2, -2, -4, -4, -1, -1, -1, -2]
-wronged	-1.9	0.53852	[-2, -2, -2, -2, -2, -1, -3, -2, -2, -1]
-x-d	2.6	0.91652	[2, 3, 3, 4, 1, 2, 3, 4, 2, 2]
-x-p	1.7	0.45826	[2, 2, 1, 2, 2, 1, 1, 2, 2, 2]
-xd	2.8	0.87178	[3, 3, 4, 2, 3, 3, 1, 2, 4, 3]
-xp	1.6	0.4899	[2, 2, 2, 1, 1, 1, 2, 2, 1, 2]
-yay	2.4	1.0198	[1, 3, 3, 2, 2, 1, 4, 4, 2, 2]
-yeah	1.2	0.6	[1, 1, 1, 2, 1, 1, 0, 2, 1, 2]
-yearning	0.5	1.0247	[0, 1, 0, 1, 0, 3, 0, 1, -1, 0]
-yeees	1.7	1.00499	[1, 3, 1, 2, 1, 1, 4, 2, 1, 1]
-yep	1.2	0.4	[1, 1, 1, 1, 1, 1, 2, 2, 1, 1]
-yes	1.7	0.78102	[1, 2, 2, 1, 1, 1, 3, 3, 1, 2]
-youthful	1.3	0.45826	[1, 2, 1, 2, 1, 1, 1, 1, 2, 1]
-yucky	-1.8	0.6	[-2, -1, -1, -2, -2, -1, -2, -2, -3, -2]
-yummy	2.4	1.0198	[1, 2, 4, 3, 2, 2, 3, 1, 4, 2]
-zealot	-1.9	1.04403	[-2, -3, -1, -2, -1, -3, -4, -1, -1, -1]
-zealots	-0.8	1.83303	[-1, -2, -1, -2, -2, 1, -2, 4, -1, -2]
-zealous	0.5	1.43178	[2, -1, 2, 1, 0, 0, 3, 0, -2, 0]
-{:	1.8	0.9798	[1, 3, 2, 2, 1, 1, 4, 2, 1, 1]
-|-0	-1.2	0.74833	[0, -2, -1, -1, -1, -1, -1, -1, -1, -3]
-|-:	-0.8	0.74833	[-1, -2, 0, -1, 0, -2, -1, -1, 0, 0]
-|-:>	-1.6	0.4899	[-1, -2, -2, -2, -2, -1, -1, -2, -2, -1]
-|-o	-1.2	0.9798	[-1, 0, -1, -1, -1, -1, -1, -4, -1, -1]
-|:	-0.5	1.68819	[2, -3, -1, 0, -1, -1, -1, -2, -1, 3]
-|;-)	2.2	1.32665	[4, 1, 1, 1, 3, 2, 4, 1, 4, 1]
-|=	-0.4	1.56205	[2, -2, -1, 0, -1, -1, -1, -2, -1, 3]
-|^:	-1.1	0.7	[-2, 0, -1, -1, 0, -1, -1, -2, -2, -1]
-|o:	-0.9	0.53852	[-1, 0, -1, -2, -1, 0, -1, -1, -1, -1]
-||-:	-2.3	0.45826	[-2, -2, -2, -3, -3, -3, -2, -2, -2, -2]
-}:	-2.1	0.83066	[-1, -1, -3, -2, -3, -2, -2, -1, -3, -3]
-}:(	-2.0	0.63246	[-3, -1, -2, -1, -3, -2, -2, -2, -2, -2]
-}:)	0.4	1.42829	[1, 1, -2, 1, 2, -2, 1, -1, 2, 1]
-}:-(	-2.1	0.7	[-2, -1, -2, -2, -2, -4, -2, -2, -2, -2]
-}:-)	0.3	1.61555	[1, 1, -2, 1, -1, -3, 2, 2, 1, 1]
\ No newline at end of file
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+/-:	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -1, -2, -3, -1]
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+;d	0.8	1.249	[2, -1, 2, 1, 1, 1, -2, 2, 1, 1]
+;D	0.8	1.249	[2, -1, 2, 1, 1, 1, -2, 2, 1, 1]
+;]	0.6	1.11355	[1, -1, 1, 1, 1, 1, -2, 2, 1, 1]
+;^)	1.4	0.91652	[2, 2, 1, 2, 1, 2, -1, 1, 2, 2]
+</3	-3.0	1.0	[-3, -3, -4, -3, -4, -1, -2, -2, -4, -4]
+<3	1.9	1.13578	[3, 2, 1, 3, 1, 4, 2, 0, 1, 2]
+<:	2.1	1.13578	[3, 2, 4, 1, 1, 1, 1, 2, 4, 2]
+<:-|	-1.4	0.66332	[-1, -1, -1, -2, -2, -1, -3, -1, -1, -1]
+=)	2.2	1.16619	[4, 2, 3, 3, 2, 1, 1, 4, 1, 1]
+=-3	2.0	0.63246	[2, 2, 2, 3, 1, 3, 1, 2, 2, 2]
+=-d	2.4	0.91652	[2, 2, 1, 3, 2, 4, 2, 4, 2, 2]
+=-D	2.4	0.91652	[2, 2, 1, 3, 2, 4, 2, 4, 2, 2]
+=/	-1.4	0.91652	[-1, -1, -1, -1, -1, -2, -1, -1, -4, -1]
+=3	2.1	0.7	[3, 1, 2, 1, 2, 3, 2, 2, 3, 2]
+=d	2.3	0.45826	[3, 2, 2, 2, 2, 3, 2, 2, 2, 3]
+=D	2.3	0.45826	[3, 2, 2, 2, 2, 3, 2, 2, 2, 3]
+=l	-1.2	0.6	[-2, -1, -1, 0, -2, -1, -2, -1, -1, -1]
+=\	-1.2	0.6	[-2, -1, -1, 0, -2, -1, -2, -1, -1, -1]
+=]	1.6	0.8	[2, 1, 3, 1, 1, 1, 2, 3, 1, 1]
+=p	1.3	0.9	[2, 1, 2, 1, 2, -1, 1, 2, 2, 1]
+=|	-0.8	0.87178	[-2, -1, -2, 1, 0, -1, 0, -1, -1, -1]
+>-:	-2.0	0.89443	[-2, -3, -2, -4, -1, -1, -1, -2, -2, -2]
+>.<	-1.3	0.45826	[-1, -2, -1, -2, -2, -1, -1, -1, -1, -1]
+>:	-2.1	1.13578	[-4, -1, -1, -4, -2, -3, -1, -1, -2, -2]
+>:(	-2.7	0.64031	[-2, -3, -2, -3, -3, -2, -4, -2, -3, -3]
+>:)	0.4	1.42829	[1, 1, 2, 1, -1, -2, 1, 2, -2, 1]
+>:-(	-2.7	0.78102	[-3, -2, -3, -2, -4, -2, -3, -2, -2, -4]
+>:-)	-0.4	1.68523	[1, 2, 1, -2, -2, -1, -1, -3, -1, 2]
+>:/	-1.6	0.8	[-1, -2, -1, -3, -1, -1, -1, -1, -2, -3]
+>:o	-1.2	1.16619	[-3, -1, -2, 0, -2, -2, 0, -1, 1, -2]
+>:p	1.0	0.7746	[-1, 1, 1, 2, 1, 2, 1, 1, 1, 1]
+>:[	-2.1	0.53852	[-2, -2, -2, -2, -3, -3, -2, -1, -2, -2]
+>:\	-1.7	0.64031	[-1, -2, -1, -2, -2, -3, -1, -1, -2, -2]
+>;(	-2.9	0.7	[-3, -4, -3, -2, -2, -3, -3, -3, -2, -4]
+>;)	0.1	1.04403	[-1, 1, 0, -1, 2, 0, -1, 1, 1, -1]
+>_>^	2.1	0.9434	[2, 2, 1, 4, 3, 2, 1, 3, 1, 2]
+@:	-2.1	0.9434	[-3, -2, -3, -1, -2, -4, -1, -2, -1, -2]
+@>-->--	2.1	1.22066	[1, 1, 0, 2, 4, 2, 4, 2, 3, 2]
+@}-;-'---	2.2	1.32665	[0, 1, 3, 2, 1, 4, 4, 1, 3, 3]
+aas	2.5	0.80623	[2, 3, 3, 4, 1, 2, 3, 2, 2, 3]
+aayf	2.7	0.78102	[2, 3, 2, 4, 3, 2, 2, 3, 4, 2]
+afu	-2.9	0.83066	[-3, -3, -3, -3, -3, -1, -4, -4, -2, -3]
+alol	2.8	0.74833	[2, 2, 2, 3, 3, 2, 3, 4, 4, 3]
+ambw	2.9	0.7	[2, 3, 4, 2, 3, 2, 3, 3, 4, 3]
+aml	3.4	0.66332	[4, 3, 2, 4, 3, 3, 4, 4, 3, 4]
+atab	-1.9	1.22066	[-2, 0, -1, -2, -1, -1, -2, -4, -4, -2]
+awol	-1.3	0.78102	[0, -1, -1, -1, -1, -1, -2, -2, -3, -1]
+ayc	0.2	0.9798	[0, 1, -1, 1, 0, 1, 0, -1, 2, -1]
+ayor	-1.2	0.6	[-1, -1, -2, -2, -1, -1, -1, 0, -2, -1]
+aug-00	0.3	1.18743	[2, 0, -2, 0, 0, 1, -1, 2, 1, 0]
+bfd	-2.7	0.78102	[-3, -2, -4, -2, -3, -2, -3, -2, -4, -2]
+bfe	-2.6	1.35647	[-3, -3, -4, -2, -3, -2, 1, -3, -4, -3]
+bff	2.9	0.83066	[3, 3, 4, 2, 4, 2, 2, 3, 4, 2]
+bffn	1.0	0.89443	[2, 1, -1, 1, 0, 1, 2, 1, 2, 1]
+bl	2.3	1.1	[2, 1, 4, 1, 2, 2, 4, 3, 1, 3]
+bsod	-2.2	1.07703	[-1, -4, -3, -3, 0, -2, -3, -2, -2, -2]
+btd	-2.1	0.83066	[-1, -2, -3, -3, -3, -1, -3, -2, -1, -2]
+btdt	-0.1	1.22066	[0, -1, 0, -1, 0, 3, 1, -1, -1, -1]
+bz	0.4	1.35647	[-1, 0, 0, 0, 4, 1, -1, 1, 0, 0]
+b^d	2.6	0.8	[3, 2, 2, 4, 3, 1, 3, 3, 3, 2]
+cwot	-2.3	0.45826	[-3, -2, -2, -2, -2, -3, -2, -3, -2, -2]
+d-':	-2.5	0.67082	[-3, -3, -2, -2, -2, -4, -2, -3, -2, -2]
+d8	-3.2	0.6	[-3, -3, -3, -3, -4, -4, -2, -3, -3, -4]
+d:	-2.9	0.83066	[-3, -3, -3, -3, -2, -4, -1, -3, -3, -4]
+d:<	-3.2	0.9798	[-4, -4, -4, -1, -3, -3, -4, -2, -3, -4]
+d;	-2.9	0.83066	[-1, -3, -3, -3, -3, -4, -2, -3, -3, -4]
+d=	-3.0	0.89443	[-4, -3, -3, -3, -2, -4, -1, -3, -3, -4]
+doa	-2.3	1.00499	[-2, -3, -3, -2, -2, -2, -4, 0, -2, -3]
+dx	-3.0	0.63246	[-3, -2, -3, -3, -4, -3, -4, -2, -3, -3]
+ez	1.5	0.67082	[3, 2, 2, 1, 1, 1, 2, 1, 1, 1]
+fav	2.4	0.91652	[3, 1, 3, 2, 2, 3, 1, 2, 3, 4]
+fcol	-1.8	0.74833	[-2, -2, -1, -2, -1, -2, -1, -3, -3, -1]
+ff	1.8	1.249	[4, 2, 1, 2, 1, 3, 3, 0, 2, 0]
+ffs	-2.8	0.9798	[-2, -2, -3, -3, -2, -4, -4, -4, -1, -3]
+fkm	-2.4	1.35647	[-4, -1, -4, -2, -2, -3, -1, 0, -3, -4]
+foaf	1.8	1.249	[2, 1, 2, 0, 4, 1, 1, 1, 2, 4]
+ftw	2.0	0.7746	[2, 1, 1, 2, 2, 2, 3, 3, 1, 3]
+fu	-3.7	0.45826	[-3, -4, -4, -3, -3, -4, -4, -4, -4, -4]
+fubar	-3.0	1.09545	[-4, -3, -3, -4, -3, -3, -3, -4, 0, -3]
+fwb	2.5	1.43178	[2, 3, 4, 0, 1, 2, 4, 1, 4, 4]
+fyi	0.8	1.66132	[0, 1, 0, -1, 0, 0, 4, 4, 0, 0]
+fysa	0.4	0.91652	[0, 0, 0, 1, 0, 3, 0, 0, 0, 0]
+g1	1.4	0.4899	[2, 1, 1, 1, 2, 1, 2, 1, 1, 2]
+gg	1.2	0.74833	[0, 2, 2, 1, 0, 1, 2, 2, 1, 1]
+gga	1.7	0.45826	[2, 2, 1, 2, 2, 1, 2, 2, 1, 2]
+gigo	-0.6	1.11355	[-2, -1, 1, 0, 0, 0, -1, -2, -2, 1]
+gj	2.0	1.0	[2, 1, 2, 1, 1, 3, 4, 2, 3, 1]
+gl	1.3	0.64031	[1, 1, 1, 1, 3, 1, 1, 2, 1, 1]
+gla	2.5	0.92195	[1, 2, 2, 4, 2, 4, 2, 3, 3, 2]
+gn	1.2	0.74833	[1, 1, 1, 1, 3, 1, 1, 2, 1, 0]
+gr8	2.7	0.78102	[1, 3, 3, 4, 3, 2, 3, 2, 3, 3]
+grrr	-0.4	1.42829	[-2, -1, 0, 1, -2, -1, -1, 3, 0, -1]
+gt	1.1	0.53852	[1, 1, 1, 1, 1, 1, 2, 1, 0, 2]
+h&k	2.3	0.78102	[2, 2, 2, 3, 4, 2, 3, 2, 1, 2]
+hagd	2.2	0.87178	[2, 2, 3, 2, 1, 3, 4, 1, 2, 2]
+hagn	2.2	0.87178	[2, 2, 3, 2, 1, 3, 4, 1, 2, 2]
+hago	1.2	0.4	[1, 2, 1, 1, 1, 2, 1, 1, 1, 1]
+hak	1.9	0.7	[3, 1, 2, 2, 1, 2, 3, 2, 1, 2]
+hand	2.2	0.87178	[2, 2, 1, 3, 2, 3, 4, 1, 2, 2]
+hho1/2k	1.4	1.11355	[1, -1, 2, 3, 1, 1, 1, 2, 3, 1]
+hhoj	2.0	1.09545	[4, 2, 1, 1, 2, 1, 1, 4, 2, 2]
+hhok	0.9	0.9434	[1, 2, 1, 0, -1, 0, 2, 1, 1, 2]
+hugz	2.0	0.7746	[2, 3, 1, 3, 1, 3, 1, 2, 2, 2]
+hi5	1.9	0.53852	[2, 2, 2, 1, 3, 2, 1, 2, 2, 2]
+idk	-0.4	0.66332	[0, 0, 0, 0, -1, -2, 0, 0, 0, -1]
+ijs	0.7	1.84662	[0, -1, 0, -1, 0, 4, 0, 4, -1, 2]
+ilu	3.4	0.66332	[3, 4, 3, 4, 2, 3, 4, 3, 4, 4]
+iluaaf	2.7	1.1	[3, 3, 3, 2, 3, 0, 4, 3, 2, 4]
+ily	3.4	0.66332	[3, 4, 3, 4, 2, 3, 4, 3, 4, 4]
+ily2	2.6	0.66332	[3, 2, 3, 2, 3, 2, 3, 4, 2, 2]
+iou	0.7	1.34536	[0, 0, -1, 2, 0, 0, 0, 4, 1, 1]
+iyq	2.3	1.18743	[3, 3, 1, 1, 2, 1, 4, 4, 3, 1]
+j/j	2.0	1.34164	[4, 1, 1, 1, 1, 4, 4, 1, 2, 1]
+j/k	1.6	1.2	[1, 2, 1, 3, 0, 0, 2, 2, 1, 4]
+j/p	1.4	0.66332	[1, 1, 0, 2, 1, 2, 2, 2, 1, 2]
+j/t	-0.2	1.46969	[1, -1, -1, -2, 1, 1, 2, -2, 1, -2]
+j/w	1.0	1.0	[1, 1, 1, 3, 0, 0, 0, 2, 0, 2]
+j4f	1.4	0.8	[2, 1, 1, 0, 3, 1, 1, 1, 2, 2]
+j4g	1.7	1.18743	[1, 4, 1, 1, 3, 1, 3, 0, 2, 1]
+jho	0.8	0.4	[1, 1, 1, 1, 0, 1, 1, 1, 0, 1]
+jhomf	1.0	0.63246	[1, 1, 1, 0, 1, 0, 2, 2, 1, 1]
+jj	1.0	0.63246	[1, 1, 1, 1, 2, 0, 2, 1, 1, 0]
+jk	0.9	1.22066	[1, 0, 0, 1, 0, 0, 2, 1, 4, 0]
+jp	0.8	0.74833	[1, 1, 1, 0, 2, 0, 2, 0, 1, 0]
+jt	0.9	0.83066	[1, 1, 0, 2, 2, 0, 2, 0, 1, 0]
+jw	1.6	1.68523	[3, 0, 0, 0, 0, 0, 3, 4, 2, 4]
+jealz	-1.2	0.9798	[-1, -1, -1, 1, -2, -2, -1, -3, -1, -1]
+k4y	2.3	1.00499	[2, 1, 1, 2, 4, 2, 3, 4, 2, 2]
+kfy	2.3	0.64031	[2, 2, 2, 1, 3, 2, 3, 3, 2, 3]
+kia	-3.2	0.6	[-3, -3, -3, -4, -3, -2, -3, -3, -4, -4]
+kk	1.5	1.0247	[2, 1, 0, 0, 1, 2, 3, 3, 2, 1]
+kmuf	2.2	1.4	[2, 2, 2, 3, 4, 3, -1, 1, 4, 2]
+l	2.0	0.7746	[2, 1, 2, 3, 2, 3, 1, 3, 2, 1]
+l&r	2.2	0.74833	[3, 2, 2, 3, 1, 3, 1, 3, 2, 2]
+laoj	1.3	1.73494	[1, -2, -1, 3, 3, 2, 4, 1, 1, 1]
+lmao	2.0	1.18322	[3, 0, 3, 0, 3, 1, 3, 2, 3, 2]
+lmbao	1.8	1.77764	[3, 2, 2, 2, 1, 3, -3, 2, 4, 2]
+lmfao	2.5	1.28452	[3, 2, 3, 3, 3, -1, 4, 2, 3, 2]
+lmso	2.7	0.78102	[3, 3, 4, 3, 3, 1, 3, 3, 2, 2]
+lol	2.9	0.83066	[4, 2, 2, 2, 4, 2, 3, 3, 4, 3]
+lolz	2.7	0.78102	[2, 3, 3, 2, 2, 4, 4, 3, 2, 2]
+lts	1.6	0.66332	[1, 1, 2, 2, 1, 3, 1, 1, 2, 2]
+ly	2.6	0.91652	[2, 2, 1, 3, 4, 4, 3, 2, 2, 3]
+ly4e	2.7	0.78102	[3, 3, 3, 2, 1, 3, 3, 4, 2, 3]
+lya	3.3	0.78102	[3, 4, 4, 4, 2, 2, 3, 4, 3, 4]
+lyb	3.0	0.63246	[3, 3, 4, 3, 2, 3, 2, 4, 3, 3]
+lyl	3.1	0.7	[4, 3, 4, 3, 2, 3, 3, 2, 4, 3]
+lylab	2.7	0.78102	[3, 3, 3, 1, 3, 4, 2, 2, 3, 3]
+lylas	2.6	0.8	[3, 3, 3, 1, 3, 4, 2, 2, 2, 3]
+lylb	1.6	1.56205	[2, 2, 3, -2, 4, 1, 3, 1, 1, 1]
+m8	1.4	1.0198	[3, 0, 1, 0, 1, 3, 2, 2, 1, 1]
+mia	-1.2	0.4	[-2, -1, -1, -2, -1, -1, -1, -1, -1, -1]
+mml	2.0	1.0	[1, 1, 2, 3, 3, 2, 1, 2, 4, 1]
+mofo	-2.4	2.2	[-4, -4, -4, 0, -3, -2, -2, -4, 3, -4]
+muah	2.8	1.07703	[1, 2, 4, 4, 4, 2, 4, 2, 2, 3]
+mubar	-1.0	2.36643	[-4, -2, -3, -2, -2, -2, 1, 4, 2, -2]
+musm	0.9	2.07123	[-1, 1, 1, 1, 4, 3, 1, -4, 1, 2]
+mwah	2.5	0.80623	[2, 2, 2, 4, 2, 3, 2, 2, 4, 2]
+n1	1.9	1.04403	[1, 1, 3, 2, 2, 3, 4, 1, 1, 1]
+nbd	1.3	1.34536	[2, 1, 0, 0, 0, 4, 2, 0, 3, 1]
+nbif	-0.5	0.67082	[-1, -2, 0, 0, 0, 0, -1, -1, 0, 0]
+nfc	-2.7	0.9	[-3, -2, -2, -3, -1, -2, -4, -3, -4, -3]
+nfw	-2.4	1.0198	[-2, -2, -1, -3, -1, -2, -4, -3, -4, -2]
+nh	2.2	0.6	[2, 2, 2, 2, 1, 3, 3, 3, 2, 2]
+nimby	-0.8	0.6	[0, 0, -1, 0, -1, -2, -1, -1, -1, -1]
+nimjd	-0.7	0.78102	[0, -2, -1, -2, 0, -1, 0, 0, 0, -1]
+nimq	-0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, -2, 0]
+nimy	-1.4	1.68523	[-1, -2, -3, -2, -1, 2, -3, 0, 0, -4]
+nitl	-1.5	0.92195	[-1, -1, -2, -3, -1, -3, -1, -2, 0, -1]
+nme	-2.1	1.13578	[-1, -2, -2, -1, -4, -2, -3, -3, 0, -3]
+noyb	-0.7	1.67631	[-1, -2, 0, -1, -1, -2, -2, -1, 4, -1]
+np	1.4	1.0198	[0, 1, 1, 1, 1, 2, 2, 4, 1, 1]
+ntmu	1.4	0.66332	[1, 1, 0, 1, 2, 2, 2, 2, 2, 1]
+o-8	-0.5	1.5	[2, -1, 0, 0, -2, -2, 0, -2, 2, -2]
+o-:	-0.3	1.18743	[2, -1, 0, 0, -1, -2, 0, -2, 1, 0]
+o-|	-1.1	0.53852	[-1, -1, -1, 0, -1, -1, -1, -2, -2, -1]
+o.o	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
+O.o	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
+o.O	-0.6	0.8	[-1, -1, -2, 0, 1, 0, -1, 0, -1, -1]
+o:	-0.2	0.87178	[-1, 0, -1, -2, 0, 1, 0, 1, 0, 0]
+o:)	1.5	0.67082	[3, 1, 1, 2, 2, 2, 1, 1, 1, 1]
+o:-)	2.0	1.18322	[1, 4, 1, 2, 4, 1, 1, 2, 3, 1]
+o:-3	2.2	0.9798	[1, 4, 2, 3, 3, 2, 1, 2, 3, 1]
+o:3	2.3	0.78102	[3, 3, 2, 2, 1, 2, 4, 2, 2, 2]
+o:<	-0.3	1.1	[-1, -1, -2, 0, -1, 0, 1, 2, 0, -1]
+o;^)	1.6	0.8	[1, 2, 1, 2, 1, 2, 2, 0, 3, 2]
+ok	1.6	1.42829	[0, 0, 1, 1, 1, 4, 3, 4, 1, 1]
+o_o	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
+O_o	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
+o_O	-0.5	0.92195	[0, -1, 0, -2, -2, 0, -1, 1, 0, 0]
+pita	-2.4	1.2	[-2, -1, -1, -4, -4, -2, -4, -2, -3, -1]
+pls	0.3	0.45826	[0, 1, 1, 1, 0, 0, 0, 0, 0, 0]
+plz	0.3	0.45826	[0, 1, 1, 1, 0, 0, 0, 0, 0, 0]
+pmbi	0.8	1.32665	[3, 0, 0, 1, 1, -2, 2, 2, 0, 1]
+pmfji	0.3	0.78102	[0, 0, 1, 0, 2, -1, 0, 1, 0, 0]
+pmji	0.7	1.00499	[1, 2, 0, -1, 0, 0, 2, 2, 1, 0]
+po	-2.6	0.91652	[-2, -3, -4, -3, -3, -3, -1, -3, -1, -3]
+ptl	2.6	1.11355	[3, 4, 2, 4, 1, 2, 3, 1, 4, 2]
+pu	-1.1	1.3	[-3, -1, -3, -2, -1, -1, -1, -1, 1, 1]
+qq	-2.2	0.6	[-2, -2, -1, -3, -3, -2, -2, -3, -2, -2]
+qt	1.8	0.6	[2, 2, 1, 2, 1, 3, 2, 1, 2, 2]
+r&r	2.4	1.0198	[2, 4, 2, 3, 1, 4, 2, 2, 1, 3]
+rofl	2.7	0.78102	[3, 2, 2, 2, 4, 4, 2, 3, 3, 2]
+roflmao	2.5	1.11803	[4, 2, 2, 4, 1, 1, 2, 4, 3, 2]
+rotfl	2.6	0.66332	[3, 2, 3, 3, 1, 3, 3, 3, 2, 3]
+rotflmao	2.8	1.07703	[4, 3, 2, 4, 1, 1, 4, 3, 3, 3]
+rotflmfao	2.5	1.11803	[3, 4, 1, 3, 3, 3, 0, 3, 2, 3]
+rotflol	3.0	1.09545	[1, 4, 4, 4, 2, 2, 2, 3, 4, 4]
+rotgl	2.9	0.7	[4, 3, 2, 2, 3, 3, 3, 2, 4, 3]
+rotglmao	1.8	2.4	[3, 3, 4, 3, -1, 1, 4, -4, 2, 3]
+s:	-1.1	0.83066	[-1, -1, -2, -2, -1, -1, -2, -1, 1, -1]
+sapfu	-1.1	1.57797	[-2, 0, -3, -1, -1, 1, -2, 2, -2, -3]
+sete	2.8	0.87178	[3, 3, 3, 2, 3, 3, 4, 4, 1, 2]
+sfete	2.7	0.78102	[4, 3, 3, 3, 2, 4, 2, 2, 2, 2]
+sgtm	2.4	1.0198	[2, 1, 1, 2, 3, 3, 2, 2, 4, 4]
+slap	0.6	2.15407	[2, -1, 1, -1, 0, 4, -3, 4, 1, -1]
+slaw	2.1	1.04403	[3, 2, 0, 2, 2, 2, 3, 1, 4, 2]
+smh	-1.3	0.64031	[-2, -1, 0, -1, -1, -2, -2, -1, -2, -1]
+snafu	-2.5	1.11803	[-3, -4, -3, -3, -1, 0, -2, -3, -3, -3]
+sob	-2.8	0.9798	[-3, -4, -3, -2, -2, -1, -2, -4, -4, -3]
+swak	2.3	1.00499	[2, 2, 2, 1, 4, 2, 3, 2, 1, 4]
+tgif	2.3	1.34536	[1, 3, 3, 3, -1, 2, 4, 2, 3, 3]
+thks	1.4	0.4899	[1, 2, 1, 2, 1, 2, 1, 1, 2, 1]
+thx	1.5	0.92195	[0, 1, 3, 2, 1, 2, 1, 1, 3, 1]
+tia	2.3	0.9	[3, 1, 2, 1, 4, 3, 2, 3, 2, 2]
+tmi	-0.3	1.61555	[-1, -1, 2, -1, 1, -2, -2, -1, 3, -1]
+tnx	1.1	0.53852	[2, 1, 1, 0, 1, 1, 2, 1, 1, 1]
+true	1.8	1.32665	[2, 1, 1, 0, 1, 4, 3, 1, 4, 1]
+tx	1.5	0.92195	[3, 2, 1, 0, 2, 1, 3, 1, 1, 1]
+txs	1.1	0.7	[1, 2, 0, 1, 2, 0, 1, 2, 1, 1]
+ty	1.6	0.66332	[1, 2, 3, 1, 2, 2, 1, 2, 1, 1]
+tyvm	2.5	1.11803	[2, 2, 1, 3, 1, 4, 2, 4, 2, 4]
+urw	1.9	1.13578	[1, 2, 1, 2, 4, 2, 4, 1, 1, 1]
+vbg	2.1	1.75784	[2, 3, 3, 3, 3, -3, 3, 2, 2, 3]
+vbs	3.1	0.53852	[2, 3, 3, 3, 4, 4, 3, 3, 3, 3]
+vip	2.3	1.00499	[2, 1, 1, 3, 4, 2, 2, 4, 2, 2]
+vwd	2.6	0.91652	[4, 2, 4, 2, 1, 3, 3, 2, 3, 2]
+vwp	2.1	0.7	[3, 1, 2, 2, 3, 2, 2, 3, 1, 2]
+wag	-0.2	0.74833	[-1, 0, 0, 0, 0, 0, -2, 1, 0, 0]
+wd	2.7	1.1	[3, 1, 4, 3, 4, 2, 1, 3, 2, 4]
+wilco	0.9	0.9434	[1, 3, 1, 0, 1, 0, 2, 1, 0, 0]
+wp	1.0	0.0	[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+wtf	-2.8	0.74833	[-4, -3, -2, -3, -2, -2, -2, -4, -3, -3]
+wtg	2.1	0.7	[1, 3, 2, 3, 2, 2, 2, 1, 2, 3]
+wth	-2.4	0.4899	[-2, -3, -2, -3, -2, -2, -2, -3, -3, -2]
+x-d	2.7	0.78102	[1, 3, 4, 2, 3, 3, 3, 2, 3, 3]
+x-p	1.8	0.87178	[2, 1, 3, 1, 3, 1, 3, 1, 2, 1]
+xd	2.7	0.9	[1, 4, 4, 3, 2, 2, 3, 3, 2, 3]
+xlnt	3.0	0.89443	[4, 3, 3, 1, 4, 4, 3, 3, 3, 2]
+xoxo	3.0	0.7746	[2, 2, 4, 2, 3, 3, 4, 3, 3, 4]
+xoxozzz	2.3	0.78102	[3, 1, 2, 2, 2, 2, 3, 2, 4, 2]
+xp	1.2	0.4	[1, 1, 1, 1, 2, 1, 2, 1, 1, 1]
+xqzt	1.6	1.42829	[0, 2, 1, 2, 4, -1, 3, 1, 1, 3]
+xtc	0.8	1.93907	[2, 0, -3, 3, 3, -1, 3, 1, -1, 1]
+yolo	1.1	0.83066	[0, 1, 1, 2, 1, 1, 1, 3, 0, 1]
+yoyo	0.4	1.85472	[-1, 0, -1, -1, 4, 2, -2, 2, 2, -1]
+yvw	1.6	0.4899	[1, 2, 1, 1, 2, 2, 2, 1, 2, 2]
+yw	1.8	1.32665	[1, 1, 1, 4, 1, 1, 4, 0, 3, 2]
+ywia	2.5	1.11803	[3, 2, 3, 4, 1, 1, 1, 3, 3, 4]
+zzz	-1.2	0.87178	[0, -1, 0, -1, -3, -1, -1, -2, -2, -1]
+[-;	0.5	1.28452	[1, -1, -1, 1, 1, 1, 2, -2, 2, 1]
+[:	1.3	0.45826	[1, 1, 2, 1, 2, 2, 1, 1, 1, 1]
+[;	1.0	1.34164	[2, 1, 2, 2, 1, 2, 2, -2, -1, 1]
+[=	1.7	0.64031	[2, 2, 1, 1, 1, 2, 2, 3, 2, 1]
+\-:	-1.0	1.18322	[-3, -1, -1, -1, -1, -1, 2, -2, -1, -1]
+\:	-1.0	0.0	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
+\:<	-1.7	1.18743	[-1, -3, -2, -2, -3, -3, -2, -1, 1, -1]
+\=	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -1, -2, -1, -1]
+\^:	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -1, -2, -2, -1]
+\o/	2.2	0.9798	[2, 1, 1, 2, 4, 2, 2, 4, 2, 2]
+\o:	-1.2	0.4	[-1, -1, -1, -1, -2, -1, -1, -2, -1, -1]
+]-:	-2.1	0.53852	[-2, -3, -3, -2, -2, -2, -1, -2, -2, -2]
+]:	-1.6	0.66332	[-1, -2, -1, -2, -3, -2, -1, -1, -1, -2]
+]:<	-2.5	0.80623	[-2, -2, -2, -3, -4, -2, -2, -2, -2, -4]
+^<_<	1.4	1.11355	[3, 1, 3, 2, 1, 1, 1, -1, 2, 1]
+^urs	-2.8	0.6	[-2, -3, -3, -2, -3, -3, -2, -3, -4, -3]
+abandon	-1.9	0.53852	[-1, -2, -2, -2, -2, -3, -2, -2, -1, -2]
+abandoned	-2.0	1.09545	[-1, -1, -3, -2, -1, -4, -1, -3, -3, -1]
+abandoner	-1.9	0.83066	[-1, -1, -3, -2, -1, -3, -1, -2, -3, -2]
+abandoners	-1.9	0.83066	[-2, -3, -2, -3, -2, -1, -2, -2, 0, -2]
+abandoning	-1.6	0.8	[-3, -2, -3, -2, -1, -1, -1, -1, -1, -1]
+abandonment	-2.4	1.0198	[-4, -2, -1, -4, -2, -1, -2, -3, -3, -2]
+abandonments	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
+abandons	-1.3	0.9	[-2, -1, -1, -2, -1, -2, -1, -2, 1, -2]
+abducted	-2.3	1.18743	[-3, -1, 0, -3, -1, -3, -4, -2, -3, -3]
+abduction	-2.8	0.87178	[-4, -3, -3, -4, -1, -3, -2, -2, -3, -3]
+abductions	-2.0	1.41421	[-3, -4, -1, -3, -1, -3, 1, -2, -1, -3]
+abhor	-2.0	1.09545	[-3, -3, -1, -1, -2, -1, -3, -3, 0, -3]
+abhorred	-2.4	1.49666	[-4, -4, 0, -3, -2, -1, -4, -3, -3, 0]
+abhorrent	-3.1	1.3	[-4, -4, -4, -2, 0, -4, -2, -3, -4, -4]
+abhors	-2.9	1.51327	[0, -4, -3, -3, -4, -4, 0, -4, -3, -4]
+abilities	1.0	0.63246	[1, 2, 0, 1, 0, 1, 1, 1, 1, 2]
+ability	1.3	0.64031	[1, 1, 1, 0, 1, 2, 2, 2, 2, 1]
+aboard	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+absentee	-1.1	0.53852	[-1, -1, 0, -2, -1, -1, -2, -1, -1, -1]
+absentees	-0.8	0.6	[-1, 0, 0, -1, -1, 0, -2, -1, -1, -1]
+absolve	1.2	1.46969	[2, -3, 2, 2, 1, 1, 2, 1, 2, 2]
+absolved	1.5	0.92195	[3, 1, 2, 1, 0, 2, 3, 1, 1, 1]
+absolves	1.3	1.00499	[3, 1, 1, 0, 0, 2, 3, 1, 1, 1]
+absolving	1.6	0.8	[3, 1, 2, 1, 1, 2, 3, 1, 1, 1]
+abuse	-3.2	0.6	[-4, -2, -3, -4, -3, -4, -3, -3, -3, -3]
+abused	-2.3	0.64031	[-2, -2, -3, -2, -2, -4, -2, -2, -2, -2]
+abuser	-2.6	0.4899	[-3, -2, -3, -3, -2, -3, -2, -2, -3, -3]
+abusers	-2.6	1.0198	[-2, -3, -3, -3, -3, -2, -3, -4, -3, 0]
+abuses	-2.6	0.66332	[-3, -2, -3, -3, -3, -3, -1, -2, -3, -3]
+abusing	-2.0	1.41421	[-1, -2, -2, -4, -4, -2, -3, -1, 1, -2]
+abusive	-3.2	0.74833	[-4, -3, -3, -4, -4, -3, -4, -2, -3, -2]
+abusively	-2.8	0.6	[-3, -4, -3, -2, -3, -2, -2, -3, -3, -3]
+abusiveness	-2.5	0.92195	[-2, -4, -2, -3, -2, -3, -4, -2, -1, -2]
+abusivenesses	-3.0	0.63246	[-3, -3, -4, -3, -4, -2, -2, -3, -3, -3]
+accept	1.6	0.91652	[2, 1, 2, 1, 1, 2, 4, 1, 1, 1]
+acceptabilities	1.6	0.66332	[0, 2, 2, 2, 1, 2, 2, 2, 1, 2]
+acceptability	1.1	0.53852	[1, 0, 1, 2, 1, 2, 1, 1, 1, 1]
+acceptable	1.3	0.45826	[1, 2, 1, 1, 1, 2, 1, 1, 2, 1]
+acceptableness	1.3	0.9	[1, 0, 2, 1, 2, 1, 1, 0, 2, 3]
+acceptably	1.5	0.67082	[3, 2, 1, 1, 1, 2, 1, 1, 2, 1]
+acceptance	2.0	0.63246	[3, 1, 3, 2, 1, 2, 2, 2, 2, 2]
+acceptances	1.7	0.78102	[3, 1, 1, 1, 2, 2, 1, 2, 3, 1]
+acceptant	1.6	0.8	[0, 1, 2, 2, 2, 1, 2, 1, 3, 2]
+acceptation	1.3	0.78102	[0, 1, 2, 1, 1, 1, 1, 3, 2, 1]
+acceptations	0.9	0.83066	[1, 2, 0, 2, 0, 1, 0, 2, 1, 0]
+accepted	1.1	0.3	[1, 1, 1, 1, 1, 2, 1, 1, 1, 1]
+accepting	1.6	0.66332	[2, 2, 2, 1, 1, 2, 1, 3, 1, 1]
+accepts	1.3	0.45826	[1, 2, 1, 1, 1, 2, 2, 1, 1, 1]
+accident	-2.1	0.83066	[-2, -2, -1, -3, -4, -2, -2, -1, -2, -2]
+accidental	-0.3	0.45826	[-1, -1, 0, 0, 0, 0, 0, 0, -1, 0]
+accidentally	-1.4	0.91652	[-2, 0, -2, 0, -3, -1, -1, -1, -2, -2]
+accidents	-1.3	0.78102	[-1, -1, -1, -1, -2, 0, -3, -1, -2, -1]
+accomplish	1.8	0.6	[1, 2, 3, 2, 2, 2, 1, 1, 2, 2]
+accomplished	1.9	0.53852	[2, 2, 2, 1, 2, 2, 3, 1, 2, 2]
+accomplishes	1.7	0.9	[2, 2, 1, 0, 2, 3, 3, 1, 1, 2]
+accusation	-1.0	1.09545	[-1, -1, -2, -2, -2, -1, -1, -1, 2, -1]
+accusations	-1.3	1.26886	[-2, -2, -1, -3, -2, -1, -1, 2, -2, -1]
+accuse	-0.8	1.53623	[-3, -1, -1, -2, 1, -2, 1, -2, 2, -1]
+accused	-1.2	1.46969	[-2, -1, -2, 2, -2, -3, -2, -2, -1, 1]
+accuses	-1.4	1.0198	[-2, -1, -2, 1, -2, -3, -1, -2, -1, -1]
+accusing	-0.7	1.34536	[-2, -1, -1, 1, -3, -1, -1, 2, -1, 0]
+ache	-1.6	1.2	[-1, -2, -2, -2, -1, -4, -1, 1, -2, -2]
+ached	-1.6	0.8	[-2, -2, -1, -2, -1, -2, -3, 0, -1, -2]
+aches	-1.0	0.7746	[-1, -2, -1, -1, -1, 1, -2, -1, -1, -1]
+achievable	1.3	0.45826	[2, 1, 1, 1, 1, 1, 1, 2, 2, 1]
+aching	-2.2	0.74833	[-2, -3, -2, -1, -3, -3, -2, -3, -1, -2]
+acquit	0.8	1.72047	[-3, 3, -1, 3, 2, 1, 1, 1, 0, 1]
+acquits	0.1	1.37477	[1, -3, -1, 0, 2, 0, -1, 1, 1, 1]
+acquitted	1.0	0.89443	[2, 2, 1, 1, 2, 0, 1, 1, -1, 1]
+acquitting	1.3	0.78102	[3, 2, 0, 1, 1, 1, 2, 1, 1, 1]
+acrimonious	-1.7	1.73494	[-1, -3, -2, -3, 3, -3, -1, -2, -2, -3]
+active	1.7	1.26886	[1, 2, 1, 1, 1, 4, 2, 4, 0, 1]
+actively	1.3	0.78102	[0, 1, 0, 2, 2, 1, 1, 2, 2, 2]
+activeness	0.6	0.8	[0, 2, 0, 0, 1, 0, 1, 0, 2, 0]
+activenesses	0.8	0.74833	[2, 0, 1, 0, 0, 0, 1, 2, 1, 1]
+actives	1.1	0.7	[2, 1, 0, 1, 1, 0, 1, 1, 2, 2]
+adequate	0.9	0.7	[0, 0, 1, 1, 0, 2, 1, 1, 2, 1]
+admirability	2.4	0.4899	[2, 3, 3, 3, 3, 2, 2, 2, 2, 2]
+admirable	2.6	0.66332	[2, 3, 3, 3, 4, 3, 2, 2, 2, 2]
+admirableness	2.2	0.87178	[2, 2, 3, 3, 3, 1, 3, 1, 3, 1]
+admirably	2.5	0.67082	[2, 3, 3, 3, 4, 2, 2, 2, 2, 2]
+admiral	1.3	1.18743	[0, 0, 1, 3, 3, 2, 2, 0, 2, 0]
+admirals	1.5	0.80623	[2, 2, 0, 2, 2, 0, 1, 2, 2, 2]
+admiralties	1.6	0.66332	[2, 2, 2, 1, 0, 2, 2, 2, 1, 2]
+admiralty	1.2	1.53623	[0, 4, 0, 0, 0, 2, 2, 3, 2, -1]
+admiration	2.5	0.80623	[3, 1, 1, 3, 3, 2, 3, 3, 3, 3]
+admirations	1.6	0.66332	[2, 2, 1, 1, 2, 2, 2, 2, 2, 0]
+admire	2.1	0.83066	[3, 3, 1, 3, 3, 2, 1, 2, 1, 2]
+admired	2.3	0.78102	[4, 2, 2, 2, 2, 2, 3, 3, 1, 2]
+admirer	1.8	0.74833	[2, 1, 1, 2, 3, 2, 3, 1, 1, 2]
+admirers	1.7	1.00499	[2, 3, 2, 2, 2, 1, -1, 2, 2, 2]
+admires	1.5	0.67082	[3, 1, 1, 2, 1, 2, 2, 1, 1, 1]
+admiring	1.6	0.8	[1, 2, 1, 1, 3, 3, 2, 1, 1, 1]
+admiringly	2.3	0.64031	[1, 3, 3, 2, 2, 2, 2, 3, 3, 2]
+admit	0.8	1.07703	[0, 0, 0, 0, 0, 1, 3, 2, 2, 0]
+admits	1.2	0.87178	[1, 2, 2, 2, 0, 0, 1, 2, 0, 2]
+admitted	0.4	0.66332	[0, 1, 0, 1, 0, 0, 2, 0, 0, 0]
+admonished	-1.9	0.9434	[-2, -2, -2, -1, -2, -3, -1, -1, -1, -4]
+adopt	0.7	0.64031	[0, 0, 1, 1, 1, 0, 1, 0, 1, 2]
+adopts	0.7	0.64031	[0, 0, 1, 2, 1, 0, 1, 1, 0, 1]
+adorability	2.2	0.74833	[2, 2, 2, 2, 1, 2, 3, 2, 4, 2]
+adorable	2.2	0.6	[3, 2, 2, 3, 2, 2, 1, 3, 2, 2]
+adorableness	2.5	0.67082	[2, 3, 3, 2, 3, 2, 1, 3, 3, 3]
+adorably	2.1	0.7	[3, 1, 2, 3, 2, 2, 1, 3, 2, 2]
+adoration	2.9	0.7	[3, 3, 3, 2, 3, 3, 4, 2, 4, 2]
+adorations	2.2	0.87178	[2, 2, 3, 1, 3, 1, 3, 3, 1, 3]
+adore	2.6	0.91652	[3, 3, 1, 2, 3, 3, 3, 4, 1, 3]
+adored	1.8	0.87178	[2, 3, 3, 2, 2, 1, 1, 0, 2, 2]
+adorer	1.7	1.1	[2, 4, 3, 1, 2, 1, 1, 0, 2, 1]
+adorers	2.1	0.7	[3, 2, 1, 2, 2, 2, 3, 2, 3, 1]
+adores	1.6	0.66332	[2, 1, 3, 2, 2, 1, 1, 1, 2, 1]
+adoring	2.6	0.66332	[2, 3, 3, 3, 1, 3, 3, 2, 3, 3]
+adoringly	2.4	0.8	[2, 3, 2, 3, 3, 3, 3, 1, 1, 3]
+adorn	0.9	0.53852	[1, 1, 1, 0, 2, 1, 1, 0, 1, 1]
+adorned	0.8	1.249	[1, 1, 0, 2, -1, 3, -1, 2, 1, 0]
+adorner	1.3	0.78102	[1, 1, 1, 2, 1, 3, 1, 2, 1, 0]
+adorners	0.9	0.9434	[2, 2, 0, 1, -1, 2, 1, 1, 0, 1]
+adorning	1.0	0.7746	[0, 0, 1, 1, 1, 2, 2, 1, 0, 2]
+adornment	1.3	0.78102	[1, 3, 1, 0, 2, 2, 1, 1, 1, 1]
+adornments	0.8	1.16619	[2, -1, 0, 0, 2, 1, 2, -1, 1, 2]
+adorns	0.5	1.56525	[3, -1, 1, 0, 2, -1, 3, -1, 0, -1]
+advanced	1.0	0.63246	[1, 0, 1, 1, 1, 0, 1, 2, 1, 2]
+advantage	1.0	0.63246	[1, 2, 1, 1, 2, 0, 1, 0, 1, 1]
+advantaged	1.4	0.91652	[1, 0, 3, 0, 1, 1, 2, 2, 2, 2]
+advantageous	1.5	0.67082	[2, 0, 2, 2, 2, 1, 1, 1, 2, 2]
+advantageously	1.9	0.53852	[2, 2, 2, 3, 2, 2, 2, 1, 1, 2]
+advantageousness	1.6	1.28062	[-2, 2, 3, 1, 2, 2, 2, 2, 2, 2]
+advantages	1.5	0.80623	[1, 0, 3, 1, 1, 1, 2, 2, 2, 2]
+advantaging	1.6	0.66332	[3, 1, 1, 2, 1, 1, 2, 2, 2, 1]
+adventure	1.3	0.45826	[1, 2, 1, 1, 2, 1, 1, 1, 1, 2]
+adventured	1.3	0.45826	[1, 2, 1, 2, 1, 2, 1, 1, 1, 1]
+adventurer	1.2	0.6	[1, 2, 0, 2, 1, 2, 1, 1, 1, 1]
+adventurers	0.9	0.9434	[0, 1, 0, 1, 0, 1, 0, 1, 3, 2]
+adventures	1.4	1.2	[2, 2, 1, 2, -2, 2, 2, 1, 2, 2]
+adventuresome	1.7	1.1	[0, 3, 0, 1, 2, 2, 3, 1, 2, 3]
+adventuresomeness	1.3	1.00499	[1, 0, 0, 2, 3, 2, 2, 0, 1, 2]
+adventuress	0.8	1.72047	[3, -1, 2, 2, 0, 0, 1, 2, -3, 2]
+adventuresses	1.4	1.11355	[1, 0, 0, 3, 2, 2, 3, 0, 1, 2]
+adventuring	2.3	0.78102	[2, 3, 2, 3, 1, 3, 3, 1, 2, 3]
+adventurism	1.5	0.67082	[1, 0, 2, 2, 2, 2, 1, 1, 2, 2]
+adventurist	1.4	0.4899	[1, 1, 2, 1, 2, 2, 2, 1, 1, 1]
+adventuristic	1.7	0.64031	[2, 1, 1, 2, 2, 1, 3, 2, 2, 1]
+adventurists	1.2	0.9798	[3, 1, 0, 0, 1, 2, 1, 0, 2, 2]
+adventurous	1.4	1.11355	[0, 1, 2, 1, 2, 0, 3, 2, 3, 0]
+adventurously	1.3	0.9	[0, 1, 2, 2, 1, 2, 1, 1, 0, 3]
+adventurousness	1.8	0.87178	[0, 1, 3, 2, 1, 3, 2, 2, 2, 2]
+adversarial	-1.5	0.92195	[-2, 0, -1, -3, -2, -2, 0, -1, -2, -2]
+adversaries	-1.0	0.63246	[-1, -1, -1, -1, 0, -2, -2, -1, -1, 0]
+adversary	-0.8	1.72047	[-3, -1, -2, -2, -2, 2, 1, -1, 2, -2]
+adversative	-1.2	0.74833	[-1, -1, -2, -1, -1, -1, -3, -1, 0, -1]
+adversatively	-0.1	1.37477	[0, -2, -1, 0, -1, -1, 1, 1, 3, -1]
+adversatives	-1.0	0.7746	[-1, -1, -2, -1, -2, 1, -1, -1, -1, -1]
+adverse	-1.5	0.80623	[-2, -2, -2, -1, -1, 0, -1, -3, -1, -2]
+adversely	-0.8	1.6	[-2, -2, 0, -2, -2, 2, -2, 2, -2, 0]
+adverseness	-0.6	1.35647	[-1, -2, -1, 2, -1, -2, -1, 2, -1, -1]
+adversities	-1.5	0.67082	[-2, -2, -1, -1, -2, 0, -2, -1, -2, -2]
+adversity	-1.8	0.6	[-3, -2, -1, -2, -2, -2, -1, -1, -2, -2]
+affected	-0.6	1.35647	[-1, -2, 0, -2, 0, 0, 2, -2, 1, -2]
+affection	2.4	0.8	[3, 2, 2, 3, 4, 1, 3, 2, 2, 2]
+affectional	1.9	1.04403	[3, 3, 2, 0, 2, 2, 2, 3, 2, 0]
+affectionally	1.5	0.92195	[1, 1, 3, 1, 1, 0, 2, 2, 3, 1]
+affectionate	1.9	1.13578	[1, 0, 3, 1, 3, 2, 2, 1, 2, 4]
+affectionately	2.2	0.87178	[4, 1, 1, 2, 2, 2, 3, 3, 2, 2]
+affectioned	1.8	0.4	[2, 2, 1, 2, 2, 1, 2, 2, 2, 2]
+affectionless	-2.0	0.44721	[-2, -1, -2, -2, -2, -2, -2, -2, -2, -3]
+affections	1.5	1.11803	[-1, 3, 2, 2, 1, 1, 2, 1, 3, 1]
+afflicted	-1.5	1.0247	[-1, -2, -3, -2, 1, -1, -1, -2, -2, -2]
+affronted	0.2	2.03961	[1, -2, 2, -2, -2, 4, 0, 2, 1, -2]
+aggravate	-2.5	0.80623	[-3, -3, -2, -3, -2, -4, -3, -2, -2, -1]
+aggravated	-1.9	1.04403	[-4, -3, -3, -1, -1, -1, -1, -2, -2, -1]
+aggravates	-1.9	0.83066	[-3, -2, -2, -2, -3, -1, -2, -2, 0, -2]
+aggravating	-1.2	0.9798	[-2, -2, -1, -2, -2, -1, 0, 1, -1, -2]
+aggress	-1.3	1.55242	[-2, -2, 2, -2, -1, -3, -3, -1, 1, -2]
+aggressed	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -2, -2, -1]
+aggresses	-0.5	1.43178	[-1, -2, -1, -1, -3, 0, -1, 1, 2, 1]
+aggressing	-0.6	1.28062	[-1, -2, -1, 0, -1, -2, 2, -2, 1, 0]
+aggression	-1.2	1.77764	[-2, -2, 1, 1, -4, 2, -2, -2, -2, -2]
+aggressions	-1.3	1.48661	[-1, -2, -2, -2, -2, -3, 1, -2, 2, -2]
+aggressive	-0.6	1.28062	[-2, 1, -2, -2, 0, -2, -1, 1, 1, 0]
+aggressively	-1.3	1.55242	[-1, -2, 3, -2, -3, -2, -1, -1, -2, -2]
+aggressiveness	-1.8	0.74833	[-1, -2, -1, -2, -2, -1, -3, -1, -3, -2]
+aggressivities	-1.4	1.28062	[-1, -1, -1, -2, 2, -2, -2, -2, -3, -2]
+aggressivity	-0.6	1.35647	[-3, -1, 1, 0, 0, 0, -3, -1, 1, 0]
+aggressor	-0.8	1.32665	[-2, 0, -1, 2, -2, -2, -1, -1, -2, 1]
+aggressors	-0.9	1.13578	[-2, -2, -1, -1, -1, 1, 1, 0, -2, -2]
+aghast	-1.9	1.04403	[-2, -3, -1, 0, -2, -1, -4, -2, -2, -2]
+agitate	-1.7	0.64031	[-2, -2, -3, -1, -1, -1, -2, -1, -2, -2]
+agitated	-2.0	0.63246	[-2, -2, -2, -2, -1, -3, -3, -2, -2, -1]
+agitatedly	-1.6	0.8	[-1, -2, -1, -3, -1, -3, -1, -1, -2, -1]
+agitates	-1.4	0.8	[-2, 0, -1, -2, -1, -1, -3, -1, -2, -1]
+agitating	-1.8	0.87178	[-2, -1, -1, -1, -2, -3, -1, -3, -3, -1]
+agitation	-1.0	1.09545	[-2, -1, 1, -1, -2, -1, -2, -1, 1, -2]
+agitational	-1.2	1.66132	[-3, -3, -2, 1, -1, -2, 0, 2, -1, -3]
+agitations	-1.3	1.18743	[-1, -2, -1, -3, -2, -3, 0, -1, 1, -1]
+agitative	-1.3	1.26886	[-2, -2, -1, -2, -1, -3, 1, -2, 1, -2]
+agitato	-0.1	1.13578	[1, 2, 0, 0, 0, 0, -2, 0, -2, 0]
+agitator	-1.4	0.8	[-1, -1, -1, -2, -1, -1, -2, -3, -2, 0]
+agitators	-2.1	0.9434	[-2, -3, -3, -2, -2, -1, -3, -2, 0, -3]
+agog	1.9	0.7	[2, 1, 3, 3, 2, 1, 2, 2, 1, 2]
+agonise	-2.1	0.9434	[-3, -3, -2, -3, -1, -3, -1, -3, -1, -1]
+agonised	-2.3	0.64031	[-2, -3, -3, -2, -2, -2, -2, -3, -1, -3]
+agonises	-2.4	0.91652	[-1, -4, -3, -3, -2, -2, -2, -3, -1, -3]
+agonising	-1.5	1.43178	[-3, -2, -3, -3, -1, 1, 0, 0, -1, -3]
+agonize	-2.3	0.9	[-2, -3, -1, -2, -2, -2, -4, -1, -3, -3]
+agonized	-2.2	1.249	[-2, -3, -3, -3, -3, -2, -1, -3, 1, -3]
+agonizes	-2.3	1.18743	[-1, -3, -4, -3, -3, -2, -1, -3, 0, -3]
+agonizing	-2.7	0.78102	[-3, -2, -2, -2, -4, -3, -3, -2, -4, -2]
+agonizingly	-2.3	1.48661	[-3, -1, -3, -4, -4, -2, -3, 1, -1, -3]
+agony	-1.8	1.16619	[-3, -1, -2, -4, -2, -1, 0, -3, -1, -1]
+agree	1.5	1.11803	[1, 0, 3, 1, 2, 1, 4, 1, 1, 1]
+agreeability	1.9	1.04403	[1, 1, 1, 3, 3, 2, 1, 2, 4, 1]
+agreeable	1.8	0.4	[2, 1, 2, 1, 2, 2, 2, 2, 2, 2]
+agreeableness	1.8	0.9798	[2, 3, 2, 1, 1, 1, 4, 1, 2, 1]
+agreeablenesses	1.3	0.45826	[2, 1, 1, 2, 1, 2, 1, 1, 1, 1]
+agreeably	1.6	0.4899	[1, 1, 2, 1, 1, 2, 2, 2, 2, 2]
+agreed	1.1	0.53852	[1, 1, 2, 1, 1, 2, 1, 0, 1, 1]
+agreeing	1.4	0.4899	[1, 1, 1, 1, 2, 1, 1, 2, 2, 2]
+agreement	2.2	0.74833	[2, 1, 1, 3, 3, 3, 2, 2, 2, 3]
+agreements	1.1	1.13578	[0, 1, 0, 1, 1, 2, 1, 0, 4, 1]
+agrees	0.8	1.4	[1, 1, 1, 1, 3, 1, -3, 1, 1, 1]
+alarm	-1.4	0.91652	[-1, -1, -2, -2, -2, -2, -1, 1, -2, -2]
+alarmed	-1.4	0.4899	[-2, -1, -2, -2, -1, -1, -1, -2, -1, -1]
+alarming	-0.5	1.62788	[-1, 1, -1, 1, -3, 1, -2, -3, 1, 1]
+alarmingly	-2.6	0.91652	[-3, -3, -4, -3, -2, -1, -3, -3, -1, -3]
+alarmism	-0.3	1.26886	[-2, 0, -2, -1, 0, 1, 1, -1, 2, -1]
+alarmists	-1.1	1.3	[-1, -2, -3, -2, -1, -2, 1, 1, 0, -2]
+alarms	-1.1	1.04403	[-2, 0, -2, -1, 0, 0, 0, -1, -2, -3]
+alas	-1.1	1.22066	[-1, -2, -1, 0, -1, 0, 1, -3, -1, -3]
+alert	1.2	0.87178	[1, 2, 0, 1, 0, 2, 2, 0, 2, 2]
+alienation	-1.1	1.51327	[-3, -2, -3, -1, -2, -1, 2, -1, 1, -1]
+alive	1.6	0.8	[1, 1, 2, 3, 3, 2, 1, 1, 1, 1]
+allergic	-1.2	0.4	[-1, -2, -1, -2, -1, -1, -1, -1, -1, -1]
+allow	0.9	0.83066	[0, 0, 0, 1, 2, 2, 1, 1, 2, 0]
+alone	-1.0	0.63246	[-2, -1, -1, -1, -2, -1, 0, -1, -1, 0]
+alright	1.0	0.7746	[0, 1, 0, 3, 1, 1, 1, 1, 1, 1]
+amaze	2.5	1.0247	[3, 2, 3, 4, 2, 3, 1, 4, 2, 1]
+amazed	2.2	1.07703	[1, 0, 3, 2, 2, 4, 3, 3, 2, 2]
+amazedly	2.1	0.53852	[2, 2, 2, 2, 3, 2, 2, 3, 1, 2]
+amazement	2.5	0.80623	[3, 3, 2, 4, 1, 2, 2, 3, 2, 3]
+amazements	2.2	0.87178	[3, 1, 1, 3, 3, 2, 1, 2, 3, 3]
+amazes	2.2	0.9798	[1, 0, 3, 2, 2, 3, 3, 3, 2, 3]
+amazing	2.8	0.87178	[1, 4, 3, 2, 4, 2, 3, 3, 3, 3]
+amazon	0.7	0.64031	[0, 1, 1, 0, 1, 0, 1, 0, 1, 2]
+amazonite	0.2	0.6	[0, 0, 2, 0, 0, 0, 0, 0, 0, 0]
+amazons	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, -1, 0]
+amazonstone	1.0	1.61245	[0, 0, 0, 0, 4, 4, 2, 0, 0, 0]
+amazonstones	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
+ambitious	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 2, 3, 1]
+ambivalent	0.5	0.92195	[0, 0, -1, 2, 1, 1, 1, -1, 1, 1]
+amor	3.0	0.63246	[3, 3, 2, 4, 3, 2, 4, 3, 3, 3]
+amoral	-1.6	0.66332	[-1, -2, 0, -2, -2, -2, -2, -2, -1, -2]
+amoralism	-0.7	1.34536	[-2, -1, -2, 0, 0, -3, 2, 0, -1, 0]
+amoralisms	-0.7	1.00499	[-2, 0, 1, -1, -2, -1, -1, 1, -1, -1]
+amoralities	-1.2	1.6	[-3, 0, 0, -2, 1, -1, 0, -4, -3, 0]
+amorality	-1.5	0.92195	[0, -1, -1, -2, -1, -3, -1, -3, -2, -1]
+amorally	-1.0	1.61245	[-2, 0, 1, -4, -1, 1, 1, -2, -2, -2]
+amoretti	0.2	0.4	[0, 0, 0, 1, 0, 0, 0, 0, 0, 1]
+amoretto	0.6	0.8	[0, 1, 0, 1, 0, 0, 2, 0, 0, 2]
+amorettos	0.3	0.64031	[0, 1, 0, 1, 0, 0, 0, 1, 1, -1]
+amorino	1.2	0.87178	[2, 1, 1, 0, 3, 1, 1, 0, 1, 2]
+amorist	1.6	1.0198	[3, 0, 0, 2, 2, 1, 3, 1, 2, 2]
+amoristic	1.0	1.67332	[1, 0, 2, 3, -1, 3, 1, 3, 0, -2]
+amorists	0.1	0.9434	[0, 2, 0, 0, 1, 0, -2, 0, 0, 0]
+amoroso	2.3	0.78102	[3, 1, 1, 2, 3, 3, 3, 3, 2, 2]
+amorous	1.8	0.9798	[3, 1, 2, 2, 1, 1, 3, 0, 2, 3]
+amorously	2.3	0.78102	[1, 1, 3, 2, 3, 3, 2, 3, 2, 3]
+amorousness	2.0	0.89443	[2, 3, 1, 2, 0, 2, 2, 3, 3, 2]
+amorphous	-0.2	0.4	[0, 0, 0, 0, 0, 0, -1, 0, 0, -1]
+amorphously	0.1	0.7	[-1, 0, 0, 0, 0, 0, 2, 0, 0, 0]
+amorphousness	0.3	0.45826	[0, 0, 0, 0, 0, 1, 1, 1, 0, 0]
+amort	-2.1	0.83066	[-3, -1, -2, -2, -2, -2, -2, -4, -1, -2]
+amortise	0.5	1.43178	[0, 1, 1, 0, -3, 2, 0, 0, 2, 2]
+amortised	-0.2	1.16619	[-1, -3, 0, 0, 0, 2, 0, 0, 0, 0]
+amortises	0.1	0.83066	[-1, -1, 0, 0, 0, 2, 1, 0, 0, 0]
+amortizable	0.5	1.0247	[2, 0, 1, 0, 1, 1, -2, 1, 0, 1]
+amortization	0.6	1.0198	[0, 0, 0, 0, 1, 0, 0, 0, 3, 2]
+amortizations	0.2	1.07703	[-1, 1, 0, 0, 1, 0, 2, 1, -2, 0]
+amortize	-0.1	1.04403	[0, 0, 0, 0, 2, -2, -1, 1, -1, 0]
+amortized	0.8	0.74833	[0, 2, 0, 0, 1, 1, 1, 0, 1, 2]
+amortizes	0.6	0.8	[0, 2, 0, 0, 1, 1, 0, 0, 0, 2]
+amortizing	0.8	1.249	[0, 3, 0, 0, 0, 0, 0, 0, 3, 2]
+amusable	0.7	1.18743	[2, 1, 1, 1, 1, 1, 2, -2, -1, 1]
+amuse	1.7	0.78102	[1, 2, 1, 1, 2, 1, 1, 3, 3, 2]
+amused	1.8	0.6	[1, 2, 2, 2, 2, 2, 1, 2, 3, 1]
+amusedly	2.2	0.74833	[3, 3, 2, 2, 3, 2, 2, 3, 1, 1]
+amusement	1.5	1.11803	[3, 2, 3, 1, 2, 2, -1, 1, 1, 1]
+amusements	1.5	1.0247	[2, 1, 2, 1, 2, 2, 3, -1, 2, 1]
+amuser	1.1	1.7	[2, 1, -3, 2, 2, 3, -1, 1, 2, 2]
+amusers	1.3	0.45826	[1, 1, 2, 1, 2, 1, 2, 1, 1, 1]
+amuses	1.7	0.64031	[1, 2, 1, 2, 2, 2, 1, 2, 3, 1]
+amusia	0.3	1.48661	[0, -1, 1, -1, 2, 2, -1, -1, -1, 3]
+amusias	-0.4	0.66332	[-1, 0, 0, 1, 0, 0, -1, -1, -1, -1]
+amusing	1.6	0.91652	[2, 2, 2, -1, 2, 2, 1, 2, 2, 2]
+amusingly	0.8	1.249	[1, 2, 1, 1, 1, 2, 2, -2, -1, 1]
+amusingness	1.8	0.6	[1, 2, 3, 2, 1, 2, 2, 1, 2, 2]
+amusive	1.7	1.1	[3, 1, 3, 1, 2, 2, 2, 2, -1, 2]
+anger	-2.7	1.18743	[-1, -2, -3, -2, -4, -4, -2, -1, -4, -4]
+angered	-2.3	0.78102	[-2, -3, -2, -4, -2, -2, -3, -2, -2, -1]
+angering	-2.2	0.6	[-3, -2, -1, -3, -2, -2, -3, -2, -2, -2]
+angerly	-1.9	0.53852	[-2, -2, -1, -1, -3, -2, -2, -2, -2, -2]
+angers	-2.3	0.9	[-3, -1, -2, -3, -2, -2, -4, -1, -3, -2]
+angrier	-2.3	0.64031	[-2, -3, -2, -3, -1, -3, -2, -3, -2, -2]
+angriest	-3.1	0.83066	[-4, -3, -2, -2, -2, -4, -3, -4, -4, -3]
+angrily	-1.8	0.4	[-2, -1, -2, -2, -2, -1, -2, -2, -2, -2]
+angriness	-1.7	0.64031	[-2, 0, -2, -2, -1, -2, -2, -2, -2, -2]
+angry	-2.3	0.9	[-2, -2, -1, -3, -1, -2, -4, -2, -3, -3]
+anguish	-2.9	0.83066	[-3, -3, -2, -3, -4, -1, -3, -3, -4, -3]
+anguished	-1.8	1.4	[-3, -4, -1, -3, -2, -1, -1, 1, -1, -3]
+anguishes	-2.1	1.44568	[-4, -4, -2, -3, 1, -2, -1, -1, -2, -3]
+anguishing	-2.7	0.9	[-2, -2, -1, -3, -2, -4, -4, -3, -3, -3]
+animosity	-1.9	1.75784	[-2, -3, -3, -3, -2, 2, 1, -3, -3, -3]
+annoy	-1.9	0.53852	[-2, -2, -1, -2, -2, -1, -2, -2, -2, -3]
+annoyance	-1.3	1.55242	[-2, -3, -2, -2, -1, 1, -3, -2, 2, -1]
+annoyances	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -3, -1, -2, -2]
+annoyed	-1.6	1.11355	[-3, -1, 1, -3, -1, -1, -2, -2, -2, -2]
+annoyer	-2.2	0.87178	[-3, -2, -1, -3, -2, -4, -2, -1, -2, -2]
+annoyers	-1.5	1.0247	[-2, -1, -2, -3, -2, -1, -1, -2, 1, -2]
+annoying	-1.7	0.64031	[-1, -2, -1, -2, -1, -1, -2, -2, -3, -2]
+annoys	-1.8	0.6	[-1, -2, -3, -2, -2, -2, -1, -2, -1, -2]
+antagonism	-1.9	1.04403	[-1, -1, -3, -2, -4, -2, -2, 0, -2, -2]
+antagonisms	-1.2	1.53623	[0, -2, -2, -2, -2, -2, 3, -2, -1, -2]
+antagonist	-1.9	0.7	[-3, -1, -2, -3, -2, -2, -1, -2, -2, -1]
+antagonistic	-1.7	0.9	[-2, -2, -2, 1, -2, -2, -2, -2, -2, -2]
+antagonistically	-2.2	0.87178	[-2, -3, -4, -2, -2, -3, -2, -2, -1, -1]
+antagonists	-1.7	0.64031	[-2, -1, -1, -2, -1, -2, -2, -3, -1, -2]
+antagonize	-2.0	0.44721	[-2, -2, -2, -3, -2, -1, -2, -2, -2, -2]
+antagonized	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -2, -1, -1, -2]
+antagonizes	-0.5	1.9105	[-2, 4, -2, -2, 1, 0, -2, 1, -1, -2]
+antagonizing	-2.7	0.64031	[-4, -2, -2, -3, -2, -3, -3, -2, -3, -3]
+anti	-1.3	0.78102	[0, -2, -3, -1, -1, -2, -1, -1, -1, -1]
+anticipation	0.4	1.28062	[1, 1, -1, 0, -1, 1, 1, 2, -2, 2]
+anxieties	-0.6	1.85472	[-2, -3, -3, -2, -1, 2, -1, 1, 1, 2]
+anxiety	-0.7	2.1	[-2, -2, -2, -3, 3, -1, -3, 2, 2, -1]
+anxious	-1.0	0.44721	[-1, -2, -1, -1, 0, -1, -1, -1, -1, -1]
+anxiously	-0.9	0.83066	[-1, -1, -2, -1, -1, -1, -1, 0, 1, -2]
+anxiousness	-1.0	1.48324	[-2, -1, -1, -1, -1, -2, 3, -3, -1, -1]
+aok	2.0	0.89443	[2, 3, 2, 1, 2, 1, 1, 4, 2, 2]
+apathetic	-1.2	0.87178	[-1, -1, 0, -2, -2, -1, -1, 0, -3, -1]
+apathetically	-0.4	1.28062	[-1, -1, 0, -1, -2, 2, -1, -1, 2, -1]
+apathies	-0.6	1.0198	[-1, -1, -1, -2, 0, 1, -1, -2, 1, 0]
+apathy	-1.2	1.32665	[-2, -2, -1, 1, -1, -3, -1, 1, -1, -3]
+apeshit	-0.9	2.21133	[-4, -3, 2, -3, -2, -3, 1, 0, 2, 1]
+apocalyptic	-3.4	0.66332	[-4, -2, -3, -4, -3, -4, -4, -3, -3, -4]
+apologise	1.6	0.66332	[2, 3, 2, 2, 1, 1, 2, 1, 1, 1]
+apologised	0.4	0.91652	[-1, 0, 2, 0, 0, 1, 0, 2, 0, 0]
+apologises	0.8	1.07703	[2, 0, 2, 0, 0, 1, 0, 3, 0, 0]
+apologising	0.2	1.6	[0, -1, -1, 2, 2, 1, -2, -1, 3, -1]
+apologize	0.4	0.8	[1, -1, 0, 1, 1, 1, -1, 1, 0, 1]
+apologized	1.3	0.64031	[1, 1, 1, 2, 0, 2, 1, 2, 2, 1]
+apologizes	1.5	0.80623	[2, 1, 1, 2, 0, 2, 1, 2, 3, 1]
+apologizing	-0.3	1.34536	[1, 2, -1, 1, -1, 0, -3, 0, -1, -1]
+apology	0.2	1.249	[1, 1, 1, 1, -1, 1, -1, -1, -2, 2]
+appall	-2.4	0.66332	[-3, -2, -2, -3, -2, -3, -1, -3, -2, -3]
+appalled	-2.0	0.63246	[-3, -2, -3, -2, -2, -1, -1, -2, -2, -2]
+appalling	-1.5	1.5	[-2, -4, 1, -1, 1, -1, -2, -3, -2, -2]
+appallingly	-2.0	1.67332	[-3, -2, 0, -2, 2, -3, -4, -3, -2, -3]
+appalls	-1.9	1.37477	[0, -3, -2, -3, -3, -2, -1, -3, 1, -3]
+appease	1.1	0.9434	[1, 1, 1, -1, 2, 0, 1, 2, 2, 2]
+appeased	0.9	0.53852	[0, 1, 1, 1, 1, 1, 0, 1, 2, 1]
+appeases	0.9	0.53852	[0, 1, 1, 1, 1, 1, 0, 1, 2, 1]
+appeasing	1.0	1.09545	[1, 2, -1, 1, 2, 1, 2, 2, 1, -1]
+applaud	2.0	0.63246	[3, 2, 2, 2, 1, 2, 3, 1, 2, 2]
+applauded	1.5	0.5	[2, 2, 1, 2, 2, 2, 1, 1, 1, 1]
+applauding	2.1	0.83066	[2, 2, 4, 1, 2, 2, 2, 1, 2, 3]
+applauds	1.4	0.66332	[1, 1, 2, 1, 3, 1, 1, 1, 2, 1]
+applause	1.8	0.6	[2, 1, 1, 2, 3, 2, 1, 2, 2, 2]
+appreciate	1.7	0.78102	[2, 1, 2, 1, 1, 3, 1, 2, 3, 1]
+appreciated	2.3	0.78102	[2, 1, 3, 2, 3, 4, 2, 2, 2, 2]
+appreciates	2.3	0.9	[3, 1, 3, 1, 2, 4, 2, 3, 2, 2]
+appreciating	1.9	0.7	[1, 1, 2, 2, 2, 2, 1, 3, 2, 3]
+appreciation	2.3	0.9	[3, 3, 2, 1, 1, 3, 3, 1, 3, 3]
+appreciations	1.7	0.78102	[3, 2, 1, 2, 2, 1, 3, 1, 1, 1]
+appreciative	2.6	0.8	[3, 3, 3, 2, 1, 3, 4, 2, 2, 3]
+appreciatively	1.8	0.6	[2, 2, 2, 2, 2, 1, 3, 2, 1, 1]
+appreciativeness	1.6	0.8	[2, 1, 1, 2, 1, 1, 3, 3, 1, 1]
+appreciator	2.6	0.8	[2, 3, 2, 3, 3, 2, 1, 3, 4, 3]
+appreciators	1.5	0.80623	[1, 3, 1, 3, 1, 1, 2, 1, 1, 1]
+appreciatory	1.7	0.78102	[1, 2, 1, 3, 1, 3, 2, 2, 1, 1]
+apprehensible	1.1	1.04403	[2, 0, -1, 3, 1, 2, 1, 1, 1, 1]
+apprehensibly	-0.2	1.16619	[0, 0, -1, 2, -1, 2, -1, -1, -1, -1]
+apprehension	-2.1	0.83066	[-1, -2, -2, -1, -2, -3, -3, -3, -1, -3]
+apprehensions	-0.9	1.04403	[-1, -1, -1, -1, -2, -2, -1, -1, -1, 2]
+apprehensively	-0.3	1.18743	[-1, -1, -1, 0, 1, -2, -1, 1, -1, 2]
+apprehensiveness	-0.7	0.9	[-1, 1, -1, -1, 1, -1, -2, -1, -1, -1]
+approval	2.1	0.53852	[2, 2, 2, 2, 2, 1, 3, 3, 2, 2]
+approved	1.8	0.6	[1, 1, 1, 2, 3, 2, 2, 2, 2, 2]
+approves	1.7	0.64031	[1, 1, 1, 2, 3, 2, 2, 2, 2, 1]
+ardent	2.1	0.7	[3, 3, 2, 2, 3, 1, 2, 2, 1, 2]
+arguable	-1.0	0.63246	[-1, -1, -2, -1, -1, -2, 0, 0, -1, -1]
+arguably	-1.0	1.09545	[0, -2, 0, -2, 0, 1, -1, -2, -2, -2]
+argue	-1.4	0.66332	[-1, -2, -1, -3, -2, -1, -1, -1, -1, -1]
+argued	-1.5	0.5	[-2, -2, -1, -1, -1, -1, -2, -2, -2, -1]
+arguer	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -1]
+arguers	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -1]
+argues	-1.6	0.4899	[-2, -2, -1, -2, -1, -1, -2, -2, -2, -1]
+arguing	-2.0	0.63246	[-3, -3, -1, -1, -2, -2, -2, -2, -2, -2]
+argument	-1.5	0.80623	[-3, -1, -1, -1, -1, -2, 0, -2, -2, -2]
+argumentative	-1.5	0.67082	[-3, -2, -1, -1, -1, -1, -1, -2, -2, -1]
+argumentatively	-1.8	0.9798	[-4, -2, -1, -1, -3, -1, -2, -2, -1, -1]
+argumentive	-1.5	0.80623	[-3, -2, -2, -1, 0, -1, -1, -1, -2, -2]
+arguments	-1.7	0.64031	[-1, -1, -2, -2, -2, -3, -2, -1, -1, -2]
+arrest	-1.4	1.42829	[-1, 0, -1, 0, -2, -3, 0, -4, -3, 0]
+arrested	-2.1	1.04403	[-2, -2, -2, -1, -1, -4, -1, -4, -2, -2]
+arrests	-1.9	0.83066	[-4, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+arrogance	-2.4	0.66332	[-3, -2, -2, -3, -1, -2, -3, -3, -2, -3]
+arrogances	-1.9	0.53852	[-1, -2, -3, -2, -2, -2, -2, -1, -2, -2]
+arrogant	-2.2	0.6	[-2, -2, -2, -3, -2, -3, -3, -2, -1, -2]
+arrogantly	-1.8	1.4	[-3, -2, 2, -3, -1, -3, -2, -2, -2, -2]
+ashamed	-2.1	1.3	[-3, -3, -3, -2, -2, 1, -2, -4, -1, -2]
+ashamedly	-1.7	0.64031	[-2, -2, -2, -1, -2, -3, -1, -2, -1, -1]
+ass	-2.5	1.43178	[-4, -1, -2, -1, -3, 0, -2, -4, -4, -4]
+assassination	-2.9	0.9434	[-2, -4, -4, -3, -3, -4, -2, -3, -3, -1]
+assassinations	-2.7	1.34536	[-4, -2, -3, -2, -3, -1, -4, -4, 0, -4]
+assault	-2.8	0.9798	[-3, -4, -2, -2, -4, -3, -1, -3, -2, -4]
+assaulted	-2.4	1.28062	[-3, -3, 1, -3, -3, -3, -1, -3, -3, -3]
+assaulting	-2.3	1.1	[-4, -3, -2, -1, -2, -1, -1, -4, -3, -2]
+assaultive	-2.8	0.87178	[-3, -4, -2, -4, -3, -2, -3, -1, -3, -3]
+assaults	-2.5	0.92195	[-1, -3, -3, -3, -4, -3, -1, -2, -2, -3]
+asset	1.5	0.80623	[2, 1, 1, 3, 2, 0, 2, 2, 1, 1]
+assets	0.7	1.00499	[0, 0, 1, 3, 0, 1, 0, 0, 2, 0]
+assfucking	-2.5	1.43178	[-3, -3, 0, -3, 0, -2, -4, -4, -4, -2]
+assholes	-2.8	0.74833	[-3, -3, -3, -3, -4, -3, -2, -3, -1, -3]
+assurance	1.4	0.4899	[1, 1, 2, 2, 1, 1, 1, 2, 2, 1]
+assurances	1.4	0.4899	[2, 2, 1, 1, 1, 2, 2, 1, 1, 1]
+assure	1.4	0.4899	[1, 1, 1, 1, 2, 1, 1, 2, 2, 2]
+assured	1.5	0.67082	[1, 1, 2, 1, 1, 3, 2, 1, 2, 1]
+assuredly	1.6	0.66332	[1, 1, 1, 3, 2, 2, 2, 1, 2, 1]
+assuredness	1.4	0.8	[2, 2, 2, 1, 1, 0, 2, 0, 2, 2]
+assurer	0.9	1.13578	[2, 1, 0, 1, -2, 2, 2, 1, 1, 1]
+assurers	1.1	0.9434	[2, 0, 0, 1, 3, 2, 0, 1, 1, 1]
+assures	1.3	0.45826	[2, 1, 1, 1, 2, 1, 2, 1, 1, 1]
+assurgent	1.3	0.9	[2, 1, 0, 0, 1, 2, 1, 2, 3, 1]
+assuring	1.6	0.66332	[1, 2, 2, 3, 1, 1, 1, 1, 2, 2]
+assuror	0.5	0.67082	[0, 1, 0, 1, 2, 0, 0, 1, 0, 0]
+assurors	0.7	1.34536	[2, -1, 0, 2, 0, -2, 2, 1, 1, 2]
+astonished	1.6	0.8	[3, 1, 0, 2, 2, 1, 2, 2, 1, 2]
+astound	1.7	1.26886	[2, 2, 2, 2, 0, 3, 4, 0, 0, 2]
+astounded	1.8	0.9798	[1, 3, 0, 1, 2, 2, 3, 2, 1, 3]
+astounding	1.8	1.4	[3, 4, 2, 0, 1, 2, -1, 3, 2, 2]
+astoundingly	2.1	1.44568	[3, 0, 4, 1, 4, 3, 1, 3, 0, 2]
+astounds	2.1	1.22066	[3, 3, 1, 0, 3, 2, 3, 3, 0, 3]
+attachment	1.2	0.9798	[2, 0, 1, 2, 3, 1, 1, 2, 0, 0]
+attachments	1.1	0.7	[1, 1, 2, 0, 2, 1, 2, 0, 1, 1]
+attack	-2.1	0.83066	[-1, -3, -2, -3, -3, -1, -2, -1, -2, -3]
+attacked	-2.0	1.78885	[-2, 3, -2, -2, -3, -3, -3, -4, -2, -2]
+attacker	-2.7	0.9	[-2, -3, -2, -1, -3, -3, -4, -4, -2, -3]
+attackers	-2.7	0.64031	[-3, -3, -3, -2, -3, -3, -4, -2, -2, -2]
+attacking	-2.0	0.89443	[-3, -1, -1, -3, -3, -1, -3, -1, -2, -2]
+attacks	-1.9	0.9434	[-2, -2, 0, -2, -2, -2, -1, -4, -2, -2]
+attract	1.5	0.92195	[1, 3, 1, 1, 3, 1, 1, 2, 0, 2]
+attractancy	0.9	0.7	[1, 0, 2, 1, 0, 2, 1, 1, 0, 1]
+attractant	1.3	0.9	[0, 1, 0, 1, 1, 2, 3, 2, 1, 2]
+attractants	1.4	0.8	[1, 1, 0, 2, 2, 2, 3, 1, 1, 1]
+attracted	1.8	0.6	[1, 3, 1, 2, 2, 2, 2, 2, 2, 1]
+attracting	2.1	0.83066	[3, 1, 2, 2, 3, 1, 1, 3, 2, 3]
+attraction	2.0	0.7746	[2, 2, 1, 1, 2, 3, 3, 2, 3, 1]
+attractions	1.8	0.87178	[1, 3, 0, 2, 2, 2, 2, 3, 1, 2]
+attractive	1.9	0.53852	[2, 2, 2, 1, 3, 2, 1, 2, 2, 2]
+attractively	2.2	0.6	[3, 2, 2, 3, 2, 2, 2, 3, 1, 2]
+attractiveness	1.8	1.16619	[3, 2, 2, 1, 4, 2, 0, 0, 2, 2]
+attractivenesses	2.1	0.7	[2, 1, 2, 3, 2, 3, 3, 1, 2, 2]
+attractor	1.2	1.16619	[1, 1, 2, 2, 2, -2, 2, 1, 2, 1]
+attractors	1.2	0.87178	[1, 1, 2, 2, 0, 1, 3, 1, 0, 1]
+attracts	1.7	1.00499	[2, 1, 2, 0, 2, 4, 2, 1, 1, 2]
+audacious	0.9	2.02237	[3, -1, -2, 2, 1, 2, -3, 2, 2, 3]
+authority	0.3	0.64031	[0, 0, 0, 1, 0, 0, 2, 0, 0, 0]
+aversion	-1.9	1.04403	[-3, -3, -1, -2, 0, -3, -1, -2, -1, -3]
+aversions	-1.1	1.13578	[-2, -1, -2, -2, -2, 1, -1, -2, 1, -1]
+aversive	-1.6	0.66332	[-2, -1, -1, -1, -2, -2, -1, -2, -3, -1]
+aversively	-0.8	1.53623	[-3, -1, -2, -1, 1, -2, 2, -2, 1, -1]
+avert	-0.7	0.78102	[-1, 0, -2, -1, -1, 1, -1, 0, -1, -1]
+averted	-0.3	1.00499	[-1, 1, 0, 0, 1, 0, -2, 0, 0, -2]
+averts	-0.4	1.0198	[-2, -2, -1, -1, 0, 0, 1, 0, 1, 0]
+avid	1.2	0.87178	[-1, 2, 2, 1, 1, 1, 2, 2, 1, 1]
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+avoidance	-1.7	0.45826	[-2, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+avoidances	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -2, -1, -1]
+avoided	-1.4	0.4899	[-2, -1, -2, -1, -1, -1, -2, -1, -2, -1]
+avoider	-1.8	0.6	[-2, -1, -3, -1, -2, -2, -2, -1, -2, -2]
+avoiders	-1.4	0.66332	[-2, -2, -1, -2, -1, -1, 0, -1, -2, -2]
+avoiding	-1.4	0.91652	[-2, 1, -2, -2, -1, -2, -1, -1, -2, -2]
+avoids	-0.7	0.45826	[-1, -1, -1, -1, -1, -1, 0, 0, 0, -1]
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+awarder	0.9	1.04403	[2, 0, 1, 3, 0, 2, 1, 0, 0, 0]
+awarders	1.3	1.18743	[2, 1, 0, 2, 2, 0, 0, 4, 1, 1]
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+awesome	3.1	0.83066	[3, 4, 2, 3, 2, 2, 4, 4, 4, 3]
+awful	-2.0	2.04939	[-2, -2, -3, -3, -2, -3, 4, -3, -3, -3]
+awkward	-0.6	1.56205	[-2, -1, -1, -1, -1, -1, -1, -1, 4, -1]
+awkwardly	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -1, -2, -2, -1]
+awkwardness	-0.7	1.41774	[-1, -2, -2, -1, -2, 2, -1, -1, 2, -1]
+axe	-0.4	0.8	[-2, 0, 0, 0, 0, 0, -1, -1, -1, 1]
+axed	-1.3	0.78102	[-1, -2, 0, -3, -1, -2, -1, -1, -1, -1]
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+backing	0.1	0.83066	[1, 1, -1, 0, 0, 0, -1, 1, -1, 1]
+backs	-0.2	0.4	[0, 0, -1, 0, 0, 0, 0, -1, 0, 0]
+bad	-2.5	0.67082	[-3, -2, -4, -3, -2, -2, -3, -2, -2, -2]
+badass	1.4	1.26491	[1, 3, 2, 0, -1, 1, 3, 2, 1, 2]
+badly	-2.1	0.7	[-2, -3, -2, -1, -3, -2, -3, -2, -1, -2]
+bailout	-0.4	1.35647	[-1, 0, 0, 2, -2, -1, -2, 2, -1, -1]
+bamboozle	-1.5	1.0247	[-3, -2, -2, -1, -2, -2, 1, -1, -1, -2]
+bamboozled	-1.5	1.11803	[-1, 0, -2, -4, -2, -1, -2, -1, 0, -2]
+bamboozles	-1.5	1.0247	[-1, 0, -2, -4, -2, -1, -2, -1, -1, -1]
+ban	-2.6	1.0198	[-4, -3, -4, -3, -2, -1, -3, -2, -1, -3]
+banish	-1.9	0.9434	[-2, -2, -2, -2, -1, -3, -1, -1, -1, -4]
+bankrupt	-2.6	1.0198	[-4, -4, -2, -2, -4, -3, -2, -2, -1, -2]
+bankster	-2.1	0.53852	[-3, -1, -2, -2, -2, -2, -2, -3, -2, -2]
+banned	-2.0	1.0	[-2, -1, -1, -1, -2, -2, -4, -3, -3, -1]
+bargain	0.8	1.16619	[1, 1, 1, 1, 0, 1, 2, 3, -1, -1]
+barrier	-0.5	0.92195	[-2, 0, 0, -2, -1, -1, 1, 0, 0, 0]
+bashful	-0.1	1.13578	[-1, 2, -1, 0, -1, 2, 0, 0, -1, -1]
+bashfully	0.2	0.9798	[0, 0, 0, -1, 1, 1, 1, 1, -2, 1]
+bashfulness	-0.8	0.9798	[-2, -1, 1, 1, -1, -2, -1, -1, -1, -1]
+bastard	-2.5	0.67082	[-2, -4, -2, -3, -2, -2, -3, -3, -2, -2]
+bastardies	-1.8	0.87178	[-2, -1, -3, -2, -2, -2, -1, 0, -2, -3]
+bastardise	-2.1	0.83066	[-2, -1, -4, -2, -2, -3, -2, -2, -2, -1]
+bastardised	-2.3	0.9	[-3, -2, -3, -1, -2, -3, -4, -1, -2, -2]
+bastardises	-2.3	1.18743	[-1, -4, -2, -3, -3, 0, -2, -4, -2, -2]
+bastardising	-2.6	0.8	[-3, -2, -3, -2, -2, -1, -3, -4, -3, -3]
+bastardization	-2.4	1.28062	[-1, -3, -4, -4, -2, -2, -2, 0, -2, -4]
+bastardizations	-2.1	0.7	[-2, -1, -3, -3, -2, -2, -3, -1, -2, -2]
+bastardize	-2.4	0.66332	[-2, -2, -3, -2, -2, -3, -4, -2, -2, -2]
+bastardized	-2.0	0.7746	[-2, -1, -1, -2, -3, -2, -3, -2, -1, -3]
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+bastardizing	-2.3	0.9	[-2, -2, -1, -4, -3, -2, -1, -2, -3, -3]
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+battlefront	-1.2	0.87178	[-1, 0, -2, -1, 0, -3, -1, -2, -1, -1]
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+battleships	-0.5	0.80623	[-2, 0, 0, 0, 0, -1, -2, 0, 0, 0]
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+botheration	-1.7	0.64031	[-1, -1, -1, -2, -2, -1, -2, -2, -2, -3]
+botherations	-1.3	0.64031	[-2, -2, -2, -1, -2, 0, -1, -1, -1, -1]
+bothered	-1.3	0.45826	[-1, -1, -2, -1, -2, -1, -1, -1, -1, -2]
+bothering	-1.6	0.4899	[-2, -1, -2, -2, -1, -1, -1, -2, -2, -2]
+bothers	-0.8	0.9798	[-1, -2, -1, -1, 2, -1, -1, -1, -1, -1]
+bothersome	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -2, -2, -1, -1]
+boycott	-1.3	0.45826	[-2, -1, -1, -1, -1, -2, -1, -1, -2, -1]
+boycotted	-1.7	0.64031	[-1, -2, -2, -3, -1, -1, -2, -2, -2, -1]
+boycotting	-1.7	0.64031	[-2, -2, -2, 0, -2, -1, -2, -2, -2, -2]
+boycotts	-1.4	0.91652	[-2, -2, -2, -2, -1, -2, -1, 1, -1, -2]
+brainwashing	-1.5	1.28452	[-2, -2, -2, -3, -1, -2, 2, -1, -2, -2]
+brave	2.4	0.8	[2, 3, 4, 3, 1, 3, 2, 2, 2, 2]
+braved	1.9	0.83066	[3, 1, 3, 1, 1, 2, 3, 2, 2, 1]
+bravely	2.3	0.78102	[1, 3, 2, 2, 2, 4, 2, 2, 2, 3]
+braver	2.4	0.8	[3, 2, 2, 1, 4, 2, 3, 3, 2, 2]
+braveries	2.0	1.0	[2, 4, 2, 3, 1, 1, 2, 3, 1, 1]
+bravery	2.2	0.74833	[1, 2, 2, 2, 3, 2, 3, 3, 1, 3]
+braves	1.9	0.83066	[3, 1, 3, 1, 2, 2, 3, 2, 1, 1]
+bravest	2.3	0.64031	[1, 3, 3, 2, 3, 2, 3, 2, 2, 2]
+breathtaking	2.0	1.26491	[3, 1, 3, 2, -1, 1, 2, 3, 3, 3]
+bribe	-0.8	1.98997	[-3, 0, -1, -2, -1, -2, -4, 1, 3, 1]
+bright	1.9	0.7	[2, 2, 1, 2, 1, 2, 1, 3, 3, 2]
+brighten	1.9	0.7	[2, 1, 1, 2, 3, 2, 1, 2, 2, 3]
+brightened	2.1	0.83066	[2, 3, 1, 1, 2, 2, 3, 1, 3, 3]
+brightener	1.0	1.18322	[0, 0, 0, 1, 0, 1, 2, 0, 3, 3]
+brighteners	1.0	0.89443	[0, 1, 0, 1, 1, 3, 0, 1, 2, 1]
+brightening	2.5	0.92195	[2, 3, 2, 1, 2, 3, 4, 4, 2, 2]
+brightens	1.5	0.5	[2, 1, 1, 2, 2, 1, 2, 2, 1, 1]
+brighter	1.6	0.66332	[1, 1, 1, 2, 2, 2, 1, 2, 1, 3]
+brightest	3.0	0.63246	[3, 3, 2, 3, 4, 3, 2, 3, 4, 3]
+brightly	1.5	0.67082	[2, 3, 1, 2, 1, 1, 2, 1, 1, 1]
+brightness	1.6	0.91652	[2, 2, 1, 1, 1, 3, 3, 0, 2, 1]
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+brights	0.4	0.66332	[0, 0, 2, 0, 0, 1, 0, 0, 1, 0]
+brightwork	1.1	0.83066	[1, 0, 1, 2, 1, 0, 3, 1, 1, 1]
+brilliance	2.9	0.83066	[4, 3, 2, 4, 4, 3, 2, 3, 2, 2]
+brilliances	2.9	0.83066	[3, 4, 3, 4, 4, 2, 3, 2, 2, 2]
+brilliancies	2.3	1.18743	[1, 4, 1, 3, 3, 2, 1, 3, 4, 1]
+brilliancy	2.6	1.0198	[4, 3, 2, 4, 2, 3, 1, 3, 1, 3]
+brilliant	2.8	0.6	[2, 3, 3, 2, 3, 3, 4, 2, 3, 3]
+brilliantine	0.8	1.16619	[-1, 3, 1, 0, 1, 0, 2, 0, 2, 0]
+brilliantines	2.0	1.34164	[0, 1, 4, 2, 3, 1, 3, 0, 3, 3]
+brilliantly	3.0	0.44721	[3, 2, 3, 3, 3, 3, 3, 3, 4, 3]
+brilliants	1.9	0.83066	[3, 1, 2, 1, 2, 1, 3, 2, 1, 3]
+brisk	0.6	0.8	[0, 0, 0, 0, 1, 1, 0, 2, 0, 2]
+broke	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -1, -2, -2]
+broken	-2.1	0.53852	[-2, -2, -2, -2, -3, -2, -1, -3, -2, -2]
+brooding	0.1	1.3	[3, 0, -1, -1, -1, 1, 1, -1, 1, -1]
+brutal	-3.1	0.7	[-3, -3, -4, -2, -3, -4, -3, -4, -3, -2]
+brutalise	-2.7	1.1	[-4, -3, -3, -4, -3, -2, -2, -3, 0, -3]
+brutalised	-2.9	0.83066	[-3, -3, -2, -3, -3, -4, -4, -1, -3, -3]
+brutalises	-3.2	0.4	[-3, -3, -3, -3, -3, -4, -4, -3, -3, -3]
+brutalising	-2.8	0.74833	[-3, -3, -4, -3, -2, -3, -3, -3, -1, -3]
+brutalities	-2.6	1.0198	[-4, -2, -2, -4, -2, -4, -2, -3, -1, -2]
+brutality	-3.0	0.63246	[-2, -3, -4, -2, -3, -3, -3, -4, -3, -3]
+brutalization	-2.1	2.16564	[-3, -2, -4, -2, -4, -4, 2, -3, 2, -3]
+brutalizations	-2.3	0.64031	[-2, -2, -3, -2, -1, -3, -3, -2, -2, -3]
+brutalize	-2.9	0.7	[-3, -4, -3, -3, -2, -2, -3, -4, -2, -3]
+brutalized	-2.4	0.4899	[-3, -2, -2, -3, -2, -2, -3, -3, -2, -2]
+brutalizes	-3.2	0.6	[-4, -4, -3, -2, -3, -4, -3, -3, -3, -3]
+brutalizing	-3.4	0.66332	[-4, -3, -4, -3, -4, -4, -3, -4, -2, -3]
+brutally	-3.0	0.44721	[-3, -3, -3, -3, -3, -3, -3, -2, -3, -4]
+bullied	-3.1	0.9434	[-4, -4, -4, -2, -2, -4, -4, -3, -2, -2]
+bullshit	-2.8	0.6	[-3, -3, -3, -3, -3, -4, -2, -3, -2, -2]
+bully	-2.2	1.6	[-2, -3, -3, -4, -2, -1, 2, -3, -3, -3]
+bullying	-2.9	0.7	[-3, -2, -3, -2, -4, -2, -3, -3, -4, -3]
+bummer	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -1, -2, -2, -1]
+buoyant	0.9	0.83066	[0, 1, 1, 2, 1, 0, 0, 2, 0, 2]
+burden	-1.9	0.53852	[-2, -2, -1, -2, -3, -2, -1, -2, -2, -2]
+burdened	-1.7	0.45826	[-2, -2, -2, -2, -1, -2, -1, -2, -2, -1]
+burdener	-1.3	0.45826	[-1, -1, -2, -1, -1, -1, -2, -1, -2, -1]
+burdeners	-1.7	1.00499	[-2, -2, -2, -1, -3, -2, 0, 0, -2, -3]
+burdening	-1.4	0.66332	[-2, -1, -2, -2, -1, -1, -1, 0, -2, -2]
+burdens	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -1, -2, -2]
+burdensome	-1.8	0.9798	[-1, -1, -3, -2, -1, -2, -2, -1, -4, -1]
+bwahaha	0.4	1.0198	[0, 1, 0, 1, 0, 2, -1, -1, 2, 0]
+bwahahah	2.5	0.92195	[3, 4, 2, 2, 2, 3, 1, 2, 2, 4]
+calm	1.3	0.78102	[1, 1, 0, 1, 2, 3, 2, 1, 1, 1]
+calmative	1.1	0.9434	[3, 2, -1, 1, 1, 1, 1, 1, 1, 1]
+calmatives	0.5	0.80623	[-1, 1, 0, 1, 0, 0, 1, 2, 0, 1]
+calmed	1.6	0.4899	[2, 2, 2, 1, 1, 1, 2, 1, 2, 2]
+calmer	1.5	0.67082	[1, 2, 3, 1, 1, 1, 2, 1, 2, 1]
+calmest	1.6	0.8	[3, 2, 2, 2, 1, 1, 0, 2, 1, 2]
+calming	1.7	0.78102	[2, 1, 3, 2, 2, 1, 3, 1, 1, 1]
+calmly	1.3	0.9	[0, 0, 1, 3, 2, 2, 1, 1, 2, 1]
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+calmodulin	0.2	0.4	[0, 0, 0, 0, 0, 0, 1, 0, 0, 1]
+calms	1.3	0.64031	[2, 1, 1, 2, 0, 1, 1, 2, 2, 1]
+can't stand	-2.0	0.63246	[-2, -2, -2, -1, -1, -2, -3, -2, -2, -3]
+cancel	-1.0	0.63246	[-2, -1, -1, -1, -1, 0, -1, 0, -2, -1]
+cancelled	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -2, -1, -1]
+cancelling	-0.8	0.74833	[0, 0, -1, 0, -1, -1, 0, -2, -1, -2]
+cancels	-0.9	0.53852	[0, -1, 0, -1, -1, -1, -1, -1, -2, -1]
+cancer	-3.4	0.8	[-2, -4, -3, -4, -4, -2, -3, -4, -4, -4]
+capable	1.6	0.4899	[1, 2, 2, 2, 1, 1, 2, 2, 1, 2]
+captivated	1.6	0.4899	[2, 1, 2, 2, 2, 2, 1, 2, 1, 1]
+care	2.2	0.74833	[2, 1, 2, 1, 2, 2, 3, 3, 3, 3]
+cared	1.8	0.74833	[1, 2, 1, 3, 1, 2, 2, 2, 3, 1]
+carefree	1.7	0.64031	[1, 1, 2, 2, 2, 2, 1, 1, 2, 3]
+careful	0.6	1.11355	[3, 0, 0, 0, 1, 0, -1, 2, 1, 0]
+carefully	0.5	0.67082	[1, 0, 1, 1, 0, 1, 0, 1, 1, -1]
+carefulness	2.0	0.44721	[3, 2, 2, 1, 2, 2, 2, 2, 2, 2]
+careless	-1.5	0.5	[-2, -1, -1, -2, -2, -1, -2, -2, -1, -1]
+carelessly	-1.0	0.44721	[-1, -1, -1, -2, -1, 0, -1, -1, -1, -1]
+carelessness	-1.4	0.4899	[-2, -1, -1, -2, -1, -2, -1, -1, -2, -1]
+carelessnesses	-1.6	1.11355	[-4, -2, -2, -3, -1, 0, -1, -1, -1, -1]
+cares	2.0	0.7746	[2, 3, 1, 3, 1, 2, 2, 2, 3, 1]
+caring	2.2	0.4	[2, 3, 2, 2, 2, 2, 2, 3, 2, 2]
+casual	0.8	0.74833	[1, 1, 0, 1, 0, 2, 0, 1, 2, 0]
+casually	0.7	1.00499	[1, 0, 0, 0, 1, 0, 0, 3, 2, 0]
+casualty	-2.4	0.91652	[-4, -3, -3, -2, -1, -2, -3, -1, -2, -3]
+catastrophe	-3.4	0.4899	[-3, -3, -3, -4, -4, -3, -3, -3, -4, -4]
+catastrophic	-2.2	2.22711	[-3, -2, -4, -4, -4, -3, -2, -4, 2, 2]
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+celebrate	2.7	1.00499	[4, 4, 3, 2, 4, 2, 2, 2, 3, 1]
+celebrated	2.7	0.78102	[2, 3, 3, 2, 3, 4, 3, 3, 1, 3]
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+celebrating	2.7	0.64031	[3, 3, 4, 2, 2, 2, 3, 3, 2, 3]
+censor	-2.0	1.34164	[0, -3, -2, -3, -3, 0, -4, -1, -1, -3]
+censored	-0.6	1.68523	[-1, -1, -1, 2, -3, -2, -1, -1, -1, 3]
+censors	-1.2	1.07703	[-1, 0, -3, 0, -1, 0, -1, -2, -1, -3]
+certain	1.1	0.7	[1, 0, 2, 0, 2, 2, 1, 1, 1, 1]
+certainly	1.4	1.0198	[3, 2, 0, 1, 3, 1, 0, 1, 1, 2]
+certainties	0.9	1.44568	[0, -2, 4, 0, 1, 1, 1, 1, 2, 1]
+certainty	1.0	0.89443	[2, 1, 0, 1, 0, 0, 2, 2, 2, 0]
+chagrin	-1.9	0.53852	[-1, -2, -3, -2, -1, -2, -2, -2, -2, -2]
+chagrined	-1.4	1.2	[-1, -2, 2, -1, -2, -2, -2, -2, -2, -2]
+challenge	0.3	1.00499	[1, 0, -1, 1, 1, -1, 1, 0, 2, -1]
+challenged	-0.4	1.62481	[0, -2, 1, -1, -3, -1, 3, -1, 1, -1]
+challenger	0.5	1.43178	[0, 0, 2, -1, -2, 1, 3, 0, 2, 0]
+challengers	0.4	1.56205	[0, -2, -1, 1, 1, 2, 3, 2, -1, -1]
+challenges	0.3	1.48661	[0, -1, 2, -1, -2, 0, 3, 0, 2, 0]
+challenging	0.6	0.91652	[0, 0, 0, 1, 1, -1, 0, 2, 2, 1]
+challengingly	-0.6	1.68523	[0, -1, -2, 1, -3, 2, -2, -1, 2, -2]
+champ	2.1	0.83066	[2, 2, 2, 3, 2, 3, 2, 0, 3, 2]
+champac	-0.2	0.6	[0, 0, -2, 0, 0, 0, 0, 0, 0, 0]
+champagne	1.2	1.07703	[1, 2, 2, 3, 0, 2, 0, 0, 2, 0]
+champagnes	0.5	0.92195	[0, 0, 0, 0, 0, 1, 1, 3, 0, 0]
+champaign	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
+champaigns	0.5	0.67082	[1, 0, 0, 0, 0, 0, 0, 1, 2, 1]
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+champed	1.0	0.63246	[1, 1, 2, 1, 1, 2, 1, 0, 0, 1]
+champer	-0.1	0.53852	[0, -1, 1, 0, 0, 0, 0, -1, 0, 0]
+champers	0.5	0.67082	[1, 0, 0, 0, 0, 0, 0, 1, 1, 2]
+champerties	-0.1	0.83066	[0, -1, 1, 1, 0, 0, 0, 0, -2, 0]
+champertous	0.3	0.78102	[0, 0, 0, 1, -1, 2, 1, 0, 0, 0]
+champerty	-0.2	1.32665	[-2, -1, 0, -1, 0, 0, 0, -2, 2, 2]
+champignon	0.4	0.8	[0, 0, 0, 0, 0, 2, 0, 2, 0, 0]
+champignons	0.2	0.6	[0, 2, 0, 0, 0, 0, 0, 0, 0, 0]
+champing	0.7	1.34536	[0, 2, 0, 3, 1, 1, 2, 0, -2, 0]
+champion	2.9	0.83066	[3, 2, 3, 4, 4, 3, 2, 2, 4, 2]
+championed	1.2	1.53623	[2, 1, 3, 1, 1, -3, 2, 2, 1, 2]
+championing	1.8	0.9798	[1, 3, 2, 0, 3, 1, 2, 2, 1, 3]
+champions	2.4	1.42829	[4, 0, 0, 3, 1, 3, 4, 3, 3, 3]
+championship	1.9	1.04403	[3, 1, 1, 3, 2, 1, 3, 3, 0, 2]
+championships	2.2	0.74833	[2, 2, 1, 2, 3, 2, 4, 2, 2, 2]
+champs	1.8	0.4	[2, 2, 2, 2, 1, 2, 1, 2, 2, 2]
+champy	1.0	1.0	[3, 0, 0, 0, 0, 2, 1, 2, 1, 1]
+chance	1.0	0.7746	[1, 1, 0, 0, 0, 2, 1, 2, 1, 2]
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+chaos	-2.7	0.9	[-2, -2, -3, -1, -4, -3, -3, -2, -3, -4]
+chaotic	-2.2	1.4	[-3, -2, -1, -2, -3, 1, -2, -2, -4, -4]
+charged	-0.8	0.87178	[-1, -2, -2, -1, -1, 0, -1, 1, 0, -1]
+charges	-1.1	0.7	[-2, -2, -2, -1, -1, 0, -1, -1, 0, -1]
+charitable	1.7	0.64031	[1, 2, 1, 2, 2, 1, 2, 1, 3, 2]
+charitableness	1.9	0.9434	[3, 1, 1, 3, 1, 3, 3, 2, 1, 1]
+charitablenesses	1.6	1.74356	[2, 2, 3, 4, 1, -1, -2, 3, 2, 2]
+charitably	1.4	0.66332	[1, 2, 1, 2, 2, 1, 0, 1, 2, 2]
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+charity	1.8	0.87178	[1, 3, 2, 2, 2, 1, 2, 0, 2, 3]
+charm	1.7	0.78102	[3, 1, 1, 3, 2, 2, 1, 1, 1, 2]
+charmed	2.0	0.63246	[3, 1, 2, 2, 2, 3, 1, 2, 2, 2]
+charmer	1.9	0.53852	[3, 2, 2, 2, 2, 2, 1, 1, 2, 2]
+charmers	2.1	0.83066	[2, 1, 2, 2, 4, 3, 2, 1, 2, 2]
+charmeuse	0.3	0.78102	[0, 0, 0, 1, 0, 2, 1, 0, -1, 0]
+charmeuses	0.4	0.66332	[0, 0, 1, 0, 1, 0, 0, 0, 0, 2]
+charming	2.8	0.4	[3, 3, 3, 3, 3, 3, 2, 3, 2, 3]
+charminger	1.5	0.67082	[2, 3, 1, 2, 1, 1, 2, 1, 1, 1]
+charmingest	2.4	0.66332	[2, 3, 3, 1, 3, 2, 3, 3, 2, 2]
+charmingly	2.2	0.87178	[2, 2, 2, 1, 2, 2, 3, 3, 4, 1]
+charmless	-1.8	0.87178	[-3, -1, -3, -1, -1, -1, -2, -1, -3, -2]
+charms	1.9	0.7	[1, 2, 3, 2, 1, 2, 3, 1, 2, 2]
+chastise	-2.5	0.92195	[-4, -3, -2, -1, -4, -3, -2, -2, -2, -2]
+chastised	-2.2	1.16619	[-2, -3, -2, -4, -1, -1, -3, 0, -3, -3]
+chastises	-1.7	1.61555	[-3, -3, -3, -1, 1, -2, 1, -1, -2, -4]
+chastising	-1.7	0.78102	[-2, -3, -2, -2, -2, 0, -1, -1, -2, -2]
+cheat	-2.0	0.7746	[-2, -3, -3, -2, -2, -1, -1, -1, -2, -3]
+cheated	-2.3	0.64031	[-2, -4, -2, -2, -2, -2, -3, -2, -2, -2]
+cheater	-2.5	0.67082	[-2, -4, -2, -3, -2, -2, -3, -2, -3, -2]
+cheaters	-1.9	0.83066	[-2, -2, -2, -1, -1, -4, -2, -1, -2, -2]
+cheating	-2.6	0.91652	[-2, -3, -3, -2, -4, -4, -3, -2, -1, -2]
+cheats	-1.8	0.6	[-3, -1, -2, -1, -2, -1, -2, -2, -2, -2]
+cheer	2.3	0.64031	[2, 1, 2, 2, 2, 3, 3, 3, 2, 3]
+cheered	2.3	0.78102	[2, 3, 3, 4, 2, 1, 2, 2, 2, 2]
+cheerer	1.7	0.45826	[1, 2, 2, 2, 1, 1, 2, 2, 2, 2]
+cheerers	1.8	0.87178	[2, 2, 3, 2, 1, 2, 0, 1, 3, 2]
+cheerful	2.5	0.67082	[3, 2, 3, 2, 2, 2, 4, 2, 3, 2]
+cheerfuller	1.9	0.83066	[3, 3, 2, 3, 2, 1, 1, 2, 1, 1]
+cheerfullest	3.2	0.87178	[4, 4, 4, 4, 3, 2, 2, 3, 2, 4]
+cheerfully	2.1	0.83066	[3, 2, 2, 2, 1, 3, 1, 3, 1, 3]
+cheerfulness	2.1	0.9434	[3, 2, 1, 2, 3, 4, 1, 2, 1, 2]
+cheerier	2.6	0.4899	[2, 2, 3, 3, 2, 3, 3, 2, 3, 3]
+cheeriest	2.2	0.6	[3, 2, 3, 1, 2, 2, 3, 2, 2, 2]
+cheerily	2.5	0.67082	[3, 3, 2, 3, 2, 4, 2, 2, 2, 2]
+cheeriness	2.5	0.67082	[3, 2, 4, 2, 3, 2, 3, 2, 2, 2]
+cheering	2.3	0.64031	[3, 3, 2, 1, 3, 2, 2, 2, 3, 2]
+cheerio	1.2	0.6	[2, 1, 1, 1, 2, 1, 1, 1, 2, 0]
+cheerlead	1.7	0.78102	[1, 2, 0, 2, 2, 2, 2, 3, 1, 2]
+cheerleader	0.9	0.9434	[1, 1, 0, 2, 1, 0, 0, 1, 0, 3]
+cheerleaders	1.2	1.07703	[2, 0, 0, 1, 1, 0, 3, 3, 1, 1]
+cheerleading	1.2	1.07703	[2, 2, 0, 0, 1, 0, 3, 2, 0, 2]
+cheerleads	1.2	1.07703	[2, 3, 0, 3, 1, 0, 0, 1, 1, 1]
+cheerled	1.5	1.11803	[0, 2, 1, 4, 2, 2, 2, 1, 1, 0]
+cheerless	-1.7	1.1	[-2, -3, -2, -2, -3, -2, -1, -1, 1, -2]
+cheerlessly	-0.8	1.98997	[-2, 4, -1, -2, -1, -2, -2, -2, 2, -2]
+cheerlessness	-1.7	1.48661	[-2, -1, -2, -3, -2, -4, -1, 2, -2, -2]
+cheerly	2.4	0.66332	[2, 2, 3, 2, 2, 3, 4, 2, 2, 2]
+cheers	2.1	1.3	[2, 2, 1, 3, 2, 3, 3, 4, -1, 2]
+cheery	2.6	0.66332	[3, 2, 2, 3, 2, 3, 4, 2, 3, 2]
+cherish	1.6	1.49666	[0, 3, 3, 3, 2, 2, 2, 1, -2, 2]
+cherishable	2.0	1.41421	[-2, 2, 2, 2, 3, 2, 3, 3, 2, 3]
+cherished	2.3	0.64031	[3, 2, 2, 3, 2, 2, 1, 3, 2, 3]
+cherisher	2.2	0.4	[2, 2, 3, 2, 2, 2, 2, 3, 2, 2]
+cherishers	1.9	0.7	[3, 3, 2, 2, 1, 1, 2, 2, 2, 1]
+cherishes	2.2	0.74833	[2, 2, 3, 2, 2, 2, 2, 4, 2, 1]
+cherishing	2.0	0.7746	[3, 3, 2, 2, 1, 2, 1, 3, 2, 1]
+chic	1.1	1.3	[1, 2, 2, -2, 2, 0, 1, 1, 3, 1]
+childish	-1.2	0.74833	[-1, -1, -2, -3, -1, 0, -1, -1, -1, -1]
+chilling	-0.1	1.92094	[3, -2, 0, 1, -2, -2, -1, -2, 1, 3]
+choke	-2.5	0.92195	[-1, -2, -3, -3, -2, -4, -2, -4, -2, -2]
+choked	-2.1	1.3	[-4, -3, 0, -2, -1, -3, -3, -2, 0, -3]
+chokes	-2.0	0.89443	[-4, -3, -1, -2, -1, -2, -2, -2, -1, -2]
+choking	-2.0	1.26491	[-4, -2, -2, -3, -2, -2, -3, -1, 1, -2]
+chuckle	1.7	0.45826	[2, 1, 2, 2, 2, 2, 1, 1, 2, 2]
+chuckled	1.2	0.9798	[2, 2, 1, 1, 2, 0, 1, 2, -1, 2]
+chucklehead	-1.9	0.53852	[-2, -2, -1, -3, -2, -2, -2, -2, -1, -2]
+chuckleheaded	-1.3	1.84662	[-3, -4, -2, 0, 3, -1, -2, 0, -2, -2]
+chuckleheads	-1.1	0.9434	[-1, -2, 0, -1, -1, -3, 0, 0, -2, -1]
+chuckler	0.8	1.07703	[2, 1, -1, 0, 2, 1, 1, 2, -1, 1]
+chucklers	1.2	0.87178	[1, 1, 2, 3, 1, 0, 1, 0, 2, 1]
+chuckles	1.1	1.13578	[2, 2, -1, 1, 2, 1, 1, 2, -1, 2]
+chucklesome	1.1	0.53852	[1, 1, 2, 1, 1, 1, 0, 2, 1, 1]
+chuckling	1.4	0.4899	[1, 2, 1, 2, 1, 1, 2, 2, 1, 1]
+chucklingly	1.2	0.4	[1, 1, 1, 1, 2, 1, 1, 1, 2, 1]
+clarifies	0.9	1.13578	[-2, 1, 0, 2, 1, 2, 2, 1, 1, 1]
+clarity	1.7	0.78102	[2, 1, 2, 3, 3, 1, 1, 2, 1, 1]
+classy	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
+clean	1.7	0.78102	[3, 1, 2, 1, 2, 1, 3, 2, 1, 1]
+cleaner	0.7	0.78102	[1, 0, 1, 0, 0, 0, 2, 1, 2, 0]
+clear	1.6	1.2	[2, 1, 1, 0, 3, 1, 2, 4, 2, 0]
+cleared	0.4	0.4899	[0, 0, 1, 1, 0, 0, 0, 0, 1, 1]
+clearly	1.7	0.78102	[2, 2, 2, 2, 1, 2, 0, 2, 1, 3]
+clears	0.3	0.78102	[0, 1, 0, 0, 0, -1, 1, 2, 0, 0]
+clever	2.0	0.7746	[2, 1, 2, 2, 2, 1, 3, 1, 3, 3]
+cleverer	2.0	0.44721	[2, 2, 2, 3, 2, 2, 1, 2, 2, 2]
+cleverest	2.6	0.91652	[4, 3, 2, 2, 4, 3, 2, 1, 2, 3]
+cleverish	1.0	1.18322	[1, 1, 1, 1, 1, 1, 2, 1, -2, 3]
+cleverly	2.3	0.45826	[2, 3, 2, 2, 2, 3, 2, 2, 3, 2]
+cleverness	2.3	0.9	[2, 4, 2, 2, 1, 3, 3, 3, 1, 2]
+clevernesses	1.4	0.66332	[1, 1, 1, 2, 2, 2, 2, 0, 2, 1]
+clouded	-0.2	0.9798	[-2, 0, 2, 0, 0, -1, 0, -1, 0, 0]
+clueless	-1.5	0.5	[-1, -2, -1, -2, -2, -1, -1, -1, -2, -2]
+cock	-0.6	1.49666	[0, 0, -4, 0, 0, 1, 0, -3, 0, 0]
+cocksucker	-3.1	0.83066	[-3, -4, -2, -2, -4, -4, -4, -2, -3, -3]
+cocksuckers	-2.6	1.42829	[-4, -3, -4, -3, -3, 1, -3, -1, -3, -3]
+cocky	-0.5	1.0247	[2, 0, -1, 0, -1, -2, 0, -1, -1, -1]
+coerced	-1.5	0.67082	[-1, -2, -2, -2, -1, 0, -1, -2, -2, -2]
+collapse	-2.2	0.87178	[-3, -1, -2, -4, -3, -2, -2, -2, -1, -2]
+collapsed	-1.1	1.64012	[-1, -2, -2, -1, -2, -2, 2, 2, -3, -2]
+collapses	-1.2	0.87178	[-2, -1, -2, 0, -2, 0, 0, -2, -1, -2]
+collapsing	-1.2	0.6	[-1, -1, -2, -2, -2, -1, 0, -1, -1, -1]
+collide	-0.3	1.61555	[-3, 0, -1, 3, 0, -1, -1, 2, -1, -1]
+collides	-1.1	1.22066	[-2, -2, -1, -1, 0, -2, 2, -2, -1, -2]
+colliding	-0.5	1.36015	[-2, 2, -1, -1, 0, -1, -2, 2, -1, -1]
+collision	-1.5	0.67082	[-1, -1, -2, -1, -2, -1, -1, -3, -2, -1]
+collisions	-1.1	0.7	[0, -2, -1, 0, -1, -1, -2, -2, -1, -1]
+colluding	-1.2	1.32665	[-1, -1, -2, -2, 0, -3, 2, -2, -1, -2]
+combat	-1.4	1.0198	[0, -2, 0, -2, -2, -2, -1, -3, 0, -2]
+combats	-0.8	1.16619	[0, -2, -3, -1, 0, 0, 0, -1, 1, -2]
+comedian	1.6	1.0198	[1, 0, 2, 3, 2, 0, 3, 1, 2, 2]
+comedians	1.2	1.16619	[0, 0, 0, 2, 3, 1, 3, 2, 0, 1]
+comedic	1.7	0.64031	[2, 1, 1, 3, 1, 2, 2, 2, 1, 2]
+comedically	2.1	0.7	[3, 2, 2, 1, 2, 3, 3, 2, 1, 2]
+comedienne	0.6	0.66332	[0, 2, 1, 0, 1, 1, 0, 1, 0, 0]
+comediennes	1.6	1.11355	[2, 1, 3, 0, 0, 3, 1, 1, 2, 3]
+comedies	1.7	1.00499	[0, 2, 1, 3, 3, 3, 1, 1, 2, 1]
+comedo	0.3	0.9	[0, 0, 0, 0, -1, 0, 2, 0, 2, 0]
+comedones	-0.8	0.9798	[0, 0, 0, -1, 0, -3, 0, -1, -1, -2]
+comedown	-0.8	1.07703	[-1, -1, -1, 0, -2, -1, 2, -1, -2, -1]
+comedowns	-0.9	0.53852	[-1, -1, -1, -1, 0, -2, 0, -1, -1, -1]
+comedy	1.5	0.67082	[1, 1, 2, 1, 3, 2, 1, 1, 2, 1]
+comfort	1.5	0.67082	[1, 3, 1, 2, 1, 1, 2, 1, 1, 2]
+comfortable	2.3	0.64031	[1, 2, 3, 2, 2, 3, 3, 3, 2, 2]
+comfortableness	1.3	1.48661	[4, 2, 2, 3, 1, 1, 1, -1, -1, 1]
+comfortably	1.8	0.74833	[1, 2, 2, 1, 3, 3, 1, 2, 1, 2]
+comforted	1.8	0.6	[2, 2, 2, 0, 2, 2, 2, 2, 2, 2]
+comforter	1.9	0.53852	[2, 3, 2, 2, 2, 1, 2, 2, 2, 1]
+comforters	1.2	0.6	[2, 1, 0, 2, 1, 1, 2, 1, 1, 1]
+comforting	1.7	0.64031	[1, 2, 1, 1, 2, 2, 2, 3, 2, 1]
+comfortingly	1.7	0.45826	[1, 2, 1, 2, 2, 1, 2, 2, 2, 2]
+comfortless	-1.8	0.6	[-3, -2, -1, -2, -1, -2, -1, -2, -2, -2]
+comforts	2.1	0.7	[3, 1, 3, 1, 2, 2, 3, 2, 2, 2]
+commend	1.9	0.7	[1, 2, 2, 1, 2, 1, 2, 3, 2, 3]
+commended	1.9	0.9434	[1, 3, 2, 3, 2, 2, 0, 1, 3, 2]
+commit	1.2	0.87178	[1, 0, 2, 2, 0, 0, 2, 2, 1, 2]
+commitment	1.6	0.91652	[3, 1, 2, 0, 3, 1, 2, 1, 2, 1]
+commitments	0.5	0.92195	[1, 3, 0, 0, 0, 0, 0, 0, 0, 1]
+commits	0.1	1.13578	[0, -1, 0, 2, 1, -1, 1, 1, -2, 0]
+committed	1.1	0.7	[0, 1, 1, 2, 0, 2, 1, 1, 2, 1]
+committing	0.3	1.18743	[0, 1, 0, 3, 0, -2, 1, 0, 0, 0]
+compassion	2.0	0.7746	[3, 2, 1, 1, 2, 1, 3, 2, 2, 3]
+compassionate	2.2	0.87178	[0, 3, 3, 2, 2, 3, 3, 2, 2, 2]
+compassionated	1.6	0.66332	[3, 1, 2, 2, 1, 2, 2, 1, 1, 1]
+compassionately	1.7	1.41774	[1, 3, 3, 2, 1, 2, 3, 2, -2, 2]
+compassionateness	0.9	1.37477	[-3, 2, 2, 1, 1, 1, 2, 1, 1, 1]
+compassionates	1.6	0.4899	[2, 1, 2, 2, 1, 2, 2, 1, 1, 2]
+compassionating	1.6	0.91652	[3, 0, 2, 1, 3, 1, 2, 1, 2, 1]
+compassionless	-2.6	0.8	[-3, -2, -2, -3, -4, -3, -1, -2, -3, -3]
+compelled	0.2	1.07703	[-1, 0, 0, 0, 1, 2, -1, -1, 2, 0]
+compelling	0.9	0.94339	[1, 1, 1, 0, 1, 2, 2, -1, 2, 0]
+competent	1.3	0.78102	[1, 3, 1, 1, 2, 1, 1, 0, 2, 1]
+competitive	0.7	0.9	[0, 2, 0, 2, 0, 1, 0, 0, 0, 2]
+complacent	-0.3	1.1	[2, -1, -1, 1, -1, -1, -1, 1, -1, -1]
+complain	-1.5	0.67082	[-1, -1, -1, -2, -1, -2, -3, -2, -1, -1]
+complainant	-0.7	0.78102	[0, 0, -1, 0, 0, -2, 0, -1, -2, -1]
+complainants	-1.1	1.3	[-2, -1, 0, -2, -3, -2, -1, 1, -2, 1]
+complained	-1.7	0.64031	[-1, -3, -2, -2, -1, -1, -2, -2, -1, -2]
+complainer	-1.8	0.4	[-2, -2, -2, -2, -1, -2, -2, -2, -1, -2]
+complainers	-1.3	1.00499	[-2, -1, -1, -2, -3, 1, -1, -1, -2, -1]
+complaining	-0.8	1.249	[-2, -1, -1, -1, -2, -1, -1, 2, 1, -2]
+complainingly	-1.7	0.64031	[-1, -2, -1, -2, -1, -2, -1, -2, -3, -2]
+complains	-1.6	0.66332	[-1, -2, -1, -2, -2, -3, -1, -1, -1, -2]
+complaint	-1.2	1.249	[-1, -1, -2, -2, -1, -3, -1, -1, 2, -2]
+complaints	-1.7	0.45826	[-2, -2, -2, -1, -2, -2, -2, -1, -1, -2]
+compliment	2.1	0.7	[2, 2, 3, 1, 2, 3, 3, 1, 2, 2]
+complimentarily	1.7	0.45826	[2, 2, 2, 2, 1, 1, 2, 1, 2, 2]
+complimentary	1.9	0.7	[1, 2, 2, 1, 2, 1, 2, 3, 3, 2]
+complimented	1.8	1.4	[3, 2, 2, 2, 3, 2, -2, 3, 1, 2]
+complimenting	2.3	0.64031	[2, 2, 1, 3, 3, 2, 2, 3, 3, 2]
+compliments	1.7	0.45826	[2, 1, 2, 2, 1, 2, 2, 1, 2, 2]
+comprehensive	1.0	0.63246	[1, 1, 1, 0, 2, 2, 1, 0, 1, 1]
+conciliate	1.0	1.18322	[2, 1, 1, 0, 2, 2, -2, 2, 1, 1]
+conciliated	1.1	0.9434	[1, 3, 0, 0, 2, 0, 2, 1, 1, 1]
+conciliates	1.1	0.9434	[1, 3, 0, 0, 2, 0, 2, 1, 1, 1]
+conciliating	1.3	0.78102	[2, 2, 1, 1, 2, 0, 2, 1, 2, 0]
+condemn	-1.6	1.0198	[-2, -2, -1, -2, -2, 1, -2, -3, -1, -2]
+condemnation	-2.8	0.9798	[-3, -4, -2, -4, -2, -4, -2, -1, -3, -3]
+condemned	-1.9	1.81384	[2, -2, -2, -3, -2, -3, -3, -4, 1, -3]
+condemns	-2.3	0.64031	[-2, -2, -3, -3, -3, -2, -2, -3, -1, -2]
+confidence	2.3	0.64031	[3, 3, 3, 3, 1, 2, 2, 2, 2, 2]
+confident	2.2	0.87178	[1, 3, 3, 2, 3, 1, 3, 2, 1, 3]
+confidently	2.1	0.53852	[2, 2, 3, 1, 2, 2, 2, 2, 3, 2]
+conflict	-1.3	0.45826	[-2, -2, -1, -2, -1, -1, -1, -1, -1, -1]
+conflicting	-1.7	0.64031	[-1, -2, -3, -1, -2, -1, -2, -1, -2, -2]
+conflictive	-1.8	0.6	[-2, -2, -2, -2, -1, -1, -3, -2, -1, -2]
+conflicts	-1.6	0.8	[-1, -1, -1, -2, -1, -1, -3, -2, -1, -3]
+confront	-0.7	0.78102	[0, -1, -1, 0, 1, -1, -1, -2, -1, -1]
+confrontation	-1.3	1.55242	[-3, -2, -3, -2, -1, -2, 1, 2, -1, -2]
+confrontational	-1.6	0.66332	[-1, -2, -1, -2, -1, -2, -1, -2, -3, -1]
+confrontationist	-1.0	1.34164	[-1, -2, -2, 2, 1, -1, -2, -1, -2, -2]
+confrontationists	-1.2	1.46969	[-2, -3, -1, -2, 2, 1, -1, -2, -2, -2]
+confrontations	-1.5	1.0247	[-1, -3, -2, -1, -3, 0, -2, -2, 0, -1]
+confronted	-0.8	0.74833	[-1, -2, -1, -1, -1, -1, -1, -1, 1, 0]
+confronter	-0.3	1.1	[0, -2, 1, -2, 0, -1, -1, 0, 1, 1]
+confronters	-1.3	1.26886	[-3, -2, -2, -2, -1, -2, 1, 1, -1, -2]
+confronting	-0.6	1.11355	[-2, -1, -1, 0, -2, 2, -1, 0, 0, -1]
+confronts	-0.9	0.53852	[-1, -1, -1, -1, 0, -1, 0, -1, -2, -1]
+confuse	-0.9	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, 0, -1]
+confused	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -2]
+confusedly	-0.6	1.42829	[-3, -1, -1, 1, -1, -1, -2, 2, 1, -1]
+confusedness	-1.5	0.67082	[-3, -1, -1, -2, -1, -2, -2, -1, -1, -1]
+confuses	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -1, -2, -2]
+confusing	-0.9	0.7	[-1, -1, -1, -2, -1, -1, 1, -1, -1, -1]
+confusingly	-1.4	0.66332	[-1, -1, -1, -1, -3, -1, -2, -1, -1, -2]
+confusion	-1.2	0.6	[-1, -1, -1, -1, -1, -2, 0, -1, -2, -2]
+confusional	-1.2	0.6	[-2, -2, 0, -1, -2, -1, -1, -1, -1, -1]
+confusions	-0.9	1.04403	[-1, -2, -1, -1, -1, 2, -2, -1, -1, -1]
+congrats	2.4	0.91652	[1, 3, 3, 3, 2, 2, 4, 1, 2, 3]
+congratulate	2.2	1.249	[3, 3, 2, 3, -1, 2, 1, 3, 3, 3]
+congratulation	2.9	0.9434	[3, 3, 3, 2, 4, 2, 4, 3, 4, 1]
+congratulations	2.9	0.53852	[2, 3, 3, 3, 3, 3, 3, 3, 4, 2]
+consent	0.9	0.7	[0, 0, 1, 1, 1, 2, 1, 2, 0, 1]
+consents	1.0	0.63246	[0, 2, 1, 0, 1, 1, 1, 2, 1, 1]
+considerate	1.9	1.22066	[2, -1, 3, 2, 2, 2, 4, 1, 2, 2]
+consolable	1.1	0.53852	[1, 1, 2, 1, 0, 1, 1, 1, 2, 1]
+conspiracy	-2.4	0.66332	[-2, -2, -3, -3, -2, -2, -4, -2, -2, -2]
+constrained	-0.4	1.0198	[-1, 0, -1, -1, -1, -1, 2, -1, 1, -1]
+contagion	-2.0	1.18322	[-1, 0, -2, -1, -2, -4, -2, -4, -2, -2]
+contagions	-1.5	0.92195	[-2, -2, -2, -2, 1, -2, -1, -1, -2, -2]
+contagious	-1.4	0.91652	[-2, -2, -2, 0, -1, -1, -2, 0, -1, -3]
+contempt	-2.8	0.6	[-3, -3, -4, -2, -3, -2, -3, -3, -2, -3]
+contemptibilities	-2.0	1.09545	[-2, 1, -2, -2, -3, -3, -3, -2, -2, -2]
+contemptibility	-0.9	1.51327	[-2, -1, -3, -1, 0, -3, -1, 1, 2, -1]
+contemptible	-1.6	1.68523	[-2, -2, -3, -3, -2, -3, -1, -3, 1, 2]
+contemptibleness	-1.9	0.7	[-2, -2, -1, -2, -2, -1, -1, -2, -3, -3]
+contemptibly	-1.4	1.49666	[-3, 0, -2, -3, -2, -2, -1, -3, 1, 1]
+contempts	-1.0	1.48324	[-2, -2, -1, 0, 1, -1, -2, -3, 2, -2]
+contemptuous	-2.2	1.83303	[-2, -3, -4, -2, -3, -3, 3, -2, -3, -3]
+contemptuously	-2.4	0.8	[-1, -3, -2, -3, -3, -2, -1, -3, -3, -3]
+contemptuousness	-1.1	1.57797	[-3, -1, -2, 3, -2, 0, -1, -1, -2, -2]
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+contender	0.5	1.0247	[1, 3, -1, 0, 0, 1, 0, 1, 0, 0]
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+dangering	-2.5	0.80623	[-1, -2, -2, -3, -4, -3, -3, -2, -2, -3]
+dangerous	-2.1	0.3	[-2, -3, -2, -2, -2, -2, -2, -2, -2, -2]
+dangerously	-2.0	0.44721	[-2, -2, -2, -1, -2, -3, -2, -2, -2, -2]
+dangerousness	-2.0	0.44721	[-2, -3, -2, -1, -2, -2, -2, -2, -2, -2]
+dangers	-2.2	0.87178	[-1, -1, -2, -4, -2, -3, -3, -2, -2, -2]
+daredevil	0.5	0.92195	[0, 1, -1, 2, 0, 0, 1, 0, 0, 2]
+daring	1.5	1.5	[3, 0, 1, 1, 2, -2, 3, 2, 2, 3]
+daringly	2.1	0.7	[3, 1, 2, 1, 3, 2, 2, 3, 2, 2]
+daringness	1.4	0.8	[0, 2, 1, 3, 1, 2, 2, 1, 1, 1]
+darings	0.4	0.91652	[0, 1, 1, 1, 0, 1, 0, 1, -2, 1]
+darkest	-2.2	0.6	[-3, -3, -2, -2, -3, -2, -1, -2, -2, -2]
+darkness	-1.0	0.44721	[-2, -1, -1, -1, -1, 0, -1, -1, -1, -1]
+darling	2.8	0.6	[3, 3, 2, 2, 3, 3, 4, 2, 3, 3]
+darlingly	1.6	0.66332	[1, 1, 2, 3, 1, 1, 2, 2, 2, 1]
+darlingness	2.3	0.45826	[3, 3, 2, 2, 2, 2, 2, 2, 3, 2]
+darlings	2.2	0.4	[3, 2, 2, 2, 2, 2, 2, 2, 3, 2]
+dauntless	2.3	0.78102	[3, 3, 2, 1, 3, 3, 2, 1, 2, 3]
+daze	-0.7	0.78102	[-1, 0, -1, -1, 1, -1, -1, 0, -1, -2]
+dazed	-0.7	0.64031	[0, -1, -1, 0, -1, -1, 0, -1, 0, -2]
+dazedly	-0.4	1.0198	[-1, -1, -1, -1, -1, 2, -1, 1, 0, -1]
+dazedness	-0.5	1.11803	[-1, 2, 0, -1, -1, -1, 1, -2, -1, -1]
+dazes	-0.3	0.78102	[0, -1, 0, 0, 0, -1, 0, 1, 0, -2]
+dead	-3.3	1.00499	[-4, -4, -1, -4, -4, -3, -4, -2, -3, -4]
+deadlock	-1.4	0.8	[-2, -2, -1, -3, -1, 0, -2, -1, -1, -1]
+deafening	-1.2	1.6	[-4, -2, 0, -3, 1, -2, 1, -2, -1, 0]
+dear	1.6	1.35647	[3, 3, 2, 2, 2, 2, 1, -2, 1, 2]
+dearer	1.9	0.7	[2, 2, 1, 2, 1, 1, 2, 3, 2, 3]
+dearest	2.6	0.8	[1, 2, 3, 3, 2, 2, 3, 3, 4, 3]
+dearie	2.2	0.6	[2, 2, 2, 3, 2, 1, 3, 2, 3, 2]
+dearies	1.0	1.0	[0, 1, 2, -1, 1, 1, 1, 1, 1, 3]
+dearly	1.8	1.07703	[3, 4, 2, 1, 1, 0, 1, 2, 2, 2]
+dearness	2.0	0.7746	[1, 1, 2, 3, 2, 2, 2, 3, 1, 3]
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+dearth	-2.3	1.00499	[-2, -2, -1, -4, -2, -1, -2, -4, -3, -2]
+dearths	-0.9	0.7	[0, -1, 0, -1, -2, -1, -2, 0, -1, -1]
+deary	1.9	0.83066	[3, 2, 2, 1, 2, 2, 3, 2, 0, 2]
+death	-2.9	1.04403	[-3, -4, -4, -3, -3, -1, -1, -4, -3, -3]
+debonair	0.8	1.72047	[1, -1, -1, -3, 2, 2, 2, 2, 2, 2]
+debt	-1.5	1.0247	[-2, -1, -2, -3, 1, -2, -2, -1, -1, -2]
+decay	-1.7	0.45826	[-2, -2, -2, -1, -2, -1, -1, -2, -2, -2]
+decayed	-1.6	0.91652	[-2, -2, -2, -2, -2, 1, -1, -2, -2, -2]
+decayer	-1.6	0.4899	[-2, -2, -2, -1, -2, -1, -1, -1, -2, -2]
+decayers	-1.6	0.4899	[-2, -1, -1, -2, -1, -2, -2, -2, -1, -2]
+decaying	-1.7	0.64031	[-1, -1, -2, -2, -1, -2, -3, -2, -2, -1]
+decays	-1.7	0.45826	[-2, -1, -2, -2, -1, -2, -1, -2, -2, -2]
+deceit	-2.0	1.34164	[-3, -2, -2, -3, -3, 0, 1, -2, -3, -3]
+deceitful	-1.9	1.22066	[-3, -2, -2, -3, -1, -3, -1, -3, -2, 1]
+deceive	-1.7	0.64031	[-1, -2, -2, -1, -2, -1, -1, -3, -2, -2]
+deceived	-1.9	1.3	[1, -3, -3, -1, -1, -2, -2, -2, -4, -2]
+deceives	-1.6	1.56205	[-1, 2, -2, -2, -3, -2, 0, -2, -4, -2]
+deceiving	-1.4	1.68523	[-3, -2, -2, -2, -1, -1, 1, -4, 2, -2]
+deception	-1.9	1.04403	[-1, -2, -2, -4, -2, 0, -2, -1, -3, -2]
+decisive	0.9	0.83066	[2, 2, 0, 1, -1, 1, 1, 1, 1, 1]
+dedicated	2.0	0.44721	[2, 2, 2, 2, 2, 2, 2, 1, 3, 2]
+defeat	-2.0	1.67332	[0, -4, -3, -4, -2, -1, -2, -1, 1, -4]
+defeated	-2.1	0.83066	[-1, -2, -1, -2, -3, -2, -2, -2, -2, -4]
+defeater	-1.4	0.8	[-2, -1, -1, -3, -2, -1, -2, -1, 0, -1]
+defeaters	-0.9	0.9434	[-2, 0, -1, -2, -2, -1, 0, -1, 1, -1]
+defeating	-1.6	0.66332	[-2, -2, -1, -1, -1, -1, -2, -2, -3, -1]
+defeatism	-1.3	1.00499	[-1, -2, -2, -1, -1, -3, 1, -2, -1, -1]
+defeatist	-1.7	0.9	[0, -1, -2, -3, -1, -2, -1, -3, -2, -2]
+defeatists	-2.1	0.9434	[-3, -2, -1, -2, -2, -1, -3, -4, -1, -2]
+defeats	-1.3	1.1	[-1, 0, -1, -2, -1, -2, -3, 1, -2, -2]
+defeature	-1.9	1.22066	[1, -2, -2, -2, -2, -1, -2, -3, -4, -2]
+defeatures	-1.5	1.20416	[-3, -2, -3, 0, -1, -1, -2, 0, -3, 0]
+defect	-1.4	0.8	[-2, -1, -2, -1, 0, -2, -3, -1, -1, -1]
+defected	-1.7	0.64031	[-3, -2, -2, -2, -1, -1, -1, -2, -1, -2]
+defecting	-1.8	0.6	[-2, -1, -2, -2, -2, -1, -3, -1, -2, -2]
+defection	-1.4	0.66332	[-1, -2, -1, -2, 0, -1, -2, -2, -2, -1]
+defections	-1.5	0.67082	[-2, -2, -2, -1, 0, -1, -2, -2, -1, -2]
+defective	-1.9	0.53852	[-2, -1, -2, -3, -2, -2, -2, -2, -1, -2]
+defectively	-2.1	0.83066	[-1, -3, -2, -1, -3, -2, -1, -3, -2, -3]
+defectiveness	-1.8	0.74833	[-1, -1, -2, -2, -2, -3, -1, -1, -2, -3]
+defectives	-1.8	0.74833	[-3, -3, -1, -2, -2, -1, -2, -1, -1, -2]
+defector	-1.9	0.53852	[-2, -3, -2, -2, -1, -2, -1, -2, -2, -2]
+defectors	-1.3	1.26886	[-2, -1, -2, 0, -1, -1, -2, -4, 1, -1]
+defects	-1.7	0.9	[-1, -2, -1, 0, -2, -3, -2, -2, -1, -3]
+defence	0.4	0.91652	[0, 0, 0, 1, 0, 0, 0, 2, 2, -1]
+defenceman	0.4	1.11355	[3, 0, 0, 0, 0, -1, 2, 0, 0, 0]
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+defences	-0.2	1.16619	[0, 0, 0, 1, -2, -1, 0, -2, 0, 2]
+defender	0.4	1.0198	[0, 0, 2, 1, -1, 2, 0, 1, -1, 0]
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+defense	0.5	0.67082	[0, 1, 0, 1, 2, 1, 0, 0, 0, 0]
+defenseless	-1.4	0.8	[0, -1, -1, -2, -1, -1, -3, -1, -2, -2]
+defenselessly	-1.1	0.9434	[-2, -2, -2, -1, 0, -1, 1, -1, -1, -2]
+defenselessness	-1.3	1.18743	[-3, -1, -3, 0, -2, -1, -1, -2, 1, -1]
+defenseman	0.1	1.13578	[2, 0, 0, 0, 0, 0, -1, 0, 2, -2]
+defensemen	-0.4	0.66332	[0, 0, -2, 0, -1, -1, 0, 0, 0, 0]
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+defensible	0.8	0.87178	[0, 2, 0, 0, 1, 0, 2, 0, 2, 1]
+defensibly	0.1	1.13578	[0, -1, 0, 0, -1, 0, 3, 0, -1, 1]
+defensive	0.1	1.13578	[2, -1, 0, -1, 2, 0, -1, 1, 0, -1]
+defensively	-0.6	0.91652	[1, 1, -1, -1, -1, -1, -2, -1, 0, -1]
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+defensives	-0.3	1.00499	[-1, 0, 0, -1, 0, -1, 0, -2, 2, 0]
+defer	-1.2	0.6	[-1, -2, -1, 0, -1, -2, -2, -1, -1, -1]
+deferring	-0.7	0.64031	[0, 0, -2, -1, -1, -1, -1, 0, -1, 0]
+defiant	-0.9	1.44568	[-1, -2, -1, 2, 1, -2, 0, -1, -3, -2]
+deficit	-1.7	0.78102	[-3, -3, -2, -1, -2, -2, -1, -1, -1, -1]
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+definitely	1.7	0.64031	[2, 2, 2, 2, 2, 1, 2, 2, 0, 2]
+degradable	-1.0	1.26491	[-1, -2, 0, -2, 0, -1, -2, -2, 2, -2]
+degradation	-2.4	1.0198	[-4, -3, -3, -3, -3, -2, -2, -2, 0, -2]
+degradations	-1.5	0.67082	[-2, -1, -3, -1, -2, -2, -1, -1, -1, -1]
+degradative	-2.0	0.63246	[-2, -1, -3, -2, -2, -2, -1, -2, -3, -2]
+degrade	-1.9	0.7	[-3, -2, -1, -3, -1, -2, -2, -2, -1, -2]
+degraded	-1.8	0.87178	[-2, -3, -1, 0, -2, -1, -2, -2, -3, -2]
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+degrading	-2.8	0.87178	[-3, -3, -2, -3, -4, -2, -3, -4, -3, -1]
+degradingly	-2.7	0.64031	[-3, -2, -3, -4, -2, -3, -3, -2, -3, -2]
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+dehumanized	-1.9	0.7	[-2, -2, -2, -2, -1, -3, -2, -1, -3, -1]
+dehumanizes	-1.5	0.67082	[-1, -1, -1, -2, -1, -3, -2, -1, -2, -1]
+dehumanizing	-2.4	0.91652	[-2, -3, -4, -2, -3, -2, -3, -1, -1, -3]
+deject	-2.2	0.6	[-2, -3, -2, -3, -2, -2, -3, -2, -1, -2]
+dejected	-2.2	0.74833	[-2, -1, -2, -3, -2, -2, -2, -2, -2, -4]
+dejecting	-2.3	0.64031	[-2, -2, -3, -2, -3, -2, -1, -2, -3, -3]
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+delay	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -2, -1, -2, -1]
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+delighted	2.3	0.64031	[3, 3, 2, 3, 2, 1, 3, 2, 2, 2]
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+denying	-1.4	0.4899	[-1, -1, -1, -2, -2, -2, -1, -2, -1, -1]
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+depressingly	-2.3	0.45826	[-2, -3, -2, -2, -2, -3, -3, -2, -2, -2]
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+depressive	-1.6	1.11355	[-2, -1, -1, -2, -1, -2, -3, 1, -3, -2]
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+depressor	-1.8	1.16619	[-2, -4, -3, 0, 0, -2, -2, -2, -1, -2]
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+depressurized	-0.3	0.64031	[0, 0, 0, 0, 0, 0, -1, 0, -2, 0]
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+depressurizing	-0.7	1.34536	[2, 0, -1, -1, -2, -2, 1, -2, 0, -2]
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+deprive	-2.1	0.7	[-3, -2, -1, -3, -1, -2, -2, -3, -2, -2]
+deprived	-2.1	0.7	[-2, -2, -2, -2, -2, -4, -2, -2, -1, -2]
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+deprives	-1.7	0.64031	[-2, -2, -1, -2, -1, -3, -2, -1, -1, -2]
+depriving	-2.0	0.0	[-2, -2, -2, -2, -2, -2, -2, -2, -2, -2]
+derail	-1.2	1.07703	[-1, 1, -1, -2, -1, -2, -1, -3, -2, 0]
+derailed	-1.4	0.66332	[-1, -2, -2, 0, -1, -1, -2, -1, -2, -2]
+derails	-1.3	0.78102	[-2, -3, -1, -2, -1, -1, 0, -1, -1, -1]
+deride	-1.1	1.22066	[-3, -2, -2, -1, -1, -1, 1, -2, -1, 1]
+derided	-0.8	0.87178	[-2, -1, -2, 0, 0, -1, -1, -1, 1, -1]
+derides	-1.0	1.0	[-1, -2, -2, 0, 0, 1, -1, -2, -1, -2]
+deriding	-1.5	0.80623	[-2, -2, 0, 0, -2, -1, -2, -2, -2, -2]
+derision	-1.2	1.249	[-1, -2, -2, -2, -1, -1, 1, 1, -3, -2]
+desirable	1.3	0.45826	[2, 1, 1, 1, 1, 1, 1, 2, 2, 1]
+desire	1.7	0.78102	[1, 1, 2, 1, 3, 3, 1, 2, 2, 1]
+desired	1.1	1.04403	[1, 1, 0, 3, 1, 0, 1, 1, 3, 0]
+desirous	1.3	0.64031	[1, 2, 1, 2, 2, 1, 2, 1, 0, 1]
+despair	-1.3	1.9	[2, -1, -3, -1, -3, 1, -3, 1, -3, -3]
+despaired	-2.7	0.45826	[-2, -2, -3, -3, -3, -3, -3, -2, -3, -3]
+despairer	-1.3	1.1	[-2, -2, -1, -3, -2, 1, -1, -1, 0, -2]
+despairers	-1.3	1.00499	[-2, -1, -1, 1, -2, -1, -2, -1, -1, -3]
+despairing	-2.3	0.64031	[-2, -1, -3, -2, -3, -2, -2, -2, -3, -3]
+despairingly	-2.2	0.74833	[-2, -2, -2, -2, -4, -2, -3, -1, -2, -2]
+despairs	-2.7	1.00499	[-3, -4, -1, -3, -4, -2, -1, -3, -3, -3]
+desperate	-1.3	1.34536	[-2, -1, -2, 1, -1, -2, -3, -3, -1, 1]
+desperately	-1.6	1.11355	[-3, -3, -2, -1, -2, -1, -2, -2, -1, 1]
+desperateness	-1.5	1.36015	[-1, -2, -2, -2, -3, -3, 1, -2, 1, -2]
+desperation	-2.0	1.0	[-2, -1, -1, -2, -3, -3, -1, -4, -1, -2]
+desperations	-2.2	1.66132	[-1, -4, -2, -4, -4, -1, -1, -2, 1, -4]
+despise	-1.4	1.35647	[-2, -3, -1, -2, -1, 1, -3, 1, -2, -2]
+despised	-1.7	1.48661	[-2, -1, -3, -2, -3, 1, -3, 1, -2, -3]
+despisement	-2.4	0.91652	[-3, -3, -2, -1, -3, -1, -4, -2, -2, -3]
+despisements	-2.5	1.0247	[-2, -2, -3, -2, 0, -3, -4, -3, -3, -3]
+despiser	-1.8	1.07703	[-2, -1, -3, 1, -2, -2, -3, -2, -2, -2]
+despisers	-1.6	1.35647	[-3, -3, -1, -3, -2, -1, -1, 1, 0, -3]
+despises	-2.0	1.26491	[-3, -1, -3, 1, -2, -1, -3, -2, -3, -3]
+despising	-2.7	0.9	[-4, -3, -3, -4, -1, -2, -3, -2, -2, -3]
+despondent	-2.1	0.53852	[-2, -2, -2, -3, -2, -2, -1, -3, -2, -2]
+destroy	-2.5	0.67082	[-2, -3, -3, -1, -3, -3, -3, -2, -2, -3]
+destroyed	-2.2	0.87178	[-1, -3, -3, -2, -1, -2, -1, -3, -3, -3]
+destroyer	-2.0	0.89443	[-2, -3, -3, -3, -1, -2, -2, -2, 0, -2]
+destroyers	-2.3	0.78102	[-1, -3, -3, -3, -2, -2, -3, -3, -1, -2]
+destroying	-2.6	0.91652	[-2, -4, -4, -2, -1, -3, -2, -3, -2, -3]
+destroys	-2.6	0.4899	[-3, -3, -3, -2, -2, -2, -3, -3, -2, -3]
+destruct	-2.4	0.4899	[-3, -3, -3, -2, -2, -2, -3, -2, -2, -2]
+destructed	-1.9	1.04403	[-4, -1, -2, -2, -2, -1, -3, -2, 0, -2]
+destructibility	-1.8	1.07703	[-1, -2, -1, -1, -2, -3, -2, 0, -4, -2]
+destructible	-1.5	1.11803	[-2, -2, -2, -1, 1, -1, -3, -1, -3, -1]
+destructing	-2.5	0.67082	[-2, -3, -2, -3, -2, -2, -2, -3, -2, -4]
+destruction	-2.7	0.9	[-4, -3, -4, -3, -2, -2, -3, -1, -2, -3]
+destructionist	-2.6	0.8	[-3, -4, -2, -2, -2, -3, -3, -1, -3, -3]
+destructionists	-2.1	0.53852	[-3, -1, -2, -2, -3, -2, -2, -2, -2, -2]
+destructions	-2.3	0.78102	[-3, -2, -2, -2, -1, -3, -4, -2, -2, -2]
+destructive	-3.0	0.63246	[-3, -4, -3, -2, -3, -3, -3, -2, -4, -3]
+destructively	-2.4	0.91652	[-2, -3, -1, -4, -2, -3, -3, -3, -1, -2]
+destructiveness	-2.4	0.91652	[-3, -3, -2, -4, -1, -2, -3, -2, -1, -3]
+destructivity	-2.2	1.53623	[2, -3, -3, -4, -3, -2, -2, -2, -2, -3]
+destructs	-2.4	0.91652	[-2, -1, -2, -4, -4, -2, -3, -2, -2, -2]
+detached	-0.5	1.20416	[-1, 2, -1, -1, -2, 0, 1, -2, -1, 0]
+detain	-1.8	0.9798	[-3, -1, -2, -2, -4, -2, -1, -1, -1, -1]
+detained	-1.7	0.9	[-1, -1, -1, -1, -1, -2, -2, -2, -2, -4]
+detention	-1.5	0.67082	[-1, -2, -1, -2, -1, -1, -3, -2, -1, -1]
+determinable	0.9	0.7	[2, 1, 1, 1, 0, 1, 2, 0, 0, 1]
+determinableness	0.2	1.07703	[0, 0, 0, 1, 0, 1, -1, 2, -2, 1]
+determinably	0.9	0.83066	[2, 0, 1, 1, 0, 1, 2, 2, 0, 0]
+determinacy	1.0	1.0	[0, 0, 0, 3, 1, 1, 2, 1, 0, 2]
+determinant	0.2	0.6	[0, 1, -1, 0, 1, 1, 0, 0, 0, 0]
+determinantal	-0.3	1.41774	[0, 0, 0, -4, 0, -1, 0, 0, 2, 0]
+determinate	0.8	0.87178	[2, 1, 0, 0, 0, 2, 2, 0, 1, 0]
+determinately	1.2	0.6	[1, 2, 0, 1, 1, 1, 2, 1, 2, 1]
+determinateness	1.1	0.9434	[1, 1, 1, 0, 0, 2, 3, 1, 0, 2]
+determination	1.7	0.78102	[2, 3, 1, 1, 1, 2, 1, 1, 2, 3]
+determinations	0.8	1.16619	[0, 3, 1, 0, 1, 3, 0, 0, 0, 0]
+determinative	1.1	1.04403	[2, 0, 3, 2, 1, 1, 0, 0, 2, 0]
+determinatives	0.9	1.3	[2, 0, -2, 1, 2, 2, 2, 0, 0, 2]
+determinator	1.1	1.04403	[3, 0, 1, 0, 1, 0, 2, 2, 0, 2]
+determined	1.4	1.35647	[-2, 1, 3, 2, 2, 2, 3, 1, 1, 1]
+devastate	-3.1	0.9434	[-4, -4, -1, -4, -4, -3, -3, -3, -2, -3]
+devastated	-3.0	0.89443	[-4, -3, -3, -4, -3, -1, -3, -4, -3, -2]
+devastates	-2.8	0.9798	[-4, -3, -2, -4, -2, -1, -3, -4, -3, -2]
+devastating	-3.3	0.9	[-4, -3, -4, -4, -1, -4, -3, -3, -3, -4]
+devastatingly	-2.4	1.28062	[-3, -4, -3, 0, -3, 0, -2, -3, -3, -3]
+devastation	-1.8	2.13542	[-1, -1, -3, -3, -4, -3, -4, 2, 2, -3]
+devastations	-1.9	1.92094	[-3, -3, -2, -2, 1, -1, 2, -4, -4, -3]
+devastative	-3.2	1.16619	[-4, -3, 0, -4, -4, -3, -3, -4, -3, -4]
+devastator	-2.8	0.74833	[-3, -3, -2, -2, -3, -2, -3, -4, -2, -4]
+devastators	-2.9	1.22066	[-3, -2, -3, -4, -4, -4, 0, -3, -2, -4]
+devil	-3.4	0.8	[-4, -3, -4, -4, -4, -4, -2, -3, -2, -4]
+deviled	-1.6	1.0198	[-1, -2, 0, -4, -1, -2, -2, -2, -1, -1]
+devilfish	-0.8	1.07703	[-2, -3, -1, 0, 0, 0, 0, -2, 0, 0]
+devilfishes	-0.6	1.0198	[-3, 0, -2, 0, 0, 0, 0, -1, 0, 0]
+deviling	-2.2	0.87178	[-1, -3, -1, -2, -3, -2, -2, -4, -2, -2]
+devilish	-2.1	1.04403	[-1, -2, -4, -1, -1, -2, -2, -4, -2, -2]
+devilishly	-1.6	0.8	[-2, -2, -3, -1, -2, -2, 0, -2, -1, -1]
+devilishness	-2.3	0.9	[-4, -1, -4, -2, -2, -2, -2, -2, -2, -2]
+devilkin	-2.4	0.91652	[-3, -1, -2, -3, -2, -4, -2, -3, -3, -1]
+devilled	-2.3	1.1	[-3, -1, -2, -3, 0, -4, -2, -3, -2, -3]
+devilling	-1.8	1.249	[-3, -1, -1, -2, -2, -3, -4, -2, 0, 0]
+devilment	-1.9	0.9434	[-2, -1, -2, -1, -3, -2, -2, -1, -1, -4]
+devilments	-1.1	0.7	[-2, -1, -2, -2, -1, 0, 0, -1, -1, -1]
+devilries	-1.6	1.35647	[-1, -1, -2, -4, -3, 0, -2, 0, 0, -3]
+devilry	-2.8	1.249	[-4, -3, 0, -2, -2, -2, -3, -4, -4, -4]
+devils	-2.7	0.9	[-3, -1, -3, -2, -2, -3, -4, -3, -2, -4]
+deviltries	-1.5	1.11803	[-1, -2, 1, -2, 0, -2, -2, -3, -2, -2]
+deviltry	-2.8	1.32665	[-4, -4, -3, -3, -3, -3, 1, -3, -3, -3]
+devilwood	-0.8	1.07703	[0, -1, -2, 0, 0, 0, 0, -3, -2, 0]
+devilwoods	-1.0	0.7746	[-2, 0, -2, -1, -1, 0, -1, -2, 0, -1]
+devote	1.4	1.28062	[3, 0, 2, -1, 0, 3, 2, 2, 1, 2]
+devoted	1.7	1.34536	[2, -1, 3, 2, 1, 0, 1, 3, 3, 3]
+devotedly	1.6	1.35647	[1, 1, 2, 2, 3, 2, 2, -2, 2, 3]
+devotedness	2.0	1.0	[0, 3, 2, 1, 3, 2, 2, 3, 1, 3]
+devotee	1.6	1.11355	[1, 3, 0, 2, 1, 2, 1, 1, 4, 1]
+devotees	0.5	1.0247	[0, 0, 3, 0, 0, 0, 2, 0, 0, 0]
+devotement	1.5	1.36015	[2, -1, 3, 2, -1, 1, 2, 3, 2, 2]
+devotements	1.1	1.04403	[0, 1, 0, 0, 0, 2, 2, 2, 3, 1]
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+devoting	2.1	0.7	[2, 2, 3, 1, 2, 3, 2, 3, 1, 2]
+devotion	2.0	1.0	[2, 0, 1, 2, 4, 3, 2, 2, 2, 2]
+devotional	1.2	1.16619	[0, 1, 0, 2, 2, 1, 0, 0, 3, 3]
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+dick	-2.3	1.18743	[-2, -3, -4, -2, 0, -4, -2, -1, -3, -2]
+dickhead	-3.1	0.53852	[-4, -3, -3, -3, -4, -2, -3, -3, -3, -3]
+die	-2.9	0.9434	[-4, -3, -1, -2, -4, -3, -3, -3, -2, -4]
+died	-2.6	1.28062	[-3, -1, -3, -4, -2, -4, -3, -4, -2, 0]
+difficult	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -1, -2]
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+difficultly	-1.7	0.45826	[-1, -2, -1, -2, -2, -1, -2, -2, -2, -2]
+difficulty	-1.4	0.66332	[-2, -2, -2, -2, 0, -1, -1, -2, -1, -1]
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+dignify	1.8	0.74833	[1, 2, 2, 1, 3, 3, 1, 2, 2, 1]
+dignifying	2.1	1.04403	[1, 1, 1, 3, 1, 4, 2, 3, 2, 3]
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+dirtier	-1.4	0.4899	[-2, -1, -1, -2, -1, -2, -1, -1, -2, -1]
+dirtiest	-2.4	1.0198	[-4, -3, -2, -1, -2, -3, -1, -2, -4, -2]
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+disadvantage	-1.8	0.4	[-2, -2, -1, -2, -2, -1, -2, -2, -2, -2]
+disadvantaged	-1.7	0.64031	[-2, -2, -3, -1, -2, -2, -2, -1, -1, -1]
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+disadvantageously	-2.1	0.83066	[-2, -4, -1, -2, -1, -2, -2, -2, -3, -2]
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+disagree	-1.6	0.4899	[-1, -2, -1, -1, -2, -2, -2, -2, -1, -2]
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+disagreeably	-1.5	0.67082	[-3, -2, -1, -1, -1, -2, -1, -2, -1, -1]
+disagreed	-1.3	0.64031	[-1, -2, -1, -1, -2, 0, -1, -2, -1, -2]
+disagreeing	-1.4	0.8	[-1, 0, -1, -2, -2, -1, -3, -1, -1, -2]
+disagreement	-1.5	0.67082	[-2, -1, -1, -1, -1, -1, -1, -3, -2, -2]
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+disagrees	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -1, -2, -1, -2]
+disappear	-0.9	0.7	[-2, -1, 0, 0, -2, -1, -1, -1, 0, -1]
+disappeared	-0.9	0.7	[-2, 0, -1, -1, 0, 0, -2, -1, -1, -1]
+disappears	-1.4	0.8	[-2, -2, 0, 0, -2, -1, -2, -1, -2, -2]
+disappoint	-1.7	0.64031	[-1, -1, -1, -3, -2, -2, -2, -1, -2, -2]
+disappointed	-2.1	0.83066	[-1, -3, -2, -2, -3, -1, -1, -2, -3, -3]
+disappointedly	-1.7	0.78102	[-3, -1, -3, -1, -2, -1, -1, -2, -2, -1]
+disappointing	-2.2	0.6	[-1, -2, -2, -3, -3, -2, -2, -2, -3, -2]
+disappointingly	-1.9	0.7	[-2, -1, -1, -3, -2, -3, -2, -2, -1, -2]
+disappointment	-2.3	1.00499	[-3, -1, -4, -1, -3, -1, -3, -2, -2, -3]
+disappointments	-2.0	1.09545	[-1, -2, -4, -3, -2, -2, -3, 0, -2, -1]
+disappoints	-1.6	0.4899	[-2, -1, -1, -1, -2, -1, -2, -2, -2, -2]
+disaster	-3.1	0.83066	[-2, -4, -4, -3, -3, -2, -4, -3, -2, -4]
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+disastrous	-2.9	0.53852	[-2, -2, -3, -3, -3, -3, -4, -3, -3, -3]
+disbelieve	-1.2	0.87178	[-1, -2, -1, -2, -1, 0, 0, -1, -3, -1]
+discard	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -1, -2, -1]
+discarded	-1.4	0.91652	[-1, -1, -1, -1, 0, -1, -2, -3, -3, -1]
+discarding	-0.7	0.45826	[-1, 0, -1, -1, -1, 0, -1, 0, -1, -1]
+discards	-1.0	0.63246	[0, -1, -1, -1, -2, 0, -2, -1, -1, -1]
+discomfort	-1.8	0.6	[-2, -2, -2, -1, -1, -3, -2, -2, -1, -2]
+discomfortable	-1.6	0.8	[-1, -1, -1, -2, -3, -1, -2, -1, -3, -1]
+discomforted	-1.6	0.8	[-1, -1, -1, -2, -3, -3, -1, -1, -1, -2]
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+dorky	-1.1	1.04403	[-1, 0, -1, 1, -1, -1, -3, -2, -2, -1]
+doubt	-1.5	0.5	[-1, -1, -2, -2, -1, -1, -2, -1, -2, -2]
+doubtable	-1.5	0.5	[-1, -1, -2, -1, -2, -1, -2, -2, -1, -2]
+doubted	-1.1	1.22066	[-1, -2, -2, 2, -1, -1, -2, -2, -2, 0]
+doubter	-1.6	0.91652	[-1, -3, -2, -1, -1, -1, -2, -2, -3, 0]
+doubters	-1.3	0.45826	[-1, -1, -1, -1, -1, -2, -1, -2, -2, -1]
+doubtful	-1.4	0.4899	[-1, -1, -2, -1, -2, -2, -1, -1, -2, -1]
+doubtfully	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -2]
+doubtfulness	-1.2	0.4	[-2, -1, -1, -1, -1, -1, -1, -1, -1, -2]
+doubting	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -1, -1, -2, -2]
+doubtingly	-1.4	0.4899	[-2, -2, -1, -1, -1, -1, -1, -2, -2, -1]
+doubtless	0.9	1.51327	[2, 2, 1, 2, -2, 2, -2, 1, 1, 2]
+doubtlessly	1.2	0.9798	[2, 1, 1, 2, 0, -1, 2, 1, 2, 2]
+doubtlessness	0.8	0.9798	[2, 1, 2, 0, 0, 0, 2, -1, 1, 1]
+doubts	-1.2	0.6	[-2, -1, -1, -1, -2, -2, -1, 0, -1, -1]
+douche	-1.5	1.68819	[-3, -2, -3, 1, 1, -2, -3, -2, 1, -3]
+douchebag	-3.0	0.44721	[-3, -3, -3, -3, -3, -3, -2, -3, -4, -3]
+downcast	-1.8	0.74833	[-1, -1, -1, -2, -2, -2, -1, -3, -3, -2]
+downhearted	-2.3	0.78102	[-1, -2, -2, -4, -2, -2, -2, -3, -3, -2]
+downside	-1.0	0.7746	[-1, -1, -1, -1, -1, -1, -2, 1, -2, -1]
+drag	-0.9	0.83066	[-1, -2, -1, -1, -2, -1, -1, 1, 0, -1]
+dragged	-0.2	1.07703	[-2, -1, 0, 0, -1, 0, 0, 1, 2, -1]
+drags	-0.7	0.64031	[0, -1, 0, -1, -1, -2, -1, 0, 0, -1]
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+dread	-2.0	0.63246	[-2, -3, -2, -2, -2, -2, -3, -1, -1, -2]
+dreaded	-2.7	0.64031	[-2, -3, -3, -3, -4, -3, -2, -2, -2, -3]
+dreadful	-1.9	1.86815	[-4, -2, -2, 2, -1, -4, -1, 0, -3, -4]
+dreadfully	-2.7	1.26886	[-4, -4, -3, -4, -3, -1, -2, -1, -1, -4]
+dreadfulness	-3.2	0.87178	[-3, -4, -2, -3, -4, -4, -2, -2, -4, -4]
+dreadfuls	-2.4	1.2	[-4, -3, -3, -2, -3, -2, -4, 0, -1, -2]
+dreading	-2.4	0.8	[-3, -2, -2, -2, -2, -2, -3, -4, -3, -1]
+dreadlock	-0.4	0.66332	[0, 0, 0, 0, 0, -1, -2, 0, -1, 0]
+dreadlocks	-0.2	0.9798	[0, 0, 0, 0, 0, -1, -2, 2, 0, -1]
+dreadnought	-0.6	1.35647	[-2, 0, 0, 0, -3, 0, -1, -2, 0, 2]
+dreadnoughts	-0.4	0.66332	[0, -1, -1, 0, 0, 0, 0, 0, -2, 0]
+dreads	-1.4	1.42829	[0, -1, 0, 0, -3, -3, 0, -4, -2, -1]
+dream	1.0	1.18322	[0, 1, 2, 0, 0, 3, 0, 3, 1, 0]
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+dreary	-1.4	0.4899	[-1, -1, -2, -1, -1, -2, -2, -1, -2, -1]
+droopy	-0.8	0.74833	[-1, -1, 0, -1, -2, 0, 0, -1, 0, -2]
+drop	-1.1	0.53852	[0, -1, -1, -1, -2, -1, -2, -1, -1, -1]
+drown	-2.7	1.00499	[-4, -2, -2, -4, -4, -2, -3, -1, -3, -2]
+drowned	-2.9	0.7	[-2, -3, -3, -3, -2, -4, -4, -2, -3, -3]
+drowns	-2.2	1.6	[-3, -3, -3, -4, -2, -3, -1, -2, 2, -3]
+drunk	-1.4	0.91652	[-3, -1, 0, -2, 0, -1, -1, -2, -2, -2]
+dubious	-1.5	0.5	[-1, -2, -2, -1, -1, -2, -1, -1, -2, -2]
+dud	-1.0	0.89443	[-1, -1, -1, 0, -3, 0, -1, 0, -1, -2]
+dull	-1.7	0.45826	[-2, -2, -2, -1, -2, -2, -2, -1, -1, -2]
+dullard	-1.6	0.66332	[-2, -1, -1, -2, -2, -1, -1, -2, -1, -3]
+dullards	-1.8	0.87178	[-1, -3, -1, -1, -3, -1, -1, -2, -3, -2]
+dulled	-1.5	0.5	[-2, -1, -2, -1, -1, -1, -2, -2, -1, -2]
+duller	-1.7	0.64031	[-3, -1, -2, -2, -2, -1, -2, -1, -1, -2]
+dullest	-1.7	1.00499	[-1, -4, -1, -1, -2, -3, -2, -1, -1, -1]
+dulling	-1.1	0.7	[-1, -2, 0, -1, -2, -2, 0, -1, -1, -1]
+dullish	-1.1	0.53852	[-2, -1, -1, -1, -1, -1, -1, -1, 0, -2]
+dullness	-1.4	0.8	[-1, -1, -1, -1, -1, -1, -3, -1, -3, -1]
+dullnesses	-1.9	1.04403	[-3, -2, -1, -1, -3, -1, -4, -1, -2, -1]
+dulls	-1.0	0.44721	[-1, -1, -1, -1, -1, -1, 0, -1, -1, -2]
+dullsville	-2.4	0.8	[-2, -2, -4, -3, -2, -2, -3, -2, -3, -1]
+dully	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -1, -1, -1, -2]
+dumb	-2.3	0.9	[-4, -2, -2, -2, -2, -2, -4, -2, -2, -1]
+dumbass	-2.6	1.0198	[-3, -3, -4, -4, -1, -2, -3, -3, -1, -2]
+dumbbell	-0.8	0.9798	[0, -1, -3, -2, 0, -1, 0, 0, -1, 0]
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+dumbcane	-0.3	0.45826	[0, 0, 0, 0, 0, -1, -1, 0, -1, 0]
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+dumbed	-1.4	0.4899	[-2, -1, -2, -2, -2, -1, -1, -1, -1, -1]
+dumber	-1.5	0.5	[-2, -1, -2, -1, -2, -1, -1, -2, -2, -1]
+dumbest	-2.3	1.00499	[-3, -1, -3, -4, -2, -1, -2, -3, -1, -3]
+dumbfound	-0.1	1.92094	[3, -2, -1, -1, 1, 1, -3, 3, -1, -1]
+dumbfounded	-1.6	1.11355	[-2, 0, -2, 0, -2, -1, -4, -1, -2, -2]
+dumbfounder	-1.0	0.89443	[-2, 0, 0, 0, -2, -1, -2, 0, -2, -1]
+dumbfounders	-1.0	0.89443	[-1, -3, -1, 0, -2, 0, -1, 0, -1, -1]
+dumbfounding	-0.8	0.74833	[-1, -2, 0, -1, -1, 0, 0, -1, 0, -2]
+dumbfounds	-0.3	1.26886	[0, -1, -1, 0, 0, -1, -1, -2, 0, 3]
+dumbhead	-2.6	0.66332	[-3, -4, -3, -2, -2, -3, -3, -2, -2, -2]
+dumbheads	-1.9	0.83066	[-2, -2, -2, -1, -2, -1, -2, -4, -1, -2]
+dumbing	-0.5	1.0247	[-1, 2, -1, 0, -1, -2, -1, 0, 0, -1]
+dumbly	-1.3	1.00499	[-2, -1, -2, -3, 1, -2, -1, -1, -1, -1]
+dumbness	-1.9	0.53852	[-2, -2, -2, -2, -2, -3, -2, -2, -1, -1]
+dumbs	-1.5	0.67082	[-1, -1, -1, -3, -2, -1, -2, -1, -2, -1]
+dumbstruck	-1.0	1.34164	[-1, -2, 0, 0, -2, 1, -3, 1, -2, -2]
+dumbwaiter	0.2	1.07703	[0, 0, 0, 0, 2, 0, 2, 0, -2, 0]
+dumbwaiters	-0.1	0.3	[0, 0, 0, 0, 0, 0, -1, 0, 0, 0]
+dump	-1.6	0.91652	[-3, -2, -1, -2, -1, -3, -2, -1, -1, 0]
+dumpcart	-0.6	0.8	[0, -2, -1, 0, 0, 0, -1, 0, -2, 0]
+dumped	-1.7	0.78102	[-2, -3, -2, -1, -1, -1, -3, -2, -1, -1]
+dumper	-1.2	0.87178	[-2, -3, -1, -1, -1, -2, 0, -1, 0, -1]
+dumpers	-0.8	0.6	[0, 0, -2, -1, -1, 0, -1, -1, -1, -1]
+dumpier	-1.4	0.66332	[-2, -1, -2, -1, -1, -2, 0, -2, -1, -2]
+dumpiest	-1.6	1.35647	[-1, -2, -2, -3, -2, -4, 1, 0, -1, -2]
+dumpiness	-1.2	0.6	[-2, -1, 0, -1, -1, -2, -1, -2, -1, -1]
+dumping	-1.3	1.1	[-3, -2, -2, 0, -2, -1, -1, 1, -1, -2]
+dumpings	-1.1	0.83066	[-2, 0, -1, -1, 0, -1, -2, -2, 0, -2]
+dumpish	-1.8	0.6	[-2, -1, -2, -3, -2, -2, -1, -2, -2, -1]
+dumpling	0.4	0.91652	[0, 0, 1, 0, -1, 2, 2, 0, 0, 0]
+dumplings	-0.3	1.26886	[0, 0, 0, 0, 2, 0, 0, 0, -2, -3]
+dumps	-1.7	0.9	[-3, -2, -3, -1, -1, -3, -1, -1, -1, -1]
+dumpster	-0.6	0.91652	[0, -2, 0, -2, 0, 0, 0, -2, 0, 0]
+dumpsters	-1.0	0.89443	[0, -1, 0, -2, -2, -2, 0, 0, -1, -2]
+dumpy	-1.7	0.78102	[-3, -2, -3, -1, -1, -2, -2, -1, -1, -1]
+dupe	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -2, -1, -2, -1]
+duped	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -1, -2, -2]
+dwell	0.5	0.92195	[2, 1, -1, 0, -1, 1, 1, 1, 1, 0]
+dwelled	0.4	0.66332	[2, 0, 0, 0, 0, 1, 1, 0, 0, 0]
+dweller	0.3	0.64031	[2, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+dwellers	-0.3	0.9	[-3, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+dwelling	0.1	0.53852	[0, 1, 0, 1, 0, 0, 0, -1, 0, 0]
+dwells	-0.1	0.53852	[0, 0, 0, 0, -1, 1, -1, 0, 0, 0]
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+dynamical	1.2	0.87178	[1, 2, 0, 1, 0, 2, 2, 2, 2, 0]
+dynamically	1.5	1.0247	[2, 0, 3, 2, 0, 0, 2, 2, 2, 2]
+dynamics	1.1	1.13578	[2, 3, 0, 0, 0, 2, 2, 0, 2, 0]
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+dynamistic	1.5	1.0247	[3, 1, 1, 2, 1, 3, 2, 0, 2, 0]
+dynamists	0.9	0.83066	[1, 0, 0, 0, 0, 2, 2, 1, 2, 1]
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+dynamited	-0.9	1.04403	[0, 0, 0, -1, -1, 0, -2, 0, -2, -3]
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+dynamiters	0.4	1.42829	[0, 0, 0, -3, 1, 0, 2, 2, 2, 0]
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+dynamiting	0.2	1.32665	[-2, 0, 0, 2, -1, -1, 0, 2, 2, 0]
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+dynamometric	0.3	0.9	[0, 0, 0, 0, 0, 2, 0, 0, 2, -1]
+dynamometry	0.6	1.28062	[-2, 0, 0, 0, 0, 2, 2, 2, 0, 2]
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+dynamotor	0.6	0.91652	[0, 2, 0, 0, 0, 0, 2, 0, 2, 0]
+dysfunction	-1.8	0.6	[-2, -3, -2, -1, -2, -1, -2, -1, -2, -2]
+eager	1.5	0.67082	[1, 3, 1, 2, 2, 2, 1, 1, 1, 1]
+eagerly	1.6	0.66332	[0, 1, 2, 2, 2, 2, 2, 1, 2, 2]
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+eagers	1.6	0.66332	[2, 2, 3, 1, 2, 1, 1, 1, 2, 1]
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+ease	1.5	0.92195	[1, 1, 1, 0, 2, 1, 2, 3, 3, 1]
+eased	1.2	0.74833	[2, 0, 1, 0, 2, 2, 1, 1, 1, 2]
+easeful	1.5	1.0247	[2, 1, 1, 2, 1, 0, 3, 2, 0, 3]
+easefully	1.4	0.4899	[2, 2, 1, 1, 1, 1, 2, 2, 1, 1]
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+easement	1.6	0.91652	[0, 1, 2, 3, 2, 1, 2, 1, 3, 1]
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+easier	1.8	0.9798	[1, 1, 2, 2, 4, 3, 2, 1, 1, 1]
+easiest	1.8	1.07703	[2, 4, 1, 3, 2, 0, 2, 2, 1, 1]
+easily	1.4	0.4899	[2, 1, 1, 2, 1, 2, 1, 2, 1, 1]
+easiness	1.6	0.66332	[2, 1, 1, 2, 3, 2, 1, 1, 2, 1]
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+easygoing	1.3	0.45826	[1, 1, 1, 1, 1, 1, 2, 2, 2, 1]
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+ecstasy	2.9	1.75784	[4, 3, 3, 4, 4, 2, -2, 3, 4, 4]
+ecstatic	2.3	1.34536	[3, 4, 3, 4, 1, 1, 1, 4, 1, 1]
+ecstatically	2.8	1.93907	[3, 4, -1, 4, 4, 4, -1, 3, 4, 4]
+ecstatics	2.9	0.83066	[1, 3, 4, 4, 3, 3, 3, 2, 3, 3]
+eerie	-1.5	0.67082	[-1, -1, -2, -2, -1, -1, -2, -1, -3, -1]
+eery	-0.9	1.04403	[-3, -1, -2, -1, -2, 0, 0, 0, 0, 0]
+effective	2.1	0.83066	[2, 2, 2, 1, 3, 4, 2, 1, 2, 2]
+effectively	1.9	0.7	[1, 2, 1, 2, 2, 1, 3, 3, 2, 2]
+efficiencies	1.6	0.4899	[2, 1, 1, 2, 2, 2, 1, 2, 2, 1]
+efficiency	1.5	0.5	[2, 1, 2, 2, 1, 2, 1, 1, 2, 1]
+efficient	1.8	0.9798	[1, 2, 1, 1, 2, 3, 3, 0, 2, 3]
+efficiently	1.7	0.78102	[1, 3, 2, 1, 3, 1, 1, 2, 2, 1]
+effin	-2.3	1.18743	[0, -3, -3, -3, -2, -1, -4, -1, -3, -3]
+egotism	-1.4	0.91652	[-2, -3, -1, -2, -2, 0, 0, -1, -2, -1]
+egotisms	-1.0	0.7746	[-1, -1, -1, -1, -1, 0, 0, -1, -3, -1]
+egotist	-2.3	0.9	[-2, -1, -2, -3, -4, -2, -3, -3, -1, -2]
+egotistic	-1.4	1.0198	[-2, -1, -1, -1, -2, 1, -3, -2, -1, -2]
+egotistical	-0.9	1.57797	[-1, -2, -2, -1, -2, 1, -3, 2, 1, -2]
+egotistically	-1.8	0.87178	[-2, -1, -1, -2, -1, -3, -3, -1, -1, -3]
+egotists	-1.7	0.78102	[-1, -2, 0, -2, -2, -2, -3, -1, -2, -2]
+elated	3.2	0.74833	[2, 4, 4, 3, 4, 3, 3, 2, 3, 4]
+elation	1.5	1.43178	[1, 2, -2, 2, 2, 3, 0, 3, 2, 2]
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+elegancies	1.6	1.0198	[2, 1, 2, 1, 1, 0, 4, 1, 2, 2]
+elegancy	2.1	0.53852	[3, 2, 2, 1, 2, 2, 3, 2, 2, 2]
+elegant	2.1	0.83066	[2, 2, 2, 1, 4, 1, 2, 3, 2, 2]
+elegantly	1.9	0.83066	[2, 1, 1, 3, 2, 2, 1, 3, 3, 1]
+embarrass	-1.2	1.66132	[-2, -2, -3, -1, -2, -2, 2, 2, -2, -2]
+embarrassable	-1.6	0.8	[-3, -2, -1, -3, -1, -1, -1, -2, -1, -1]
+embarrassed	-1.5	0.67082	[-2, -2, -1, -2, -1, -3, -1, -1, -1, -1]
+embarrassedly	-1.1	1.44568	[-2, -1, -2, -3, 1, -1, -1, -2, -2, 2]
+embarrasses	-1.7	0.78102	[-2, -3, -1, -2, -1, -3, -2, -1, -1, -1]
+embarrassing	-1.6	0.8	[-3, -1, -1, -1, -1, -2, -1, -2, -3, -1]
+embarrassingly	-1.7	0.64031	[-2, -1, -1, -2, -1, -2, -1, -3, -2, -2]
+embarrassment	-1.9	0.53852	[-2, -2, -1, -2, -2, -2, -2, -1, -3, -2]
+embarrassments	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -3]
+embittered	-0.4	1.35647	[1, -2, -1, 1, -2, 2, 0, -1, 0, -2]
+embrace	1.3	1.34536	[3, 2, 1, 3, 2, -1, 2, 1, -1, 1]
+emergency	-1.6	2.05913	[-3, -3, -3, -3, -4, 2, 1, -1, 1, -3]
+emotional	0.6	1.0198	[1, -1, 0, 0, 0, 2, 0, 2, 2, 0]
+empathetic	1.7	1.1	[-1, 3, 2, 2, 2, 1, 3, 1, 2, 2]
+emptied	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
+emptier	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
+emptiers	-0.7	0.78102	[0, 0, -1, 0, -1, -1, -2, 0, -2, 0]
+empties	-0.7	0.64031	[-1, 0, 0, 0, -1, -1, -1, -2, 0, -1]
+emptiest	-1.8	1.07703	[-1, -2, -2, -1, -1, -2, -3, 0, -4, -2]
+emptily	-1.0	1.41421	[-2, 2, -1, -1, -1, 0, -4, -1, -1, -1]
+emptiness	-1.9	0.7	[-2, -2, -3, -2, -2, -1, -1, -3, -1, -2]
+emptinesses	-1.5	1.11803	[-1, -1, -3, -1, -1, -1, -2, 0, -4, -1]
+emptins	-0.3	0.45826	[0, 0, 0, -1, 0, 0, 0, -1, -1, 0]
+empty	-0.8	0.74833	[-1, -1, -1, -1, -1, -1, -2, 0, -1, 1]
+emptying	-0.6	1.0198	[2, -1, -1, 0, -1, 0, -1, -1, -2, -1]
+enchanted	1.6	0.8	[1, 3, 1, 2, 1, 3, 1, 2, 1, 1]
+encourage	2.3	0.78102	[2, 1, 3, 2, 3, 4, 2, 2, 2, 2]
+encouraged	1.5	0.5	[1, 2, 2, 2, 2, 2, 1, 1, 1, 1]
+encouragement	1.8	0.9798	[2, 1, 2, 1, 1, 3, 1, 2, 4, 1]
+encouragements	2.1	0.7	[3, 2, 3, 2, 1, 2, 3, 2, 2, 1]
+encourager	1.5	0.5	[2, 1, 2, 1, 1, 2, 1, 1, 2, 2]
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+encourages	1.9	0.53852	[2, 2, 1, 2, 2, 1, 2, 2, 2, 3]
+encouraging	2.4	0.66332	[2, 3, 2, 3, 3, 2, 3, 2, 1, 3]
+encouragingly	2.0	0.7746	[1, 1, 1, 3, 2, 2, 2, 3, 2, 3]
+endorse	1.3	0.9	[0, 1, 0, 1, 3, 2, 2, 2, 1, 1]
+endorsed	1.0	0.89443	[1, 2, 0, 1, 1, 0, 1, 0, 3, 1]
+endorsement	1.3	0.9	[0, 1, 2, 2, 1, 2, 0, 1, 3, 1]
+endorses	1.4	0.4899	[1, 2, 1, 2, 1, 1, 1, 2, 2, 1]
+enemies	-2.2	0.6	[-2, -3, -1, -2, -2, -3, -2, -3, -2, -2]
+enemy	-2.5	0.92195	[-3, -2, -3, -3, -3, -4, -1, -3, -1, -2]
+energetic	1.9	0.53852	[2, 1, 3, 2, 2, 2, 1, 2, 2, 2]
+energetically	1.8	0.6	[2, 2, 1, 1, 2, 2, 3, 1, 2, 2]
+energetics	0.3	0.64031	[1, 0, 0, 0, 0, 0, 2, 0, 0, 0]
+energies	0.9	1.04403	[1, 0, 0, 2, 0, 1, 3, 2, 0, 0]
+energise	2.2	0.4	[2, 2, 2, 2, 2, 2, 3, 2, 3, 2]
+energised	2.1	0.53852	[2, 3, 1, 2, 2, 2, 3, 2, 2, 2]
+energises	2.2	0.6	[3, 3, 2, 2, 1, 3, 2, 2, 2, 2]
+energising	1.9	0.7	[2, 3, 1, 2, 2, 3, 2, 1, 1, 2]
+energization	1.6	0.66332	[1, 2, 1, 3, 1, 1, 2, 2, 2, 1]
+energizations	1.5	1.11803	[1, 0, 3, 1, 3, 0, 1, 1, 2, 3]
+energize	2.1	0.7	[2, 2, 2, 1, 3, 2, 3, 2, 3, 1]
+energized	2.3	0.64031	[3, 2, 3, 3, 3, 2, 2, 2, 1, 2]
+energizer	2.1	0.53852	[3, 2, 2, 2, 2, 2, 2, 3, 1, 2]
+energizers	1.7	0.9	[2, 0, 2, 3, 3, 1, 1, 2, 2, 1]
+energizes	2.1	0.53852	[3, 2, 3, 2, 2, 2, 2, 2, 1, 2]
+energizing	2.0	0.63246	[3, 3, 2, 1, 2, 2, 1, 2, 2, 2]
+energy	1.1	0.83066	[0, 2, 0, 2, 1, 1, 2, 1, 2, 0]
+engage	1.4	0.8	[1, 2, 3, 2, 1, 1, 0, 1, 2, 1]
+engaged	1.7	1.1	[1, 1, 2, 2, 1, 0, 2, 3, 4, 1]
+engagement	2.0	1.34164	[0, 0, 3, 4, 4, 2, 1, 2, 2, 2]
+engagements	0.6	0.8	[1, 0, 0, 2, 0, 2, 0, 0, 1, 0]
+engager	1.1	0.7	[1, 1, 0, 2, 1, 0, 2, 1, 2, 1]
+engagers	1.0	0.7746	[1, 1, 1, 0, 2, 1, 0, 2, 2, 0]
+engages	1.0	0.7746	[1, 1, 0, 2, 1, 0, 1, 2, 2, 0]
+engaging	1.4	0.4899	[2, 2, 1, 1, 2, 1, 1, 1, 1, 2]
+engagingly	1.5	0.67082	[1, 2, 3, 1, 1, 1, 1, 1, 2, 2]
+engrossed	0.6	1.49666	[0, 2, 0, 2, -2, 2, 3, -1, 0, 0]
+enjoy	2.2	0.6	[3, 2, 2, 2, 3, 2, 2, 3, 2, 1]
+enjoyable	1.9	0.53852	[3, 2, 2, 1, 2, 1, 2, 2, 2, 2]
+enjoyableness	1.9	1.13578	[2, 2, 2, 2, 1, 3, 3, 3, -1, 2]
+enjoyably	1.8	0.4	[2, 2, 2, 1, 2, 1, 2, 2, 2, 2]
+enjoyed	2.3	0.64031	[2, 2, 1, 3, 3, 3, 2, 2, 2, 3]
+enjoyer	2.2	0.6	[2, 2, 1, 3, 3, 2, 2, 2, 2, 3]
+enjoyers	2.2	0.74833	[2, 4, 2, 2, 2, 2, 2, 3, 2, 1]
+enjoying	2.4	0.66332	[2, 2, 2, 3, 3, 3, 1, 3, 2, 3]
+enjoyment	2.6	0.4899	[2, 3, 2, 3, 2, 3, 2, 3, 3, 3]
+enjoyments	2.0	0.7746	[3, 1, 1, 3, 2, 1, 2, 2, 2, 3]
+enjoys	2.3	0.45826	[2, 3, 2, 2, 2, 3, 2, 3, 2, 2]
+enlighten	2.3	1.1	[2, 2, 1, 3, 2, 1, 1, 4, 3, 4]
+enlightened	2.2	0.87178	[4, 2, 3, 1, 2, 2, 1, 3, 2, 2]
+enlightening	2.3	0.64031	[3, 2, 2, 2, 2, 2, 2, 4, 2, 2]
+enlightens	1.7	1.00499	[2, 1, 1, 1, 1, 2, 4, 1, 3, 1]
+ennui	-1.2	0.6	[-1, -1, -1, -2, -1, -1, -2, -1, 0, -2]
+enrage	-2.6	0.91652	[-3, -3, -3, -4, -1, -1, -3, -2, -3, -3]
+enraged	-1.7	1.79165	[-3, -3, -3, -3, 2, -1, -3, -1, 1, -3]
+enrages	-1.8	1.6	[-3, -3, -3, -3, 1, -1, -3, -1, 1, -3]
+enraging	-2.8	0.74833	[-4, -2, -3, -2, -2, -3, -3, -2, -4, -3]
+enrapture	3.0	0.63246	[2, 4, 3, 3, 4, 3, 3, 2, 3, 3]
+enslave	-3.1	0.9434	[-3, -4, -2, -4, -4, -2, -4, -2, -4, -2]
+enslaved	-1.7	2.41039	[3, -3, -3, -3, -4, -4, -4, 1, -1, 1]
+enslaves	-1.6	2.15407	[2, -2, -3, -2, -4, -4, -4, 1, -1, 1]
+ensure	1.6	0.91652	[2, 1, 3, 1, 1, 2, 3, 2, 0, 1]
+ensuring	1.1	0.9434	[0, 1, 3, 1, 1, 2, 1, 0, 2, 0]
+enterprising	2.3	0.78102	[3, 2, 1, 3, 3, 2, 1, 2, 3, 3]
+entertain	1.3	0.64031	[1, 2, 1, 1, 2, 1, 2, 0, 1, 2]
+entertained	1.7	0.64031	[1, 2, 2, 1, 2, 1, 1, 3, 2, 2]
+entertainer	1.6	1.2	[1, 4, 2, 2, 0, 0, 1, 3, 1, 2]
+entertainers	1.0	0.7746	[0, 1, 2, 2, 0, 0, 1, 1, 2, 1]
+entertaining	1.9	0.83066	[1, 2, 1, 1, 3, 2, 3, 2, 3, 1]
+entertainingly	1.9	0.53852	[2, 1, 2, 3, 2, 2, 1, 2, 2, 2]
+entertainment	1.8	0.9798	[2, 0, 4, 2, 2, 1, 2, 2, 1, 2]
+entertainments	2.3	1.18743	[3, 3, 3, 2, 1, 0, 3, 4, 1, 3]
+entertains	2.4	0.66332	[2, 2, 2, 2, 2, 3, 4, 3, 2, 2]
+enthral	0.4	1.42829	[2, 2, 0, 2, 0, -1, -2, 2, 0, -1]
+enthuse	1.6	0.66332	[1, 2, 1, 1, 3, 1, 2, 2, 2, 1]
+enthused	2.0	0.63246	[3, 3, 1, 2, 2, 2, 2, 1, 2, 2]
+enthuses	1.7	0.78102	[2, 3, 1, 2, 1, 3, 1, 1, 1, 2]
+enthusiasm	1.9	0.9434	[3, 3, 3, 2, 1, 0, 2, 1, 2, 2]
+enthusiasms	2.0	0.89443	[1, 3, 2, 2, 3, 2, 0, 2, 3, 2]
+enthusiast	1.5	0.67082	[1, 2, 2, 2, 0, 1, 1, 2, 2, 2]
+enthusiastic	2.2	0.9798	[1, 2, 3, 4, 2, 3, 2, 1, 1, 3]
+enthusiastically	2.6	0.66332	[3, 3, 3, 2, 3, 3, 3, 3, 2, 1]
+enthusiasts	1.4	0.91652	[1, 1, 0, 3, 3, 2, 1, 1, 1, 1]
+enthusing	1.9	0.7	[2, 1, 2, 1, 2, 3, 2, 1, 2, 3]
+entitled	1.1	0.83066	[2, 2, 1, 1, 2, 1, 1, -1, 1, 1]
+entrusted	0.8	1.46969	[3, 0, 2, 2, 1, 1, -1, 0, -2, 2]
+envied	-1.1	0.83066	[-1, -2, -2, 1, -2, -1, -1, -1, -1, -1]
+envier	-1.0	0.7746	[-1, -2, -2, -1, -1, 1, -1, -1, -1, -1]
+enviers	-1.1	1.13578	[-3, -1, 0, -3, -1, -1, -1, -1, 1, -1]
+envies	-0.8	0.9798	[-1, -2, -2, 1, -1, 1, -1, -1, -1, -1]
+envious	-1.1	0.83066	[-2, -1, -1, -1, -2, -1, -1, 1, -2, -1]
+envy	-1.1	0.83066	[-2, -1, -1, -2, -1, -1, -1, 1, -1, -2]
+envying	-0.8	1.32665	[-1, -1, -1, -1, -3, 2, -2, -1, 1, -1]
+envyingly	-1.3	1.55242	[-2, 3, -2, -2, -1, -3, -1, -1, -2, -2]
+erroneous	-1.8	0.6	[-2, -3, -2, -2, -2, -2, -1, -1, -1, -2]
+error	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -1, -2, -3, -2]
+errors	-1.4	0.66332	[-2, -1, -2, 0, -2, -2, -1, -1, -1, -2]
+escape	0.7	1.00499	[2, 0, 0, 1, 0, 1, 0, 3, 0, 0]
+escapes	0.5	1.36015	[4, 1, 1, 0, -1, 0, -1, 0, 1, 0]
+escaping	0.2	1.46969	[-2, 2, -1, 0, 1, 0, 2, 2, -2, 0]
+esteemed	1.9	0.83066	[3, 2, 1, 2, 3, 1, 1, 2, 3, 1]
+ethical	2.3	0.78102	[3, 3, 3, 3, 2, 2, 1, 3, 2, 1]
+euphoria	3.3	0.9	[4, 4, 3, 3, 3, 4, 4, 4, 1, 3]
+euphoric	3.2	0.87178	[3, 4, 3, 3, 3, 4, 4, 4, 1, 3]
+eviction	-2.0	0.63246	[-2, -2, -3, -2, -3, -2, -1, -2, -1, -2]
+evil	-3.4	0.91652	[-4, -4, -4, -3, -3, -4, -1, -4, -3, -4]
+evildoer	-3.1	0.7	[-2, -3, -3, -3, -4, -4, -3, -2, -3, -4]
+evildoers	-2.4	0.4899	[-3, -3, -2, -2, -2, -2, -2, -2, -3, -3]
+evildoing	-3.1	0.7	[-4, -4, -3, -3, -3, -4, -2, -3, -2, -3]
+evildoings	-2.5	1.0247	[-3, -1, -1, -3, -4, -2, -4, -2, -2, -3]
+eviler	-2.1	1.13578	[-2, -1, -3, -2, -4, -3, -1, -2, 0, -3]
+evilest	-2.5	1.0247	[-3, -4, -1, -3, -2, -3, -1, -4, -2, -2]
+eviller	-2.9	0.83066	[-3, -3, -4, -2, -2, -3, -2, -4, -2, -4]
+evillest	-3.3	0.78102	[-3, -4, -2, -3, -4, -2, -4, -4, -3, -4]
+evilly	-3.4	0.8	[-2, -4, -4, -4, -3, -4, -4, -4, -3, -2]
+evilness	-3.1	1.04403	[-3, -4, -4, -4, -4, -2, -3, -2, -1, -4]
+evils	-2.7	0.78102	[-3, -2, -2, -4, -4, -2, -3, -2, -3, -2]
+exaggerate	-0.6	0.66332	[-1, -1, -1, 0, -1, 0, 1, -1, -1, -1]
+exaggerated	-0.4	1.2	[-1, -1, -1, -1, -1, 2, 1, 1, -2, -1]
+exaggerates	-0.6	1.28062	[-1, -1, -1, -1, -1, 1, 0, 2, -3, -1]
+exaggerating	-0.7	0.9	[-1, -2, 0, -1, 0, 0, -2, -1, 1, -1]
+exasperated	-1.8	1.53623	[-4, -3, -3, -1, -1, -1, 1, -1, -4, -1]
+excel	2.0	1.0	[3, 0, 2, 3, 1, 1, 3, 3, 2, 2]
+excelled	2.2	0.87178	[1, 2, 2, 2, 3, 2, 4, 3, 2, 1]
+excellence	3.1	0.9434	[4, 3, 4, 3, 2, 3, 1, 4, 3, 4]
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+excellencies	2.4	0.4899	[3, 2, 3, 3, 2, 2, 2, 2, 3, 2]
+excellency	2.5	0.80623	[4, 2, 3, 3, 2, 3, 1, 3, 2, 2]
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+excelling	2.5	0.67082	[2, 2, 3, 3, 3, 2, 2, 4, 2, 2]
+excels	2.5	0.92195	[4, 2, 4, 2, 2, 1, 2, 3, 3, 2]
+excelsior	0.7	0.64031	[1, 0, 0, 2, 0, 1, 1, 1, 1, 0]
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+excitability	1.2	0.87178	[0, 1, 1, 0, 1, 2, 3, 1, 2, 1]
+excitable	1.5	0.92195	[2, 3, 1, 0, 1, 2, 2, 0, 2, 2]
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+excitant	1.8	1.16619	[1, 0, 1, 3, 2, 0, 3, 3, 2, 3]
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+excitation	1.8	0.87178	[2, 0, 3, 1, 3, 2, 2, 2, 1, 2]
+excitations	1.8	1.16619	[3, 3, -1, 2, 2, 2, 1, 1, 3, 2]
+excitative	0.3	0.78102	[0, 1, 1, 0, 0, 0, 2, 0, -1, 0]
+excitatory	1.1	1.7	[-1, 2, 2, 1, 2, 2, 2, 3, -3, 1]
+excite	2.1	1.22066	[1, 2, 2, 1, 2, 0, 4, 4, 3, 2]
+excited	1.4	0.4899	[1, 1, 2, 1, 2, 1, 2, 1, 1, 2]
+excitedly	2.3	0.9	[3, 3, 2, 3, 1, 3, 1, 3, 1, 3]
+excitement	2.2	0.4	[2, 2, 2, 3, 3, 2, 2, 2, 2, 2]
+excitements	1.9	0.53852	[2, 1, 2, 3, 2, 2, 2, 2, 2, 1]
+exciter	1.9	0.9434	[3, 2, 3, 1, 0, 1, 2, 3, 2, 2]
+exciters	1.4	1.42829	[1, 2, 0, 1, 2, 4, 0, -1, 3, 2]
+excites	2.1	0.83066	[2, 3, 3, 2, 0, 2, 2, 3, 2, 2]
+exciting	2.2	0.87178	[3, 2, 1, 1, 1, 3, 3, 3, 2, 3]
+excitingly	1.9	0.9434	[3, 2, 3, 0, 1, 2, 1, 2, 2, 3]
+exciton	0.3	0.64031	[2, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+excitonic	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
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+excitor	0.5	0.67082	[2, 0, 0, 0, 1, 1, 1, 0, 0, 0]
+exclude	-0.9	1.13578	[-1, -2, -1, -3, -1, 1, -1, -1, 1, -1]
+excluded	-1.4	1.62481	[-2, -1, -3, -3, -2, -3, -2, 1, -1, 2]
+exclusion	-1.2	1.249	[-2, -2, -3, -1, -2, -1, -1, -1, 2, -1]
+exclusive	0.5	0.92195	[0, 0, 0, -1, 2, 0, 1, 2, 1, 0]
+excruciate	-2.7	0.64031	[-2, -3, -2, -3, -3, -2, -4, -3, -2, -3]
+excruciated	-1.3	1.9	[-4, -1, -4, 0, 2, -2, -1, -1, -3, 1]
+excruciates	-1.0	2.19089	[-4, 1, -4, 0, 1, -3, -1, 1, -3, 2]
+excruciating	-3.3	0.9	[-3, -4, -4, -4, -4, -4, -4, -2, -2, -2]
+excruciatingly	-2.9	1.04403	[-2, -4, -3, -2, -4, -1, -2, -3, -4, -4]
+excruciation	-3.4	0.66332	[-4, -3, -2, -4, -4, -3, -4, -3, -3, -4]
+excruciations	-1.9	1.51327	[-3, -3, -2, -4, -1, -1, 1, -4, -1, -1]
+excuse	0.3	1.73494	[0, 0, 3, -1, 0, -1, -2, 0, 4, 0]
+exempt	0.4	0.91652	[1, 0, 0, 0, 2, -1, 0, 0, 2, 0]
+exhaust	-1.2	0.87178	[0, -1, 0, -1, -1, -3, -2, -2, -1, -1]
+exhausted	-1.5	1.28452	[-2, -1, 2, -2, -3, -2, -2, -1, -2, -2]
+exhauster	-1.3	0.64031	[-1, -1, 0, -1, -2, -1, -1, -2, -2, -2]
+exhausters	-1.3	0.45826	[-2, -1, -2, -1, -1, -2, -1, -1, -1, -1]
+exhaustibility	-0.8	1.07703	[0, -2, -3, 0, 1, -1, -1, -1, 0, -1]
+exhaustible	-1.0	0.63246	[-1, -1, 0, -1, -2, -2, -1, 0, -1, -1]
+exhausting	-1.5	0.5	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -2]
+exhaustion	-1.5	0.92195	[-2, -1, 1, -2, -2, -2, -2, -1, -2, -2]
+exhaustions	-1.1	0.9434	[-1, -3, -2, -1, -1, -1, -1, 1, -1, -1]
+exhaustive	-0.5	0.67082	[-1, -1, 0, -1, -2, 0, 0, 0, 0, 0]
+exhaustively	-0.7	0.78102	[-2, 0, -1, -1, -1, -2, 0, 0, 0, 0]
+exhaustiveness	-1.1	1.3	[-2, -2, 0, -1, -1, 1, -4, -1, 0, -1]
+exhaustless	0.2	1.8868	[1, 1, 0, 2, 3, 0, -2, 2, -2, -3]
+exhaustlessness	0.9	1.75784	[2, 2, 1, 1, -4, 2, 1, 2, 0, 2]
+exhausts	-1.1	0.53852	[-2, -1, 0, -1, -1, -2, -1, -1, -1, -1]
+exhilarated	3.0	0.63246	[3, 3, 3, 3, 2, 2, 4, 4, 3, 3]
+exhilarates	2.8	1.07703	[4, 3, 3, 3, 0, 2, 3, 4, 3, 3]
+exhilarating	1.7	1.61555	[3, 4, 3, 2, -1, 1, 1, 3, -1, 2]
+exonerate	1.8	0.74833	[2, 2, 2, 2, 3, 2, 1, 0, 2, 2]
+exonerated	1.8	1.83303	[3, -2, 2, 3, 2, 4, 3, 1, -1, 3]
+exonerates	1.6	1.90788	[3, -2, 1, 2, 3, 4, 0, 3, -1, 3]
+exonerating	1.0	1.41421	[2, -2, 3, 0, 0, 2, 0, 2, 2, 1]
+expand	1.3	0.64031	[0, 2, 2, 1, 1, 1, 2, 1, 2, 1]
+expands	0.4	0.66332	[0, 1, 0, 0, 0, 0, 0, 0, 2, 1]
+expel	-1.9	1.44568	[0, -4, -3, -1, -3, -1, 0, -2, -4, -1]
+expelled	-1.0	1.94936	[-1, -2, 2, -2, -4, -3, -2, 1, 2, -1]
+expelling	-1.6	1.49666	[-2, -2, -2, -2, -2, -3, -4, -1, 1, 1]
+expels	-1.6	1.11355	[-4, -2, 0, -3, -1, -1, -1, -2, -1, -1]
+exploit	-0.4	1.62481	[-2, -1, -1, 2, -2, -2, 2, -1, 2, -1]
+exploited	-2.0	1.0	[-3, -3, -1, -1, -1, -4, -2, -2, -1, -2]
+exploiting	-1.9	1.22066	[0, -3, -3, 0, -2, -3, -1, -1, -3, -3]
+exploits	-1.4	0.8	[-2, -2, -2, -1, -1, 0, -2, 0, -2, -2]
+exploration	0.9	0.7	[2, 2, 0, 1, 1, 0, 1, 0, 1, 1]
+explorations	0.3	1.1	[1, 1, 0, 0, 1, 2, 1, -2, -1, 0]
+expose	-0.6	0.8	[-1, -1, 0, 0, -2, 1, -1, 0, -1, -1]
+exposed	-0.3	1.18743	[-2, -1, 0, 2, 0, 0, -1, 1, -2, 0]
+exposes	-0.5	0.92195	[-1, -1, 0, 2, -1, 0, -1, -1, -1, -1]
+exposing	-1.1	0.7	[-2, -2, -1, -1, 0, -2, -1, -1, 0, -1]
+extend	0.7	0.78102	[2, 0, 0, 0, 1, 2, 1, 1, 0, 0]
+extends	0.5	0.80623	[2, 0, 2, 0, 0, 0, 1, 0, 0, 0]
+exuberant	2.8	0.6	[2, 3, 2, 3, 2, 4, 3, 3, 3, 3]
+exultant	3.0	1.18322	[4, 4, 3, 0, 3, 4, 3, 3, 2, 4]
+exultantly	1.4	1.49666	[3, 2, 4, 1, 1, 2, -2, 1, 1, 1]
+fab	2.0	1.0	[2, 1, 1, 3, 1, 2, 2, 4, 3, 1]
+fabulous	2.4	0.8	[2, 2, 3, 4, 3, 3, 1, 2, 2, 2]
+fabulousness	2.8	1.07703	[4, 1, 4, 3, 1, 3, 3, 2, 4, 3]
+fad	0.9	0.83066	[2, 0, 1, 1, 1, 0, 0, 2, 2, 0]
+fag	-2.1	0.83066	[-3, -1, -2, -4, -2, -2, -2, -1, -2, -2]
+faggot	-3.4	0.8	[-2, -4, -4, -3, -2, -4, -4, -4, -3, -4]
+faggots	-3.2	0.9798	[-2, -4, -4, -4, -3, -4, -4, -3, -1, -3]
+fail	-2.5	0.67082	[-2, -3, -3, -3, -4, -2, -2, -2, -2, -2]
+failed	-2.3	0.9	[-2, -3, -1, -2, -2, -1, -3, -3, -4, -2]
+failing	-2.3	1.1	[-2, -3, -3, -3, -4, -1, -2, -2, 0, -3]
+failingly	-1.4	0.8	[-1, -3, -2, -1, 0, -1, -2, -1, -2, -1]
+failings	-2.2	1.07703	[-2, -2, -3, -4, -1, -2, -1, -1, -4, -2]
+faille	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+fails	-1.8	0.74833	[-2, -3, -2, -3, -2, -2, -1, -1, -1, -1]
+failure	-2.3	1.00499	[-3, -1, -3, -2, -1, -2, -3, -1, -4, -3]
+failures	-2.0	0.63246	[-1, -2, -1, -2, -3, -2, -2, -3, -2, -2]
+fainthearted	-0.3	1.34536	[3, -1, -1, -1, -2, -1, 0, 1, -1, 0]
+fair	1.3	1.00499	[0, 1, 1, 2, 4, 1, 1, 1, 1, 1]
+faith	1.8	0.6	[1, 3, 2, 2, 1, 2, 2, 2, 1, 2]
+faithed	1.3	1.00499	[3, 2, 1, 2, 1, 2, -1, 1, 1, 1]
+faithful	1.9	0.83066	[1, 3, 2, 2, 1, 1, 3, 3, 2, 1]
+faithfully	1.8	1.07703	[3, 1, 2, 2, 4, 1, 0, 1, 2, 2]
+faithfulness	1.9	0.53852	[1, 2, 2, 3, 2, 2, 2, 1, 2, 2]
+faithless	-1.0	0.89443	[-1, -1, -1, -2, -2, -1, -1, 0, 1, -2]
+faithlessly	-0.9	1.51327	[-1, -2, -1, -3, -2, -1, 3, 0, -1, -1]
+faithlessness	-1.8	1.249	[-3, -2, 1, -2, -2, -1, -2, -1, -4, -2]
+faiths	1.8	0.9798	[2, 3, 1, 1, 3, 3, 0, 2, 2, 1]
+fake	-2.1	0.9434	[-2, -2, -1, -1, -1, -3, -3, -4, -2, -2]
+fakes	-1.8	1.07703	[-2, -3, -2, -2, -3, 1, -2, -2, -1, -2]
+faking	-1.8	0.87178	[-3, -1, -2, -1, -2, -2, -3, -2, 0, -2]
+fallen	-1.5	0.80623	[-1, -1, -2, -2, -1, -3, 0, -1, -2, -2]
+falling	-0.6	1.8	[-2, -2, -1, 0, -1, 3, -3, 2, 0, -2]
+falsified	-1.6	0.91652	[-4, -1, -1, -2, -1, -1, -2, -2, -1, -1]
+falsify	-2.0	0.7746	[-2, -1, -3, -3, -1, -2, -2, -2, -1, -3]
+fame	1.9	1.13578	[0, 2, 1, 2, 2, 4, 1, 3, 3, 1]
+fan	1.3	0.78102	[2, 0, 1, 1, 2, 1, 1, 3, 1, 1]
+fantastic	2.6	0.91652	[1, 3, 3, 3, 2, 4, 4, 2, 2, 2]
+fantastical	2.0	1.18322	[-1, 3, 2, 2, 2, 2, 3, 1, 3, 3]
+fantasticalities	2.1	1.04403	[2, 4, 2, 2, 1, 1, 2, 4, 1, 2]
+fantasticality	1.7	1.26886	[4, 1, 0, 2, 2, 1, 4, 1, 1, 1]
+fantasticalness	1.3	1.9	[2, 3, -3, 0, 3, 2, 2, 3, -1, 2]
+fantasticate	1.5	1.96214	[1, 2, -3, 1, 4, 1, 3, 4, 0, 2]
+fantastico	0.4	1.49666	[0, 0, 2, 0, 2, -2, 1, -1, -1, 3]
+farce	-1.7	0.45826	[-2, -2, -1, -2, -2, -1, -1, -2, -2, -2]
+fascinate	2.4	1.0198	[4, 2, 2, 3, 1, 2, 3, 4, 1, 2]
+fascinated	2.1	0.83066	[2, 2, 2, 3, 1, 2, 4, 2, 1, 2]
+fascinates	2.0	0.44721	[2, 3, 1, 2, 2, 2, 2, 2, 2, 2]
+fascination	2.2	0.74833	[2, 1, 3, 3, 2, 3, 2, 2, 1, 3]
+fascinating	2.5	0.92195	[3, 3, 3, 4, 2, 3, 2, 3, 1, 1]
+fascist	-2.6	0.8	[-3, -3, -2, -2, -2, -3, -1, -3, -4, -3]
+fascists	-0.8	1.6	[-2, -3, -1, 1, -1, 2, -3, 1, -1, -1]
+fatal	-2.5	1.62788	[-2, -3, -3, -4, -3, -3, 2, -4, -2, -3]
+fatalism	-0.6	1.8	[0, 0, -3, -4, -1, 1, 0, 2, -2, 1]
+fatalisms	-1.7	0.9	[-2, -4, -2, -2, -2, -1, -1, -1, -1, -1]
+fatalist	-0.5	1.56525	[0, 0, -1, -4, -1, 2, 0, 1, -2, 0]
+fatalistic	-1.0	1.34164	[-3, -1, -3, -1, 1, 0, 1, -2, -1, -1]
+fatalists	-1.2	0.87178	[0, -2, -1, -2, -1, 0, -1, -1, -3, -1]
+fatalities	-2.9	0.7	[-2, -3, -3, -4, -2, -2, -3, -4, -3, -3]
+fatality	-3.5	0.67082	[-2, -4, -4, -4, -3, -4, -4, -4, -3, -3]
+fatally	-3.2	0.74833	[-3, -2, -4, -2, -3, -4, -4, -3, -3, -4]
+fatigue	-1.0	0.7746	[-2, -1, -1, -1, 1, -1, -2, -1, -1, -1]
+fatigued	-1.4	0.4899	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -1]
+fatigues	-1.3	1.00499	[-2, -1, -1, -2, -1, 1, -3, -2, -1, -1]
+fatiguing	-1.2	0.6	[-1, -2, -2, -1, 0, -2, -1, -1, -1, -1]
+fatiguingly	-1.5	0.80623	[-1, 0, -3, -2, -1, -1, -2, -1, -2, -2]
+fault	-1.7	0.64031	[-1, -2, -2, -2, -1, -1, -2, -2, -1, -3]
+faulted	-1.4	0.4899	[-2, -2, -1, -2, -1, -1, -1, -1, -2, -1]
+faultfinder	-0.8	1.32665	[-3, -2, -2, -1, 1, 1, 1, -1, -1, -1]
+faultfinders	-1.5	0.80623	[-2, -2, -1, -3, -2, -1, 0, -1, -1, -2]
+faultfinding	-2.1	0.83066	[-3, -2, -1, -2, -1, -3, -1, -3, -2, -3]
+faultier	-2.1	0.7	[-3, -3, -3, -1, -2, -2, -2, -1, -2, -2]
+faultiest	-2.1	0.53852	[-3, -1, -2, -2, -2, -2, -2, -2, -3, -2]
+faultily	-2.0	0.89443	[-2, -2, -2, -3, -2, -1, 0, -3, -2, -3]
+faultiness	-1.5	0.92195	[-1, -1, -3, -1, 0, -2, -3, -1, -2, -1]
+faulting	-1.4	0.4899	[-1, -2, -1, -1, -2, -1, -1, -2, -1, -2]
+faultless	2.0	1.41421	[3, 2, 0, 1, 3, 1, 4, 0, 2, 4]
+faultlessly	2.0	1.09545	[3, 3, 2, 2, 0, 3, 2, 3, 2, 0]
+faultlessness	1.1	2.02237	[3, 2, 4, 2, 1, -1, -2, 1, -2, 3]
+faults	-2.1	0.3	[-2, -2, -2, -2, -2, -2, -3, -2, -2, -2]
+faulty	-1.3	0.45826	[-1, -1, -1, -1, -2, -2, -2, -1, -1, -1]
+fav	2.0	0.63246	[2, 1, 2, 2, 2, 1, 3, 2, 3, 2]
+fave	1.9	1.51327	[1, 3, -2, 3, 2, 3, 1, 3, 2, 3]
+favor	1.7	0.64031	[2, 2, 2, 2, 2, 2, 0, 1, 2, 2]
+favorable	2.1	0.7	[2, 1, 2, 3, 1, 2, 2, 3, 3, 2]
+favorableness	2.2	0.87178	[1, 2, 1, 3, 2, 2, 2, 4, 2, 3]
+favorably	1.6	0.66332	[2, 1, 1, 1, 1, 2, 2, 2, 3, 1]
+favored	1.8	0.6	[2, 2, 1, 1, 3, 1, 2, 2, 2, 2]
+favorer	1.3	1.18743	[2, 2, 1, 1, -2, 1, 2, 2, 2, 2]
+favorers	1.4	0.4899	[2, 2, 1, 2, 1, 2, 1, 1, 1, 1]
+favoring	1.8	0.6	[2, 1, 1, 3, 2, 2, 1, 2, 2, 2]
+favorite	2.0	0.63246	[2, 1, 3, 1, 2, 2, 2, 3, 2, 2]
+favorited	1.7	0.45826	[1, 2, 2, 1, 2, 2, 2, 1, 2, 2]
+favorites	1.8	0.6	[1, 2, 1, 3, 2, 2, 1, 2, 2, 2]
+favoritism	0.7	1.79165	[-1, 3, -1, -1, 2, -2, 2, 2, 3, 0]
+favoritisms	0.7	0.9	[0, 2, -1, 1, 0, 0, 1, 1, 2, 1]
+favors	1.0	0.7746	[2, 1, 1, 1, 2, 1, -1, 1, 1, 1]
+favour	1.9	0.53852	[2, 1, 2, 3, 2, 2, 2, 1, 2, 2]
+favoured	1.8	0.4	[1, 2, 2, 2, 1, 2, 2, 2, 2, 2]
+favourer	1.6	0.4899	[1, 2, 2, 1, 1, 2, 2, 2, 1, 2]
+favourers	1.6	0.66332	[2, 2, 1, 0, 2, 2, 1, 2, 2, 2]
+favouring	1.3	0.45826	[1, 2, 1, 1, 2, 1, 1, 1, 1, 2]
+favours	1.8	0.6	[3, 2, 1, 2, 1, 2, 2, 1, 2, 2]
+fear	-2.2	0.6	[-2, -3, -2, -3, -2, -1, -2, -3, -2, -2]
+feared	-2.2	0.6	[-2, -3, -2, -1, -3, -2, -3, -2, -2, -2]
+fearful	-2.2	0.87178	[-2, -2, -3, -1, -2, -3, -2, -2, -4, -1]
+fearfuller	-2.2	0.87178	[-1, -4, -2, -2, -1, -2, -3, -2, -3, -2]
+fearfullest	-2.5	1.0247	[-3, -3, -4, -4, -3, -2, -1, -2, -2, -1]
+fearfully	-2.2	0.87178	[-2, -2, -2, -1, -1, -3, -4, -2, -3, -2]
+fearfulness	-1.8	0.87178	[-1, -1, -1, -2, -2, -1, -4, -2, -2, -2]
+fearing	-2.7	0.9	[-3, -3, -3, -2, -4, -2, -1, -3, -2, -4]
+fearless	1.9	0.83066	[3, 3, 3, 2, 2, 2, 1, 1, 1, 1]
+fearlessly	1.1	1.22066	[2, -2, 1, 1, 2, 1, 3, 1, 1, 1]
+fearlessness	1.1	1.13578	[3, 2, -1, 2, 0, 2, 1, 1, 1, 0]
+fears	-1.8	0.6	[-2, -2, -3, -2, -2, -1, -1, -2, -1, -2]
+fearsome	-1.7	0.64031	[-3, -1, -1, -2, -1, -2, -2, -2, -1, -2]
+fed up	-1.8	1.249	[-2, -2, -3, -4, -2, -2, -1, -2, -1, 1]
+feeble	-1.2	1.249	[-2, -2, -3, -1, -1, -2, -1, -1, 2, -1]
+feeling	0.5	1.0247	[0, 0, 0, 3, 0, 2, 0, 0, 0, 0]
+felonies	-2.5	0.5	[-3, -3, -3, -2, -2, -2, -2, -3, -2, -3]
+felony	-2.5	1.36015	[-4, -3, -4, -2, -3, -3, -2, -3, -2, 1]
+ferocious	-0.4	1.56205	[1, 1, -2, -3, -1, 2, 1, -2, -1, 0]
+ferociously	-1.1	1.86815	[-3, -4, 2, -2, 0, -2, -1, -1, 2, -2]
+ferociousness	-1.0	1.89737	[2, -4, -2, 0, -2, -3, -1, 0, 2, -2]
+ferocities	-1.0	1.54919	[1, 0, -2, 0, 0, -3, 0, 0, -2, -4]
+ferocity	-0.7	1.67631	[-2, -1, -4, 0, 0, -3, 1, 1, 0, 1]
+fervent	1.1	1.44568	[3, 0, 0, 1, -2, 2, 2, 3, 1, 1]
+fervid	0.5	2.20227	[4, -2, 1, -2, 4, 0, -1, 2, 1, -2]
+festival	2.2	0.6	[2, 2, 3, 2, 3, 2, 2, 2, 3, 1]
+festivalgoer	1.3	1.1	[1, 3, 2, 3, 0, 0, 1, 2, 0, 1]
+festivalgoers	1.2	0.9798	[2, 2, 0, 0, 0, 2, 2, 0, 2, 2]
+festivals	1.5	1.11803	[2, 0, 2, 3, 0, 3, 2, 1, 2, 0]
+festive	2.0	0.63246	[2, 3, 2, 3, 1, 2, 2, 2, 1, 2]
+festively	2.2	0.6	[2, 2, 3, 1, 3, 2, 3, 2, 2, 2]
+festiveness	2.4	0.8	[1, 3, 2, 1, 3, 3, 3, 3, 2, 3]
+festivities	2.1	0.7	[1, 2, 1, 2, 3, 2, 3, 3, 2, 2]
+festivity	2.2	1.07703	[3, 3, 3, 0, 2, 1, 3, 3, 1, 3]
+feud	-1.4	0.66332	[-3, -2, -1, -2, -1, -1, -1, -1, -1, -1]
+feudal	-0.8	0.87178	[-1, -2, -2, 0, 0, 0, -2, -1, 0, 0]
+feudalism	-0.9	1.37477	[-2, -3, -2, -3, 0, 0, 1, 0, 0, 0]
+feudalisms	-0.2	0.74833	[0, 0, 0, 0, 0, 0, -1, 0, -2, 1]
+feudalist	-0.9	1.13578	[-2, -2, -2, -2, 0, 0, 1, 0, 0, -2]
+feudalistic	-1.1	0.7	[0, -1, -1, 0, -2, -1, -2, -1, -2, -1]
+feudalities	-0.4	1.0198	[-1, 0, -1, -2, -1, 0, -1, 0, 0, 2]
+feudality	-0.5	1.28452	[1, -1, 0, -1, 1, 0, -3, -2, 1, -1]
+feudalization	-0.3	1.18743	[-2, -2, 0, 0, 2, 0, -1, -1, 1, 0]
+feudalize	-0.5	0.92195	[-1, 0, -1, 0, -2, 0, 1, 0, 0, -2]
+feudalized	-0.8	1.07703	[-1, -1, -3, 0, 0, 0, 1, -1, -2, -1]
+feudalizes	-0.1	0.53852	[0, 0, -1, 0, -1, 0, 0, 0, 1, 0]
+feudalizing	-0.7	1.34536	[2, -2, -1, 0, 0, -2, -1, -2, 1, -2]
+feudally	-0.6	0.66332	[0, 0, -1, -1, 0, -1, 0, -1, -2, 0]
+feudaries	-0.3	0.9	[0, 0, 0, -2, -2, 0, 0, 0, 0, 1]
+feudary	-0.8	0.74833	[0, 0, -1, -1, -2, 0, -1, 0, -2, -1]
+feudatories	-0.5	0.92195	[-3, 0, -1, 0, 0, 0, 0, -1, 0, 0]
+feudatory	-0.1	0.83066	[-2, 0, 0, 0, 1, 0, 1, -1, 0, 0]
+feuded	-2.2	0.6	[-2, -2, -2, -1, -3, -3, -2, -3, -2, -2]
+feuding	-1.6	0.66332	[-2, -1, -2, -2, -1, -1, -3, -1, -2, -1]
+feudist	-1.1	0.83066	[-2, 0, -3, -1, -1, -1, 0, -1, -1, -1]
+feudists	-0.7	0.9	[0, 0, -1, 0, 0, -2, -2, 0, -2, 0]
+feuds	-1.4	1.0198	[-2, -2, -2, -1, -1, -1, -3, -2, 1, -1]
+fiasco	-2.3	0.64031	[-2, -2, -3, -3, -2, -3, -1, -3, -2, -2]
+fidgety	-1.4	0.66332	[-1, -2, -2, 0, -1, -1, -2, -1, -2, -2]
+fiery	-1.4	0.91652	[0, -1, -1, -2, -2, 0, -3, -1, -2, -2]
+fiesta	2.1	0.7	[3, 2, 1, 2, 2, 1, 3, 3, 2, 2]
+fiestas	1.5	1.0247	[3, 0, 3, 1, 0, 2, 2, 1, 2, 1]
+fight	-1.6	1.56205	[-1, -2, -3, -3, -1, 2, -4, -1, -2, -1]
+fighter	0.6	1.11355	[3, 0, 0, -1, 1, 0, 1, 0, 2, 0]
+fighters	-0.2	1.46969	[-1, 2, -2, 0, 2, 0, -2, -2, 0, 1]
+fighting	-1.5	1.11803	[-1, -2, -3, -2, -2, -2, 0, -3, 0, 0]
+fightings	-1.9	0.53852	[-2, -3, -1, -2, -2, -2, -2, -1, -2, -2]
+fights	-1.7	0.64031	[-2, -2, -1, -2, -2, -1, -3, -1, -1, -2]
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+fired	-2.6	0.91652	[-2, -3, -4, -3, -3, -1, -3, -3, -1, -3]
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+flattered	1.6	2.00998	[2, 3, 3, 1, 2, 3, 3, 1, 2, -4]
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+flattery	0.4	1.49666	[1, -1, -2, 1, 3, -2, 1, 1, 1, 1]
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+flunker	-1.9	1.04403	[-4, -1, -3, -2, -1, -1, -3, -2, -1, -1]
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+freeloads	-1.3	0.9	[-1, -1, -2, -2, -2, 0, 0, -1, -1, -3]
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+freers	1.0	0.89443	[0, 1, 1, 2, 3, 1, 0, 1, 0, 1]
+frees	1.2	0.6	[1, 2, 0, 1, 1, 1, 2, 1, 1, 2]
+freesia	0.4	0.91652	[0, 0, 3, 0, 1, 0, 0, 0, 0, 0]
+freesias	0.4	0.66332	[0, 0, 0, 1, 1, 2, 0, 0, 0, 0]
+freest	1.6	1.28062	[3, 4, 0, 3, 0, 1, 1, 2, 1, 1]
+freestanding	1.1	0.83066	[2, 1, 1, 2, 0, 0, 0, 2, 1, 2]
+freestyle	0.7	0.9	[2, 0, 1, 0, 2, 0, 0, 2, 0, 0]
+freestyler	0.4	0.91652	[0, 0, 0, 0, 1, 0, 0, 0, 0, 3]
+freestylers	0.8	0.87178	[2, 1, 0, 0, 0, 1, 0, 2, 2, 0]
+freestyles	0.3	0.64031	[0, 0, 0, 0, 1, 0, 0, 0, 0, 2]
+freethinker	1.0	0.63246	[1, 2, 1, 1, 2, 1, 0, 0, 1, 1]
+freethinkers	1.0	0.7746	[1, 0, 0, 1, 2, 2, 1, 2, 0, 1]
+freethinking	1.1	0.7	[1, 0, 1, 1, 2, 2, 0, 2, 1, 1]
+freeware	0.7	1.48661	[1, 0, 0, 2, 4, 0, 1, -2, 1, 0]
+freeway	0.2	0.6	[0, 0, 0, 0, 0, 0, 2, 0, 0, 0]
+freewheel	0.5	1.11803	[2, 0, 1, 2, 0, -2, 0, 0, 1, 1]
+freewheeled	0.3	0.78102	[1, 0, 0, 0, 0, 1, 2, -1, 0, 0]
+freewheeler	0.2	0.87178	[-2, 1, 0, 0, 0, 1, 1, 1, 0, 0]
+freewheelers	-0.3	1.00499	[-2, 0, 0, 0, 2, -1, -1, 0, -1, 0]
+freewheeling	0.5	1.11803	[-1, 2, 0, -1, 1, 2, 2, 0, 0, 0]
+freewheelingly	0.8	0.87178	[1, 2, 0, 0, 1, 2, 1, -1, 1, 1]
+freewheels	0.6	0.91652	[0, 3, 1, 1, 1, 0, 0, 0, 0, 0]
+freewill	1.0	0.7746	[1, 1, 1, -1, 1, 1, 1, 2, 2, 1]
+freewriting	0.8	1.07703	[0, 2, 0, 0, 1, 0, 3, 0, 2, 0]
+freeze	0.2	0.9798	[-1, 0, 1, 1, -1, 0, 0, -1, 2, 1]
+freezers	-0.1	0.3	[0, 0, 0, -1, 0, 0, 0, 0, 0, 0]
+freezes	-0.1	1.13578	[0, -2, -2, 1, 0, 0, 0, 0, 2, 0]
+freezing	-0.4	1.28062	[-2, -1, -2, -2, 0, 0, 0, 1, 2, 0]
+freezingly	-1.6	0.4899	[-1, -2, -2, -1, -2, -2, -2, -2, -1, -1]
+frenzy	-1.3	1.48661	[-1, -1, -2, -2, 2, -4, -1, -2, 0, -2]
+fresh	1.3	0.45826	[2, 2, 1, 1, 1, 1, 2, 1, 1, 1]
+friend	2.2	0.6	[2, 2, 3, 2, 3, 3, 1, 2, 2, 2]
+friended	1.7	0.78102	[2, 2, 1, 3, 1, 1, 2, 3, 1, 1]
+friending	1.8	1.07703	[1, 4, 2, 0, 1, 3, 2, 2, 1, 2]
+friendless	-1.5	0.67082	[-1, -2, -2, -1, 0, -2, -1, -2, -2, -2]
+friendlessness	-0.3	2.05183	[-2, -2, 2, 1, -4, -1, 2, 1, -2, 2]
+friendlier	2.0	0.63246	[3, 2, 2, 1, 2, 2, 2, 1, 3, 2]
+friendlies	2.2	0.74833	[3, 2, 2, 3, 2, 2, 1, 3, 1, 3]
+friendliest	2.6	0.91652	[3, 3, 1, 3, 2, 1, 3, 3, 4, 3]
+friendlily	1.8	0.74833	[1, 2, 2, 1, 3, 1, 1, 2, 3, 2]
+friendliness	2.0	0.7746	[3, 1, 3, 2, 2, 3, 2, 1, 2, 1]
+friendly	2.2	0.6	[2, 1, 3, 3, 2, 2, 3, 2, 2, 2]
+friends	2.1	0.53852	[3, 3, 2, 2, 2, 1, 2, 2, 2, 2]
+friendship	1.9	0.53852	[1, 2, 2, 1, 3, 2, 2, 2, 2, 2]
+friendships	1.6	0.91652	[2, 1, 1, 0, 3, 2, 2, 3, 1, 1]
+fright	-1.6	1.35647	[-2, -1, 0, -3, -2, -4, 1, -1, -2, -2]
+frighted	-1.4	0.91652	[0, -1, -1, -1, -2, -1, -3, -1, -1, -3]
+frighten	-1.4	0.8	[0, -1, -1, -1, -2, -1, -3, -2, -1, -2]
+frightened	-1.9	0.7	[-2, -3, -1, -1, -2, -2, -3, -1, -2, -2]
+frightening	-2.2	0.9798	[-1, -1, -4, -3, -3, -3, -2, -2, -1, -2]
+frighteningly	-2.1	0.7	[-2, -2, -2, -2, -4, -2, -1, -2, -2, -2]
+frightens	-1.7	0.78102	[-2, -1, -2, -1, -1, -1, -2, -3, -3, -1]
+frightful	-2.3	0.78102	[-2, -2, -2, -2, -3, -2, -3, -1, -4, -2]
+frightfully	-1.7	0.78102	[-1, -1, -1, -2, -2, -1, -2, -3, -1, -3]
+frightfulness	-1.9	0.7	[-1, -1, -2, -3, -3, -2, -1, -2, -2, -2]
+frighting	-1.5	0.67082	[-1, -2, -2, -3, -1, -1, -1, -1, -2, -1]
+frights	-1.1	0.83066	[-2, 0, -2, 0, -2, -1, 0, -1, -1, -2]
+frisky	1.0	1.48324	[1, -2, 1, 1, 1, 3, 3, 2, -1, 1]
+frowning	-1.4	1.42829	[-1, -1, -1, -3, -3, 1, -2, -3, 1, -2]
+frustrate	-2.0	0.63246	[-2, -3, -2, -1, -3, -2, -2, -1, -2, -2]
+frustrated	-2.4	0.66332	[-2, -1, -3, -3, -2, -2, -3, -2, -3, -3]
+frustrates	-1.9	0.7	[-1, -1, -3, -2, -1, -2, -2, -2, -3, -2]
+frustrating	-1.9	0.83066	[-2, -2, -1, -1, -1, -2, -2, -2, -4, -2]
+frustratingly	-2.0	0.63246	[-1, -3, -2, -2, -2, -2, -2, -3, -2, -1]
+frustration	-2.1	0.7	[-3, -2, -3, -2, -1, -2, -3, -2, -1, -2]
+frustrations	-2.0	0.7746	[-2, -1, -1, -3, -2, -2, -3, -3, -2, -1]
+fuck	-2.5	1.20416	[0, -3, -4, -3, -2, -3, -4, -1, -2, -3]
+fucked	-3.4	0.66332	[-2, -3, -4, -3, -4, -4, -3, -4, -3, -4]
+fucker	-3.3	0.78102	[-3, -4, -4, -2, -3, -4, -4, -2, -4, -3]
+fuckers	-2.9	0.9434	[-3, -3, -4, -3, -4, -4, -2, -1, -2, -3]
+fuckface	-3.2	1.07703	[-4, -2, -4, -1, -4, -4, -2, -4, -3, -4]
+fuckhead	-3.1	1.04403	[-1, -4, -2, -4, -3, -3, -2, -4, -4, -4]
+fucks	-2.1	1.13578	[-3, -2, -1, -1, -1, -2, -4, -2, -4, -1]
+fucktard	-3.1	0.9434	[-4, -4, -4, -3, -4, -2, -4, -2, -2, -2]
+fud	-1.1	1.37477	[-1, -3, -1, -1, -3, -2, 2, 0, -1, -1]
+fuked	-2.5	0.92195	[-2, -3, -3, -3, -3, -3, 0, -3, -3, -2]
+fuking	-3.2	0.9798	[-4, -1, -3, -4, -3, -2, -4, -3, -4, -4]
+fulfill	1.9	1.04403	[1, 1, 2, 4, 1, 1, 2, 1, 3, 3]
+fulfilled	1.8	0.87178	[1, 2, 1, 0, 2, 2, 3, 2, 2, 3]
+fulfills	1.0	1.09545	[2, 1, 1, 1, 1, -2, 2, 2, 1, 1]
+fume	-1.2	1.16619	[0, 0, 0, -2, -3, -2, -1, -3, -1, 0]
+fumed	-1.8	0.87178	[-3, -2, -3, -2, -2, 0, -2, -1, -1, -2]
+fumeless	0.3	0.64031	[0, 0, 0, 1, 0, 0, 0, 2, 0, 0]
+fumelike	-0.7	1.18743	[0, 0, -3, 0, 0, -2, -1, -2, 1, 0]
+fumer	0.7	0.9	[2, 1, 0, 1, 0, 2, 0, -1, 1, 1]
+fumers	-0.8	0.6	[0, -1, -1, -2, -1, 0, 0, -1, -1, -1]
+fumes	-0.1	1.13578	[0, -2, 0, 0, -1, 1, -1, -1, 1, 2]
+fumet	0.4	1.0198	[2, 0, 0, -1, 0, 1, -1, 0, 2, 1]
+fumets	-0.4	0.66332	[0, -1, 0, -1, 0, 0, -2, 0, 0, 0]
+fumette	-0.6	1.11355	[-2, -2, 0, -1, -1, 2, 0, 0, -1, -1]
+fuming	-2.7	0.64031	[-2, -3, -3, -2, -3, -4, -3, -2, -2, -3]
+fun	2.3	0.45826	[2, 3, 2, 3, 2, 2, 3, 2, 2, 2]
+funeral	-1.5	1.74642	[-2, -3, -2, -1, -3, -1, -4, 1, 2, -2]
+funerals	-1.6	2.2891	[-3, -4, -1, -4, 2, -3, -3, 2, 1, -3]
+funky	-0.4	1.62481	[0, -1, 2, -1, 2, 0, -4, -1, 0, -1]
+funned	2.3	0.9	[2, 3, 3, 4, 1, 2, 2, 2, 3, 1]
+funnel	0.1	0.53852	[1, 0, 0, 0, 0, -1, 0, 0, 1, 0]
+funneled	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
+funnelform	0.5	0.80623	[0, 0, 1, 0, 0, 0, 0, 2, 2, 0]
+funneling	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+funnelled	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+funnelling	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+funnels	0.4	0.66332	[0, 0, 0, 1, 0, 0, 0, 0, 2, 1]
+funner	2.2	0.74833	[2, 2, 3, 4, 1, 2, 2, 2, 2, 2]
+funnest	2.9	0.7	[4, 3, 4, 3, 2, 3, 2, 3, 2, 3]
+funnier	1.7	1.00499	[2, 2, -1, 2, 2, 2, 3, 1, 2, 2]
+funnies	1.3	1.00499	[2, 1, -1, 2, 1, 2, 3, 1, 1, 1]
+funniest	2.6	0.8	[3, 3, 3, 3, 2, 2, 1, 2, 4, 3]
+funnily	1.9	0.53852	[2, 3, 1, 2, 2, 2, 2, 1, 2, 2]
+funniness	1.8	0.9798	[3, 2, 3, 2, 2, 1, 3, 0, 1, 1]
+funninesses	1.6	0.91652	[1, 3, 0, 3, 1, 2, 1, 2, 2, 1]
+funning	1.8	0.9798	[2, 2, 1, 2, 1, 4, 0, 2, 2, 2]
+funny	1.9	0.53852	[3, 2, 2, 1, 2, 2, 1, 2, 2, 2]
+funnyman	1.4	0.4899	[2, 2, 1, 2, 1, 1, 1, 1, 2, 1]
+funnymen	1.3	1.1	[2, 1, 1, 0, 0, 3, 3, 1, 2, 0]
+furious	-2.7	1.41774	[-3, -3, -3, -4, -4, -4, 1, -2, -3, -2]
+furiously	-1.9	1.04403	[-2, -2, -4, -2, -1, -2, -1, -3, 0, -2]
+fury	-2.7	0.78102	[-4, -3, -2, -2, -2, -3, -4, -2, -3, -2]
+futile	-1.9	0.83066	[0, -3, -2, -2, -2, -2, -3, -1, -2, -2]
+gag	-1.4	1.0198	[-2, -2, -1, -2, 0, -2, -3, 0, 0, -2]
+gagged	-1.3	1.55242	[-2, -2, -1, -2, 2, -3, -1, -3, 1, -2]
+gain	2.4	0.4899	[2, 3, 2, 2, 3, 2, 3, 2, 3, 2]
+gained	1.6	0.66332	[2, 1, 2, 1, 1, 3, 2, 1, 2, 1]
+gaining	1.8	0.4	[1, 2, 2, 2, 1, 2, 2, 2, 2, 2]
+gains	1.4	0.4899	[1, 2, 1, 2, 2, 2, 1, 1, 1, 1]
+gallant	1.7	1.1	[4, 0, 3, 1, 1, 2, 2, 2, 1, 1]
+gallantly	1.9	0.53852	[2, 2, 3, 2, 2, 2, 2, 1, 2, 1]
+gallantry	2.6	0.8	[3, 3, 1, 2, 2, 3, 4, 2, 3, 3]
+geek	-0.8	0.9798	[0, 0, 0, -2, -3, -1, -1, 0, 0, -1]
+geekier	0.2	1.4	[0, 3, -1, -1, -1, 1, 2, 1, -1, -1]
+geekiest	-0.1	0.9434	[1, -1, -1, -1, -1, 1, 1, 1, 0, -1]
+geeks	-0.4	0.91652	[0, 0, -1, 0, 0, 0, 0, 0, -3, 0]
+geeky	-0.6	0.91652	[0, 0, -1, 0, -1, 0, -1, 0, -3, 0]
+generosities	2.6	0.4899	[3, 3, 2, 3, 2, 3, 2, 3, 2, 3]
+generosity	2.3	0.64031	[3, 1, 2, 2, 3, 2, 3, 3, 2, 2]
+generous	2.3	0.78102	[3, 2, 4, 2, 2, 1, 2, 3, 2, 2]
+generously	1.8	0.74833	[3, 3, 2, 1, 2, 1, 1, 2, 1, 2]
+generousness	2.4	0.91652	[3, 2, 3, 1, 3, 4, 3, 2, 2, 1]
+genial	1.8	0.6	[3, 1, 2, 1, 2, 2, 1, 2, 2, 2]
+gentle	1.9	0.53852	[2, 2, 2, 1, 2, 3, 2, 2, 1, 2]
+gentler	1.4	0.4899	[2, 1, 1, 1, 1, 2, 2, 1, 2, 1]
+gentlest	1.8	0.4	[2, 1, 2, 2, 2, 1, 2, 2, 2, 2]
+gently	2.0	0.7746	[2, 2, 2, 1, 1, 3, 3, 2, 1, 3]
+ghost	-1.3	1.34536	[-2, 0, 0, 0, 0, -3, -2, -3, 0, -3]
+giddy	-0.6	1.62481	[-2, -2, 3, -1, -1, -1, -1, -2, 2, -1]
+gift	1.9	0.53852	[2, 1, 2, 2, 2, 1, 2, 3, 2, 2]
+giggle	1.8	0.9798	[2, 2, 2, 2, 2, 3, 2, -1, 2, 2]
+giggled	1.5	1.20416	[1, 3, 1, 3, 3, 1, 1, -1, 2, 1]
+giggler	0.6	0.8	[1, 1, 1, 1, -1, 1, 1, 1, -1, 1]
+gigglers	1.4	0.4899	[1, 2, 2, 1, 2, 1, 1, 1, 1, 2]
+giggles	0.8	1.249	[1, 2, 2, 1, -1, 1, 1, 2, -2, 1]
+gigglier	1.0	1.09545	[2, 1, 1, 2, 2, 1, -1, 2, 1, -1]
+giggliest	1.7	1.26886	[4, 2, 1, 2, 1, 3, 2, 2, -1, 1]
+giggling	1.5	0.5	[2, 2, 1, 2, 2, 1, 1, 1, 1, 2]
+gigglingly	1.1	1.37477	[1, 2, 1, 1, -1, 2, 1, -1, 4, 1]
+giggly	1.0	1.41421	[1, 2, -2, 1, 2, 3, 1, -1, 2, 1]
+giver	1.4	0.66332	[1, 2, 2, 0, 1, 2, 1, 2, 1, 2]
+givers	1.7	1.34536	[2, -1, 3, 3, 3, 1, 1, 2, 0, 3]
+giving	1.4	1.0198	[1, 1, 3, 1, 1, 2, 3, 0, 2, 0]
+glad	2.0	0.63246	[3, 2, 1, 2, 2, 2, 1, 3, 2, 2]
+gladly	1.4	0.4899	[2, 2, 1, 2, 1, 1, 2, 1, 1, 1]
+glamor	2.1	0.9434	[1, 2, 2, 2, 1, 3, 2, 4, 3, 1]
+glamorise	1.3	1.1	[0, 1, 4, 1, 0, 2, 1, 2, 1, 1]
+glamorised	1.8	0.74833	[1, 2, 2, 2, 2, 2, 0, 2, 3, 2]
+glamorises	2.1	1.04403	[1, 3, 2, 4, 2, 2, 0, 2, 3, 2]
+glamorising	1.2	1.16619	[3, 2, 0, 3, 1, 2, 0, 1, 0, 0]
+glamorization	1.6	0.91652	[2, 2, 3, 0, 3, 1, 2, 1, 1, 1]
+glamorize	1.7	1.1	[1, 2, 1, 4, 2, 0, 3, 1, 2, 1]
+glamorized	2.1	1.04403	[3, 2, 1, 2, 4, 2, 2, 0, 3, 2]
+glamorizer	2.4	1.0198	[3, 2, 2, 3, 4, 3, 2, 0, 3, 2]
+glamorizers	1.6	1.11355	[4, 1, 1, 1, 1, 2, 0, 2, 3, 1]
+glamorizes	2.4	1.2	[3, 2, 2, 4, 4, 1, 2, 0, 3, 3]
+glamorizing	1.8	1.16619	[3, 0, 1, 2, 3, 2, 1, 0, 3, 3]
+glamorous	2.3	0.78102	[3, 2, 4, 2, 2, 2, 3, 2, 2, 1]
+glamorously	2.1	1.04403	[1, 3, 2, 1, 2, 1, 4, 1, 3, 3]
+glamors	1.4	0.66332	[1, 1, 2, 2, 2, 1, 2, 2, 0, 1]
+glamour	2.4	0.91652	[2, 4, 2, 1, 3, 2, 2, 2, 2, 4]
+glamourize	0.8	1.32665	[2, 1, 0, 1, 0, 4, 0, 0, -1, 1]
+glamourless	-1.6	1.49666	[-4, -1, -1, -2, -2, -3, -2, -1, 2, -2]
+glamourous	2.0	0.7746	[1, 3, 3, 2, 1, 2, 2, 2, 3, 1]
+glamours	1.9	0.83066	[1, 3, 2, 2, 3, 2, 1, 1, 3, 1]
+glee	3.2	0.4	[3, 4, 3, 3, 4, 3, 3, 3, 3, 3]
+gleeful	2.9	0.53852	[3, 3, 3, 3, 3, 4, 2, 2, 3, 3]
+gloom	-2.6	0.66332	[-4, -2, -3, -3, -2, -3, -2, -2, -2, -3]
+gloomed	-1.9	0.7	[-1, -2, -3, -1, -2, -2, -1, -2, -3, -2]
+gloomful	-2.1	0.9434	[-3, -1, -4, -2, -1, -1, -2, -3, -2, -2]
+gloomier	-1.5	1.20416	[-3, -2, -2, -3, -1, -2, 0, 1, -1, -2]
+gloomiest	-1.8	2.03961	[-2, -2, 2, -4, -2, -3, -4, -3, 2, -2]
+gloominess	-1.8	0.6	[-2, -1, -2, -3, -2, -1, -2, -2, -2, -1]
+gloominesses	-1.0	1.09545	[-1, -2, -2, -1, -1, -2, 2, -1, -1, -1]
+glooming	-1.8	0.74833	[-1, -2, -2, -1, -2, -1, -3, -1, -3, -2]
+glooms	-0.9	1.57797	[3, -2, -1, -2, -2, -2, 1, -2, -1, -1]
+gloomy	-0.6	1.56205	[2, -1, -2, -2, -2, -1, 1, -2, 2, -1]
+gloried	2.4	1.0198	[2, 3, 3, 4, 4, 1, 1, 2, 2, 2]
+glories	2.1	1.3	[4, 1, 4, 1, 1, 4, 2, 2, 1, 1]
+glorification	2.0	0.89443	[3, 1, 3, 2, 3, 1, 1, 3, 2, 1]
+glorified	2.3	0.9	[1, 4, 2, 2, 4, 2, 2, 2, 2, 2]
+glorifier	2.3	1.00499	[1, 4, 1, 2, 4, 2, 3, 2, 2, 2]
+glorifiers	1.6	1.0198	[2, 1, 2, -1, 2, 2, 2, 1, 2, 3]
+glorifies	2.2	0.9798	[1, 4, 2, 2, 4, 2, 1, 2, 2, 2]
+glorify	2.7	0.78102	[3, 3, 4, 3, 1, 3, 2, 3, 2, 3]
+glorifying	2.4	1.28062	[3, 4, 2, 2, 4, 4, 0, 1, 2, 2]
+gloriole	1.5	1.36015	[2, 4, 1, 2, 0, -1, 1, 3, 2, 1]
+glorioles	1.2	0.87178	[0, 2, 0, 2, 0, 1, 2, 2, 1, 2]
+glorious	3.2	0.6	[4, 3, 3, 2, 3, 3, 3, 4, 3, 4]
+gloriously	2.9	0.83066	[3, 4, 3, 2, 4, 2, 2, 2, 4, 3]
+gloriousness	2.6	1.0198	[3, 2, 3, 4, 3, 2, 1, 4, 3, 1]
+glory	2.5	0.80623	[1, 3, 3, 1, 3, 3, 3, 2, 3, 3]
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+gn8	0.6	0.66332	[1, 1, 0, 0, 0, 0, 2, 1, 0, 1]
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+goddammed	-2.4	0.91652	[-2, -3, -1, -1, -2, -2, -4, -3, -3, -3]
+goddamn	-2.1	1.75784	[-3, -3, -2, -4, -4, -3, -3, -1, 1, 1]
+goddamned	-1.8	2.03961	[-3, -3, -3, -4, -1, 2, -2, -3, 2, -3]
+goddamns	-2.1	1.51327	[-3, -2, -4, 2, -2, -3, -3, -2, -2, -2]
+goddams	-1.9	1.92094	[-3, -3, -2, -4, -4, -2, -3, -1, 2, 1]
+godsend	2.8	0.87178	[2, 3, 3, 2, 4, 3, 3, 1, 4, 3]
+good	1.9	0.9434	[2, 1, 1, 3, 2, 4, 2, 2, 1, 1]
+goodness	2.0	1.54919	[2, 2, 2, 3, 1, 2, -2, 4, 3, 3]
+gorgeous	3.0	0.63246	[3, 3, 2, 3, 3, 3, 4, 4, 3, 2]
+gorgeously	2.3	0.78102	[2, 2, 2, 3, 1, 2, 4, 3, 2, 2]
+gorgeousness	2.9	0.9434	[3, 4, 3, 1, 4, 4, 2, 2, 3, 3]
+gorgeousnesses	2.1	0.7	[3, 2, 1, 3, 2, 2, 1, 2, 3, 2]
+gossip	-0.7	0.45826	[-1, -1, -1, 0, 0, -1, -1, 0, -1, -1]
+gossiped	-1.1	0.53852	[-1, -1, -1, -1, -1, -1, 0, -1, -2, -2]
+gossiper	-1.1	0.7	[-1, -1, -1, 0, -2, -1, -1, -2, 0, -2]
+gossipers	-1.1	0.53852	[-1, 0, -1, -1, -1, -1, -1, -1, -2, -2]
+gossiping	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -1, -2, -2]
+gossipmonger	-1.0	1.41421	[-1, -2, 1, -3, -2, 1, -1, -2, -2, 1]
+gossipmongers	-1.4	0.66332	[-2, -1, -1, -1, -2, -2, -1, 0, -2, -2]
+gossipped	-1.3	0.9	[-2, -2, -1, -2, -1, -1, -2, -1, 1, -2]
+gossipping	-1.8	0.6	[-2, -1, -2, -2, -1, -2, -2, -1, -3, -2]
+gossipries	-0.8	0.6	[-1, -1, -1, 0, -1, 0, -1, 0, -2, -1]
+gossipry	-1.2	1.16619	[1, 0, -1, -2, -1, -1, -1, -3, -3, -1]
+gossips	-1.3	0.64031	[-1, -2, -1, -1, -2, -1, 0, -1, -2, -2]
+gossipy	-1.3	0.78102	[-1, -2, -2, -1, -2, -1, 0, 0, -2, -2]
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+graced	0.9	1.04403	[1, 1, 2, -2, 1, 1, 1, 2, 1, 1]
+graceful	2.0	0.63246	[2, 1, 2, 2, 2, 3, 3, 2, 2, 1]
+gracefuller	2.2	0.74833	[2, 3, 2, 2, 1, 2, 3, 1, 3, 3]
+gracefullest	2.8	0.74833	[3, 3, 3, 3, 1, 3, 3, 3, 4, 2]
+gracefully	2.4	0.66332	[3, 3, 2, 1, 3, 2, 2, 2, 3, 3]
+gracefulness	2.2	0.6	[3, 2, 1, 2, 2, 2, 3, 2, 2, 3]
+graces	1.6	0.4899	[2, 2, 2, 1, 1, 2, 1, 2, 1, 2]
+gracile	1.7	0.78102	[1, 3, 2, 1, 2, 3, 2, 1, 1, 1]
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+gracilis	0.4	0.66332	[0, 0, 0, 0, 0, 1, 0, 1, 0, 2]
+gracility	1.2	0.87178	[1, 1, 0, 1, 1, 3, 2, 2, 0, 1]
+gracing	1.3	0.9	[1, 0, 3, 2, 1, 2, 0, 1, 2, 1]
+gracioso	1.0	0.63246	[2, 2, 1, 1, 1, 1, 0, 1, 0, 1]
+gracious	2.6	0.8	[2, 2, 3, 3, 3, 3, 2, 4, 1, 3]
+graciously	2.3	0.9	[2, 4, 1, 3, 3, 2, 1, 2, 3, 2]
+graciousness	2.4	0.66332	[2, 2, 2, 2, 2, 3, 4, 3, 2, 2]
+grand	2.0	0.63246	[2, 2, 3, 1, 2, 2, 2, 2, 3, 1]
+grandee	1.1	0.83066	[0, 1, 1, 0, 1, 1, 2, 1, 3, 1]
+grandees	1.2	0.87178	[0, 2, 2, 1, 0, 1, 0, 2, 2, 2]
+grander	1.7	0.9	[3, 1, 1, 2, 2, 2, 0, 2, 3, 1]
+grandest	2.4	1.2	[3, 3, 1, 2, 2, 0, 4, 2, 4, 3]
+grandeur	2.4	1.11355	[3, 2, 3, 2, 4, 1, 1, 4, 1, 3]
+grandeurs	2.1	1.3	[2, 2, 1, 0, 0, 4, 3, 3, 3, 3]
+grant	1.5	0.80623	[2, 2, 1, 0, 3, 1, 1, 1, 2, 2]
+granted	1.0	1.09545	[3, 0, 0, 0, 0, 1, 2, 2, 2, 0]
+granting	1.3	0.45826	[2, 1, 1, 2, 1, 2, 1, 1, 1, 1]
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+grateful	2.0	0.63246	[2, 3, 1, 2, 2, 2, 3, 1, 2, 2]
+gratefuller	1.8	0.87178	[2, 3, 0, 3, 2, 1, 1, 2, 2, 2]
+gratefully	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 3, 1, 2]
+gratefulness	2.2	0.6	[2, 3, 2, 1, 2, 2, 3, 2, 3, 2]
+graticule	0.1	0.3	[0, 0, 0, 1, 0, 0, 0, 0, 0, 0]
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+gratifications	1.8	0.4	[2, 2, 1, 2, 2, 1, 2, 2, 2, 2]
+gratified	1.6	0.91652	[3, 1, 1, 1, 3, 1, 1, 1, 1, 3]
+gratifies	1.5	0.80623	[3, 1, 1, 1, 2, 1, 1, 1, 1, 3]
+gratify	1.3	1.00499	[2, -1, 1, 3, 1, 1, 1, 1, 2, 2]
+gratifying	2.3	0.45826	[2, 3, 2, 2, 2, 2, 3, 2, 2, 3]
+gratifyingly	2.0	0.63246	[2, 2, 2, 1, 3, 2, 1, 3, 2, 2]
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+grating	-0.4	0.4899	[-1, -1, -1, 0, 0, -1, 0, 0, 0, 0]
+gratingly	-0.2	1.6	[1, -3, -2, -2, 0, 2, 1, -1, 1, 1]
+gratings	-0.8	0.9798	[0, -2, -1, -1, 0, 0, -3, 0, 0, -1]
+gratins	0.2	0.6	[0, 0, 0, 0, 0, 0, 0, 0, 2, 0]
+gratis	0.2	0.9798	[-2, 1, 1, 0, 0, 0, -1, 1, 1, 1]
+gratitude	2.3	0.64031	[2, 2, 3, 1, 2, 3, 2, 3, 3, 2]
+gratz	2.0	0.89443	[2, 3, 2, 1, 1, 1, 2, 2, 4, 2]
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+graved	-0.9	1.13578	[0, 0, -1, 0, -1, -1, -1, -1, -4, 0]
+gravel	-0.5	0.5	[0, -1, 0, -1, -1, -1, -1, 0, 0, 0]
+graveled	-0.5	0.80623	[0, 0, 0, 0, -1, -2, 0, 0, -2, 0]
+graveless	-1.3	1.34536	[-2, -2, 0, -1, 0, -2, -4, 1, -1, -2]
+graveling	-0.4	1.28062	[-3, 0, -2, 0, 2, -1, 0, 0, 0, 0]
+gravelled	-0.9	0.53852	[0, -1, -1, -2, 0, -1, -1, -1, -1, -1]
+gravelling	-0.4	1.11355	[0, -1, -2, -2, 0, -1, 0, 0, 2, 0]
+gravelly	-0.9	0.7	[0, -2, -1, -1, 0, -1, -1, 0, -1, -2]
+gravels	-0.5	0.80623	[0, -1, 0, 0, 0, -2, 0, 0, 0, -2]
+gravely	-1.5	1.0247	[0, -3, -1, 0, -3, -2, -1, -1, -2, -2]
+graven	-0.9	1.22066	[0, 0, -1, 0, -2, -1, -1, 0, -4, 0]
+graveness	-1.5	0.67082	[-1, -2, -2, -3, -2, -1, -1, -1, -1, -1]
+graver	-1.1	1.22066	[0, -2, -1, 0, 0, -2, -1, 0, -4, -1]
+gravers	-1.2	1.6	[-4, 0, -2, 0, -2, -2, -2, 0, 2, -2]
+graves	-1.2	1.07703	[0, 0, -1, -1, -2, -1, -1, -1, -4, -1]
+graveside	-0.8	0.6	[-1, -1, -1, 0, 0, 0, -1, -2, -1, -1]
+gravesides	-1.6	1.2	[-2, -1, 0, -3, -1, 0, -1, -2, -2, -4]
+gravest	-1.3	1.9	[-3, -1, -2, -2, 1, 1, -2, 2, -3, -4]
+gravestone	-0.7	0.78102	[0, -1, 0, -1, -1, -2, 0, 0, -2, 0]
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+graveyard	-1.2	0.87178	[0, 0, -1, -2, -1, -1, -2, -1, -3, -1]
+graveyards	-1.2	0.87178	[0, -1, -3, -1, -1, -2, 0, -1, -2, -1]
+great	3.1	0.7	[2, 4, 4, 4, 3, 3, 3, 3, 2, 3]
+greater	1.5	0.67082	[2, 1, 2, 1, 2, 2, 2, 1, 0, 2]
+greatest	3.2	0.74833	[3, 4, 3, 3, 3, 4, 4, 2, 2, 4]
+greed	-1.7	1.61555	[-2, -1, -2, -1, -2, -4, -1, 2, -4, -2]
+greedier	-2.0	0.63246	[-2, -2, -2, -2, -2, -3, -2, -1, -1, -3]
+greediest	-2.8	0.87178	[-3, -4, -3, -2, -2, -4, -4, -2, -2, -2]
+greedily	-1.9	1.22066	[-2, -1, -3, -3, -3, -2, -1, -2, 1, -3]
+greediness	-1.7	1.00499	[-2, -1, -2, -1, -2, -4, -1, 0, -2, -2]
+greeds	-1.0	1.18322	[-1, -2, -2, -2, -2, -2, 1, 0, -1, 1]
+greedy	-1.3	1.48661	[-2, -2, -2, -2, -3, -2, 2, -1, -2, 1]
+greenwash	-1.8	1.4	[-1, 0, -2, -2, -3, -4, 0, 0, -3, -3]
+greenwashing	-0.4	0.91652	[-1, 0, 0, 1, 1, -2, -1, -1, 0, -1]
+greet	1.3	0.64031	[1, 1, 1, 1, 0, 2, 2, 2, 2, 1]
+greeted	1.1	0.9434	[2, 0, 0, 1, 1, 1, 0, 2, 1, 3]
+greeting	1.6	0.4899	[2, 1, 2, 2, 1, 2, 2, 1, 1, 2]
+greetings	1.8	1.07703	[1, 2, 3, 3, 1, 1, 1, 4, 1, 1]
+greets	0.6	0.66332	[0, 0, 2, 0, 1, 1, 0, 1, 1, 0]
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+grief	-2.2	0.6	[-2, -1, -3, -2, -3, -3, -2, -2, -2, -2]
+grievance	-2.1	0.53852	[-2, -2, -3, -2, -2, -3, -2, -1, -2, -2]
+grievances	-1.5	0.5	[-2, -2, -1, -1, -2, -1, -1, -2, -2, -1]
+grievant	-0.8	1.249	[-2, 1, -1, -2, -1, 2, -2, -1, -1, -1]
+grievants	-1.1	0.83066	[-1, -1, -1, -1, -1, -1, 0, -2, 0, -3]
+grieve	-1.6	1.49666	[-2, -3, -1, -3, 1, -3, -1, -2, 1, -3]
+grieved	-2.0	0.89443	[-3, -3, -3, -2, -2, -3, -1, -1, -1, -1]
+griever	-1.9	0.83066	[-2, -2, -3, -2, -3, -3, -1, -1, -1, -1]
+grievers	-0.3	1.55242	[-1, 2, -2, -1, 1, -2, 2, -2, 1, -1]
+grieves	-2.1	0.9434	[-3, -3, -3, -2, -3, -3, -1, -1, -1, -1]
+grieving	-2.3	1.1	[-2, -4, -2, -3, -3, 0, -3, -2, -1, -3]
+grievous	-2.0	1.84391	[-3, -4, -2, -3, -1, 3, -2, -3, -2, -3]
+grievously	-1.7	1.55242	[-3, -1, -4, -2, -2, 1, -3, 1, -2, -2]
+grievousness	-2.7	0.78102	[-3, -3, -3, -2, -3, -4, -2, -1, -3, -3]
+grim	-2.7	0.64031	[-2, -4, -3, -3, -2, -2, -3, -3, -2, -3]
+grimace	-1.0	2.14476	[-4, -3, -2, -2, 2, -1, -1, -3, 2, 2]
+grimaced	-2.0	0.63246	[-2, -3, -2, -2, -2, -2, -1, -3, -1, -2]
+grimaces	-1.8	0.74833	[-1, -2, -1, -2, -2, -1, -3, -3, -1, -2]
+grimacing	-1.4	1.56205	[-3, -2, -3, -3, -1, -1, 1, 0, 1, -3]
+grimalkin	-0.9	1.04403	[-1, -2, -1, 1, -2, -2, -1, -1, 1, -1]
+grimalkins	-0.9	0.9434	[0, 0, 0, -2, -1, -1, -1, 0, -3, -1]
+grime	-1.5	0.92195	[-1, -2, -1, -1, -1, -3, 0, -2, -1, -3]
+grimed	-1.2	0.74833	[-2, -2, 0, -2, -1, -1, -1, -2, -1, 0]
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+grimier	-1.6	1.0198	[-1, -2, -2, -2, -1, 0, -4, -1, -1, -2]
+grimiest	-0.7	2.05183	[-2, -3, 1, -3, 2, -2, -2, -2, 2, 2]
+grimily	-0.7	1.61555	[-2, -1, -1, -2, -2, 2, -2, 2, 1, -2]
+griminess	-1.6	0.4899	[-1, -2, -2, -2, -1, -2, -2, -1, -1, -2]
+griming	-0.7	1.55242	[-3, -1, -1, -2, 0, 2, -1, -2, -1, 2]
+grimly	-1.3	1.55242	[-2, -1, 2, -2, -2, -1, -3, -3, 1, -2]
+grimmer	-1.5	1.36015	[1, -2, -3, 1, -2, -1, -2, -2, -3, -2]
+grimmest	-0.8	1.72047	[-2, -1, -3, 0, -2, -1, 0, 2, 2, -3]
+grimness	-0.8	1.98997	[2, -2, -3, -2, -3, 2, -1, 1, 1, -3]
+grimy	-1.8	0.87178	[-2, -2, -2, -1, -1, -3, 0, -2, -2, -3]
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+grinned	1.1	0.9434	[1, 1, 2, 1, 3, 1, -1, 1, 1, 1]
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+grinning	1.5	1.0247	[3, 2, 2, 1, 1, -1, 1, 2, 2, 2]
+grins	0.9	1.92094	[1, 4, -3, 1, 2, 1, 2, -2, 2, 1]
+gross	-2.1	1.51327	[-1, -3, -2, -3, -3, -3, -3, 2, -2, -3]
+grossed	-0.4	1.11355	[-1, -2, -1, -2, 0, 0, 1, 1, 1, -1]
+grosser	-0.3	1.41774	[1, -2, -1, -2, 0, -1, 1, 2, 1, -2]
+grosses	-0.8	1.77764	[-2, -2, 3, -2, -3, -1, 1, -1, 1, -2]
+grossest	-2.1	0.83066	[-2, -1, -2, -3, -3, -1, -3, -3, -1, -2]
+grossing	-0.3	1.79165	[-1, -3, -1, 1, 0, -1, -3, 1, 1, 3]
+grossly	-0.9	1.44568	[1, -2, 0, -3, -1, -2, 1, 1, -2, -2]
+grossness	-1.8	0.6	[-2, -2, -1, -1, -1, -3, -2, -2, -2, -2]
+grossular	-0.3	1.34536	[0, -2, 0, -1, -2, -1, 0, 0, 0, 3]
+grossularite	-0.1	1.13578	[2, 0, 0, 0, 0, -3, 0, 0, 0, 0]
+grossularites	-0.7	1.26886	[0, -4, -1, -2, 0, 0, 0, 0, 0, 0]
+grossulars	-0.3	0.45826	[0, 0, 0, 0, -1, -1, 0, 0, 0, -1]
+grouch	-2.2	0.87178	[-2, -3, -3, -3, -2, -1, -3, -1, -1, -3]
+grouched	-0.8	0.9798	[-2, -1, -2, -2, 1, -1, 0, 0, 0, -1]
+grouches	-0.9	1.13578	[-2, -1, -2, -1, -1, -1, -1, 2, 0, -2]
+grouchier	-2.0	0.63246	[-2, -3, -3, -2, -2, -2, -2, -1, -2, -1]
+grouchiest	-2.3	0.78102	[-3, -3, -2, -2, -1, -3, -1, -3, -3, -2]
+grouchily	-1.4	1.56205	[-2, -1, -2, -3, -3, 2, -2, -2, 1, -2]
+grouchiness	-2.0	0.7746	[-2, -2, -3, -2, -3, -2, -2, 0, -2, -2]
+grouching	-1.7	1.1	[-1, -3, -2, 1, -2, -3, -2, -1, -2, -2]
+grouchy	-1.9	0.7	[-1, -3, -2, -2, -1, -3, -1, -2, -2, -2]
+growing	0.7	0.64031	[0, 1, 1, 2, 1, 0, 0, 1, 1, 0]
+growth	1.6	1.0198	[2, 0, 3, 0, 2, 3, 1, 1, 2, 2]
+guarantee	1.0	1.0	[2, 3, 1, 0, 2, 0, 1, 0, 0, 1]
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+guiltier	-2.0	0.63246	[-2, -1, -3, -1, -3, -2, -2, -2, -2, -2]
+guiltiest	-1.7	1.79165	[-3, -2, -2, -4, -1, -2, 3, -1, -3, -2]
+guiltily	-1.1	1.57797	[-3, -1, -1, -2, 0, -2, 3, -2, -1, -2]
+guiltiness	-1.8	0.6	[-2, -2, -1, -2, -1, -1, -2, -2, -3, -2]
+guiltless	0.8	1.53623	[3, 2, 1, 2, -2, 1, 1, -2, 1, 1]
+guiltlessly	0.7	1.18743	[-1, 1, -2, 2, 1, 1, 1, 1, 2, 1]
+guiltlessness	0.6	1.42829	[1, 1, -1, -1, -1, 1, 2, 3, -1, 2]
+guilts	-1.4	0.66332	[-1, -2, -1, -1, -3, -1, -1, -2, -1, -1]
+guilty	-1.8	0.6	[-1, -2, -2, -3, -2, -2, -1, -2, -2, -1]
+gullibility	-1.6	0.66332	[-1, -1, -2, -2, -1, -2, -1, -2, -1, -3]
+gullible	-1.5	0.67082	[-1, -2, -2, -1, -1, -3, -2, -1, -1, -1]
+gun	-1.4	1.49666	[0, -4, 0, -3, 0, -3, -2, 0, -2, 0]
+h8	-2.7	1.00499	[-4, -3, -4, -1, -1, -3, -3, -3, -2, -3]
+ha	1.4	0.8	[1, 0, 1, 1, 3, 2, 2, 1, 2, 1]
+hacked	-1.7	1.00499	[-2, -1, -2, -4, 0, -2, -2, -1, -1, -2]
+haha	2.0	0.89443	[1, 1, 2, 3, 2, 1, 4, 2, 2, 2]
+hahaha	2.6	1.0198	[2, 4, 2, 4, 1, 2, 3, 4, 2, 2]
+hahas	1.8	0.9798	[1, 2, 2, 4, 3, 2, 1, 1, 1, 1]
+hail	0.3	0.9	[0, 0, 0, 2, 0, 0, 2, 0, -1, 0]
+hailed	0.9	0.83066	[1, 2, 1, 1, 0, 0, 0, 2, 2, 0]
+hallelujah	3.0	0.7746	[3, 4, 3, 1, 3, 3, 3, 3, 3, 4]
+handsome	2.2	0.74833	[2, 2, 2, 2, 2, 3, 4, 1, 2, 2]
+handsomely	1.9	0.7	[1, 3, 1, 1, 2, 2, 2, 2, 2, 3]
+handsomeness	2.4	1.28062	[2, 4, 1, 4, 0, 2, 4, 3, 2, 2]
+handsomer	2.0	0.63246	[2, 3, 2, 2, 2, 2, 1, 3, 1, 2]
+handsomest	2.6	0.91652	[3, 2, 1, 2, 3, 4, 4, 3, 2, 2]
+hapless	-1.4	1.11355	[-3, -1, -1, -1, -2, -1, 1, -2, -3, -1]
+haplessness	-1.4	1.0198	[-1, -2, 0, -1, -1, -1, -1, -2, -1, -4]
+happier	2.4	0.66332	[3, 1, 2, 3, 2, 2, 3, 3, 3, 2]
+happiest	3.2	0.74833	[4, 3, 2, 4, 4, 3, 3, 3, 2, 4]
+happily	2.6	0.91652	[4, 1, 2, 4, 2, 3, 2, 2, 3, 3]
+happiness	2.6	0.4899	[2, 3, 3, 3, 3, 2, 2, 3, 2, 3]
+happing	1.1	0.83066	[1, 1, 1, 0, 2, 2, 0, 2, 0, 2]
+happy	2.7	0.9	[2, 2, 2, 4, 2, 4, 3, 4, 2, 2]
+harass	-2.2	0.6	[-2, -3, -2, -2, -2, -3, -2, -3, -1, -2]
+harassed	-2.5	0.80623	[-4, -2, -3, -3, -2, -2, -3, -2, -3, -1]
+harasser	-2.4	0.8	[-3, -2, -2, -3, -2, -2, -4, -2, -3, -1]
+harassers	-2.8	0.6	[-3, -3, -2, -2, -3, -3, -3, -4, -2, -3]
+harasses	-2.5	0.80623	[-3, -3, -2, -3, -2, -2, -4, -2, -3, -1]
+harassing	-2.5	1.62788	[-2, -4, -3, -4, -3, -3, 2, -2, -3, -3]
+harassment	-2.5	0.67082	[-2, -3, -2, -2, -3, -2, -4, -3, -2, -2]
+harassments	-2.6	0.4899	[-3, -3, -2, -3, -2, -3, -3, -2, -2, -3]
+hard	-0.4	1.2	[0, -1, 0, -1, 0, 1, -2, -1, -2, 2]
+hardier	-0.6	1.68523	[-3, -2, -2, 1, 1, 2, 1, 0, -2, -2]
+hardship	-1.3	1.84662	[-2, 2, -4, -1, -2, -3, -1, -2, 2, -2]
+hardy	1.7	1.00499	[1, 2, 1, 0, 2, 2, 4, 1, 2, 2]
+harm	-2.5	0.80623	[-2, -2, -2, -3, -2, -1, -3, -3, -3, -4]
+harmed	-2.1	0.83066	[-1, -4, -2, -2, -2, -2, -1, -2, -3, -2]
+harmfully	-2.6	0.91652	[-3, -4, -3, -1, -3, -3, -3, -3, -1, -2]
+harmfulness	-2.6	0.8	[-3, -1, -3, -3, -3, -2, -4, -2, -2, -3]
+harming	-2.6	0.66332	[-3, -3, -2, -2, -3, -3, -2, -2, -2, -4]
+harmless	1.0	0.7746	[2, 1, 1, 1, 1, 0, 0, 2, 0, 2]
+harmlessly	1.4	1.2	[4, 0, 1, 0, 1, 1, 1, 2, 3, 1]
+harmlessness	0.8	1.16619	[1, 2, 0, 1, 0, 1, 2, 1, 2, -2]
+harmonic	1.8	0.87178	[2, 1, 2, 3, 0, 1, 3, 2, 2, 2]
+harmonica	0.6	0.8	[0, 1, 0, 0, 0, 2, 1, 0, 2, 0]
+harmonically	2.1	1.13578	[3, 3, 4, 1, 0, 1, 2, 2, 2, 3]
+harmonicas	0.1	0.3	[0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
+harmonicist	0.5	0.92195	[0, 0, 0, 0, 1, 0, 0, 0, 1, 3]
+harmonicists	0.9	1.3	[2, 1, 0, 0, 2, 0, 0, 0, 4, 0]
+harmonics	1.5	1.0247	[2, 2, 2, 0, 0, 2, 3, 2, 0, 2]
+harmonies	1.3	0.9	[2, 0, 2, 1, 2, 2, 0, 2, 0, 2]
+harmonious	2.0	1.09545	[3, 4, 2, 2, 2, 0, 2, 3, 1, 1]
+harmoniously	1.9	0.9434	[4, 2, 2, 1, 2, 1, 1, 3, 2, 1]
+harmoniousness	1.8	0.6	[1, 2, 2, 2, 2, 1, 2, 3, 2, 1]
+harmonise	1.8	0.74833	[1, 1, 2, 3, 2, 1, 1, 3, 2, 2]
+harmonised	1.3	0.9	[2, 3, 2, 0, 2, 1, 1, 1, 1, 0]
+harmonising	1.4	0.66332	[1, 2, 1, 1, 2, 1, 1, 1, 1, 3]
+harmonium	0.9	1.22066	[0, 3, 0, 2, 3, 0, 0, 0, 0, 1]
+harmoniums	0.8	0.9798	[0, 0, 0, 2, 0, 2, 0, 2, 2, 0]
+harmonization	1.9	0.83066	[3, 1, 2, 2, 2, 2, 3, 0, 2, 2]
+harmonizations	0.9	0.9434	[0, 0, 2, 0, 2, 2, 0, 2, 1, 0]
+harmonize	1.7	0.78102	[3, 2, 2, 1, 2, 2, 0, 1, 2, 2]
+harmonized	1.6	0.91652	[1, 2, 1, 1, 2, 2, 3, 3, 0, 1]
+harmonizer	1.6	0.8	[1, 2, 1, 1, 2, 2, 2, 3, 0, 2]
+harmonizers	1.6	1.11355	[2, 2, 2, 1, 2, 0, 4, 0, 2, 1]
+harmonizes	1.5	0.92195	[0, 2, 2, 2, 0, 1, 1, 2, 3, 2]
+harmonizing	1.4	0.66332	[0, 1, 1, 2, 2, 1, 2, 2, 1, 2]
+harmony	1.7	0.45826	[2, 2, 2, 2, 1, 2, 2, 2, 1, 1]
+harms	-2.2	1.6	[2, -3, -2, -2, -3, -2, -4, -4, -2, -2]
+harried	-1.4	0.4899	[-1, -1, -2, -1, -2, -2, -1, -1, -1, -2]
+harsh	-1.9	0.7	[-1, -1, -2, -2, -1, -3, -3, -2, -2, -2]
+harsher	-2.2	0.6	[-2, -3, -2, -3, -2, -2, -1, -3, -2, -2]
+harshest	-2.9	0.83066	[-4, -2, -2, -2, -2, -3, -3, -4, -4, -3]
+hate	-2.7	1.00499	[-4, -3, -4, -4, -2, -2, -2, -2, -1, -3]
+hated	-3.2	0.6	[-3, -3, -4, -3, -2, -3, -3, -4, -4, -3]
+hateful	-2.2	1.249	[-3, 1, -3, -3, -1, -2, -2, -3, -3, -3]
+hatefully	-2.3	0.78102	[-1, -3, -3, -3, -1, -2, -2, -2, -3, -3]
+hatefulness	-3.6	0.4899	[-4, -4, -3, -3, -3, -4, -4, -4, -4, -3]
+hater	-1.8	0.6	[-2, -1, -2, -2, -2, -1, -1, -2, -2, -3]
+haters	-2.2	0.6	[-2, -1, -3, -2, -3, -2, -3, -2, -2, -2]
+hates	-1.9	0.7	[-2, -1, -2, -2, -3, -1, -1, -2, -2, -3]
+hating	-2.3	1.1	[-4, -3, -4, -1, -2, -2, -1, -2, -1, -3]
+hatred	-3.2	0.9798	[-1, -3, -2, -4, -3, -3, -4, -4, -4, -4]
+haunt	-1.7	1.00499	[-1, -1, -3, -1, -2, -2, -1, -4, -1, -1]
+haunted	-2.1	0.7	[-2, -2, -1, -3, -3, -2, -2, -3, -1, -2]
+haunting	-1.1	0.83066	[-3, 0, -2, -1, 0, -1, -1, -1, -1, -1]
+haunts	-1.0	1.41421	[0, -2, -2, -2, -2, -1, 2, -2, 1, -2]
+havoc	-2.9	0.7	[-2, -4, -4, -3, -2, -3, -3, -3, -2, -3]
+healthy	1.7	0.9	[1, 3, 1, 1, 3, 3, 1, 2, 1, 1]
+heartbreak	-2.7	0.78102	[-1, -3, -3, -3, -2, -4, -2, -3, -3, -3]
+heartbreaker	-2.2	1.07703	[-2, -3, 0, -3, -2, -1, -4, -3, -2, -2]
+heartbreakers	-2.1	0.9434	[-3, -2, -3, -2, -1, -1, -4, -1, -2, -2]
+heartbreaking	-2.0	1.73205	[-3, -1, -3, -3, -4, 2, -3, -2, 0, -3]
+heartbreakingly	-1.8	2.08806	[-3, 3, 1, -3, -3, -2, -3, -3, -4, -1]
+heartbreaks	-1.8	1.77764	[-2, 1, -3, -2, -3, -2, -3, 2, -4, -2]
+heartbroken	-3.3	0.45826	[-4, -3, -3, -4, -3, -3, -4, -3, -3, -3]
+heartfelt	2.5	0.5	[3, 3, 2, 3, 2, 2, 3, 2, 2, 3]
+heartless	-2.2	0.74833	[-2, -2, -2, -4, -2, -1, -2, -3, -2, -2]
+heartlessly	-2.8	0.6	[-3, -2, -3, -3, -2, -3, -4, -2, -3, -3]
+heartlessness	-2.8	0.87178	[-3, -3, -2, -3, -4, -4, -1, -3, -2, -3]
+heartwarming	2.1	1.22066	[3, 2, 3, 3, 2, 2, 3, 3, -1, 1]
+heaven	2.3	1.18743	[1, 1, 2, 4, 3, 3, 3, 4, 1, 1]
+heavenlier	3.0	0.63246	[3, 2, 3, 3, 4, 3, 3, 4, 2, 3]
+heavenliest	2.7	1.1	[3, 2, 3, 4, 2, 4, 3, 0, 3, 3]
+heavenliness	2.7	0.9	[3, 2, 1, 4, 3, 2, 3, 4, 3, 2]
+heavenlinesses	2.3	2.2383	[4, 4, 4, 3, -2, 3, 3, 4, -2, 2]
+heavenly	3.0	0.63246	[3, 3, 3, 3, 2, 3, 3, 4, 2, 4]
+heavens	1.7	1.18743	[4, 0, 1, 2, 0, 3, 2, 2, 2, 1]
+heavenward	1.4	1.35647	[0, 3, 0, 4, 1, 2, 2, 0, 2, 0]
+heavenwards	1.2	1.32665	[1, 4, 0, 0, 2, 1, 1, 0, 3, 0]
+heavyhearted	-2.1	0.83066	[-2, -3, -3, -2, -3, -1, -1, -1, -2, -3]
+heh	-0.6	1.28062	[0, 1, -1, 1, -1, -2, -1, -3, 1, -1]
+hell	-3.6	0.66332	[-4, -4, -4, -4, -4, -2, -3, -4, -3, -4]
+hellish	-3.2	0.74833	[-3, -3, -2, -2, -4, -3, -4, -4, -3, -4]
+help	1.7	0.78102	[3, 2, 1, 2, 1, 2, 3, 1, 1, 1]
+helper	1.4	0.8	[1, 1, 0, 1, 1, 2, 1, 2, 3, 2]
+helpers	1.1	0.83066	[1, 1, 0, 2, 1, 1, 1, 1, 3, 0]
+helpful	1.8	0.87178	[2, 1, 3, 1, 1, 3, 1, 2, 3, 1]
+helpfully	2.3	0.9	[1, 2, 2, 3, 2, 3, 3, 2, 4, 1]
+helpfulness	1.9	1.13578	[1, 4, 1, 2, 2, 1, 1, 2, 4, 1]
+helping	1.2	0.6	[2, 1, 1, 2, 0, 1, 1, 1, 2, 1]
+helpless	-2.0	0.63246	[-2, -3, -2, -2, -2, -3, -1, -2, -1, -2]
+helplessly	-1.4	0.4899	[-1, -1, -2, -2, -1, -1, -1, -2, -2, -1]
+helplessness	-2.1	0.9434	[-2, -4, -1, -2, -1, -3, -3, -2, -1, -2]
+helplessnesses	-1.7	0.64031	[-2, -1, -2, -1, -2, -1, -3, -2, -1, -2]
+helps	1.6	0.4899	[1, 1, 1, 2, 2, 2, 1, 2, 2, 2]
+hero	2.6	0.8	[2, 3, 2, 2, 4, 4, 2, 3, 2, 2]
+heroes	2.3	0.9	[3, 4, 3, 1, 3, 2, 1, 2, 2, 2]
+heroic	2.6	0.8	[3, 3, 1, 4, 2, 3, 2, 3, 2, 3]
+heroical	2.9	1.04403	[4, 4, 2, 4, 2, 3, 1, 4, 2, 3]
+heroically	2.4	0.8	[2, 2, 2, 3, 3, 3, 4, 1, 2, 2]
+heroicomic	1.0	1.0	[1, 0, 1, 0, 2, 0, 3, 1, 2, 0]
+heroicomical	1.1	0.83066	[2, 0, 0, 2, 1, 2, 1, 2, 1, 0]
+heroics	2.4	0.8	[2, 1, 2, 2, 2, 3, 3, 3, 4, 2]
+heroin	-2.2	1.83303	[0, -2, -4, 2, -4, -2, -2, -3, -3, -4]
+heroine	2.7	1.1	[0, 2, 4, 4, 3, 3, 3, 3, 2, 3]
+heroines	1.8	1.32665	[2, 1, 1, 4, 3, 1, 0, 3, 3, 0]
+heroinism	-2.0	2.0	[-3, -4, 2, -2, -4, -3, -2, -1, 1, -4]
+heroism	2.8	0.6	[3, 3, 4, 3, 2, 2, 3, 3, 2, 3]
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+heroize	2.1	0.7	[3, 2, 3, 1, 2, 2, 2, 3, 1, 2]
+heroized	2.0	1.18322	[1, 0, 3, 3, 2, 0, 3, 3, 2, 3]
+heroizes	2.2	0.9798	[1, 3, 2, 3, 4, 3, 2, 1, 2, 1]
+heroizing	1.9	1.64012	[2, 3, -2, 2, 4, 3, 2, 2, 3, 0]
+heron	0.1	0.3	[0, 0, 0, 0, 0, 1, 0, 0, 0, 0]
+heronries	0.7	1.1	[2, 0, 0, 0, 2, 0, 3, 0, 0, 0]
+heronry	0.1	0.9434	[0, 0, 0, 0, 0, 2, 0, 1, -2, 0]
+herons	0.5	1.0247	[0, 0, 0, 3, 0, 2, 0, 0, 0, 0]
+heros	1.3	1.18743	[3, 0, 0, 2, 0, 2, 2, 3, 1, 0]
+hesitance	-0.9	0.3	[-1, -1, 0, -1, -1, -1, -1, -1, -1, -1]
+hesitancies	-1.0	0.63246	[-1, -1, -1, -2, -1, -1, -2, 0, 0, -1]
+hesitancy	-0.9	0.53852	[0, -1, 0, -2, -1, -1, -1, -1, -1, -1]
+hesitant	-1.0	0.7746	[0, -1, 0, -1, -2, 0, -1, -2, -1, -2]
+hesitantly	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -2, -1, -1]
+hesitate	-1.1	0.53852	[-2, -1, -1, -1, -2, -1, -1, 0, -1, -1]
+hesitated	-1.3	0.9	[-1, -2, -1, -2, -2, -2, -1, 1, -1, -2]
+hesitater	-1.4	0.66332	[-1, -1, -1, -1, -1, -2, -1, -3, -2, -1]
+hesitaters	-1.4	0.4899	[-1, -2, -1, -1, -1, -1, -2, -2, -2, -1]
+hesitates	-1.4	0.4899	[-1, -1, -1, -2, -1, -2, -1, -2, -2, -1]
+hesitating	-1.4	0.66332	[-1, -1, -2, -1, -1, -3, -2, -1, -1, -1]
+hesitatingly	-1.5	0.80623	[-1, -1, -1, -1, -3, -2, -3, -1, -1, -1]
+hesitation	-1.1	0.53852	[-2, 0, -1, -1, -1, -1, -1, -2, -1, -1]
+hesitations	-1.1	0.53852	[-1, -1, -1, 0, -2, -1, -1, -2, -1, -1]
+hid	-0.4	0.4899	[0, -1, 0, 0, -1, -1, -1, 0, 0, 0]
+hide	-0.7	0.64031	[0, -1, -1, -1, -1, 0, 0, -2, -1, 0]
+hides	-0.7	0.9	[-1, -2, -1, 0, -1, 0, 0, -2, 1, -1]
+hiding	-1.2	0.4	[-1, -1, -2, -1, -1, -1, -1, -1, -2, -1]
+highlight	1.4	0.91652	[3, 0, 1, 1, 2, 1, 0, 2, 2, 2]
+hilarious	1.7	1.41774	[2, 2, 2, 3, 3, 1, -2, 2, 3, 1]
+hindrance	-1.7	0.78102	[-2, -3, -2, -1, -1, -1, -3, -1, -2, -1]
+hoax	-1.1	1.04403	[-3, -1, -2, -1, 1, -2, -1, -1, -1, 0]
+holiday	1.7	1.18743	[1, 3, 2, 2, 0, 0, 1, 2, 4, 2]
+holidays	1.6	1.0198	[2, 0, 1, 2, 3, 0, 1, 2, 3, 2]
+homesick	-0.7	1.67631	[-2, -1, -1, -2, -1, -2, 2, -1, 3, -2]
+homesickness	-1.8	1.249	[-3, -2, -1, -1, -3, -2, -1, 1, -3, -3]
+homesicknesses	-1.8	0.6	[-1, -2, -2, -2, -1, -2, -1, -2, -3, -2]
+honest	2.3	0.9	[3, 2, 1, 2, 3, 1, 2, 3, 2, 4]
+honester	1.9	0.7	[2, 3, 2, 2, 1, 3, 1, 1, 2, 2]
+honestest	3.0	0.7746	[1, 3, 3, 3, 3, 3, 4, 4, 3, 3]
+honesties	1.8	1.07703	[4, 3, 1, 1, 1, 1, 3, 2, 1, 1]
+honestly	2.0	0.63246	[2, 3, 2, 2, 1, 2, 2, 1, 3, 2]
+honesty	2.2	0.6	[2, 3, 2, 2, 1, 2, 3, 2, 3, 2]
+honor	2.2	1.16619	[3, 2, 1, 2, 0, 4, 3, 1, 3, 3]
+honorability	2.2	0.4	[3, 3, 2, 2, 2, 2, 2, 2, 2, 2]
+honorable	2.5	0.67082	[2, 2, 3, 2, 4, 3, 2, 2, 2, 3]
+honorableness	2.2	0.87178	[2, 4, 1, 3, 3, 2, 1, 2, 2, 2]
+honorably	2.4	0.66332	[2, 2, 3, 2, 3, 3, 3, 1, 2, 3]
+honoraria	0.6	0.8	[1, 0, 1, 0, 0, 0, 2, 0, 2, 0]
+honoraries	1.5	1.5	[2, 2, 1, 3, 3, 1, -2, 2, 3, 0]
+honorarily	1.9	0.7	[2, 2, 3, 1, 2, 1, 2, 1, 3, 2]
+honorarium	0.7	1.48661	[3, 2, -1, 2, 1, -2, 1, 1, -1, 1]
+honorariums	1.0	1.0	[0, 0, 0, 0, 1, 2, 1, 3, 2, 1]
+honorary	1.4	0.91652	[2, 2, 2, 3, 1, 1, 0, 1, 2, 0]
+honored	2.8	0.87178	[3, 4, 4, 3, 1, 2, 2, 3, 3, 3]
+honoree	2.1	0.7	[3, 2, 3, 3, 1, 2, 1, 2, 2, 2]
+honorees	2.3	0.78102	[1, 3, 3, 4, 2, 2, 2, 2, 2, 2]
+honorer	1.7	0.78102	[2, 1, 3, 3, 1, 2, 1, 2, 1, 1]
+honorers	1.3	0.45826	[1, 1, 2, 2, 1, 1, 2, 1, 1, 1]
+honorific	1.4	1.2	[2, 2, 2, 2, 2, 1, 2, 1, 2, -2]
+honorifically	2.2	0.74833	[3, 4, 1, 2, 2, 2, 2, 2, 2, 2]
+honorifics	1.7	0.78102	[1, 2, 0, 1, 2, 2, 2, 3, 2, 2]
+honoring	2.3	0.64031	[3, 3, 1, 2, 2, 3, 3, 2, 2, 2]
+honors	2.3	0.64031	[3, 2, 2, 2, 1, 3, 3, 2, 3, 2]
+honour	2.7	0.78102	[2, 3, 2, 2, 2, 3, 4, 4, 3, 2]
+honourable	2.1	0.53852	[2, 3, 2, 2, 2, 1, 3, 2, 2, 2]
+honoured	2.2	1.249	[3, 3, 4, 3, -1, 2, 2, 2, 2, 2]
+honourer	1.8	0.87178	[2, 3, 2, 1, 2, 3, 1, 0, 2, 2]
+honourers	1.6	1.0198	[0, 2, 2, 1, 2, 2, 1, 3, 0, 3]
+honouring	2.1	0.3	[2, 2, 2, 3, 2, 2, 2, 2, 2, 2]
+honours	2.2	0.87178	[4, 3, 2, 2, 3, 2, 2, 1, 2, 1]
+hooligan	-1.5	0.5	[-1, -2, -1, -2, -2, -2, -1, -1, -2, -1]
+hooliganism	-2.1	0.83066	[-3, -2, -3, -3, -2, -2, -2, -2, 0, -2]
+hooligans	-1.1	1.22066	[-2, -1, -1, 2, -1, -1, -1, -3, -2, -1]
+hooray	2.3	0.9	[3, 2, 3, 2, 1, 3, 1, 2, 2, 4]
+hope	1.9	0.53852	[3, 2, 2, 1, 2, 2, 1, 2, 2, 2]
+hoped	1.6	0.4899	[1, 2, 1, 1, 2, 2, 1, 2, 2, 2]
+hopeful	2.3	0.78102	[2, 1, 1, 3, 3, 3, 2, 3, 2, 3]
+hopefully	1.7	0.78102	[1, 3, 1, 3, 1, 2, 1, 1, 2, 2]
+hopefulness	1.6	1.35647	[2, 1, -2, 2, 3, 2, 1, 3, 2, 2]
+hopeless	-2.0	1.78885	[-3, -3, -3, -3, 3, -1, -3, -3, -2, -2]
+hopelessly	-2.2	0.74833	[-3, -4, -2, -2, -1, -2, -2, -2, -2, -2]
+hopelessness	-3.1	0.7	[-3, -4, -4, -3, -3, -3, -4, -3, -2, -2]
+hopes	1.8	0.6	[1, 3, 1, 2, 2, 2, 1, 2, 2, 2]
+hoping	1.8	0.4	[2, 2, 2, 1, 2, 2, 2, 2, 2, 1]
+horrendous	-2.8	0.87178	[-3, -3, -4, -4, -3, -3, -2, -2, -1, -3]
+horrendously	-1.9	1.92094	[-3, -2, -4, -4, 2, -1, -3, -2, 1, -3]
+horrent	-0.9	1.04403	[0, -1, -2, 0, 0, -3, -1, 0, -2, 0]
+horrible	-2.5	0.67082	[-2, -2, -3, -2, -2, -4, -3, -3, -2, -2]
+horribleness	-2.4	0.4899	[-3, -3, -2, -2, -3, -2, -2, -3, -2, -2]
+horribles	-2.1	0.7	[-2, -4, -2, -2, -1, -2, -2, -2, -2, -2]
+horribly	-2.4	0.66332	[-2, -2, -2, -2, -2, -4, -3, -3, -2, -2]
+horrid	-2.5	1.0247	[-2, -3, -3, -4, -4, -1, -2, -2, -3, -1]
+horridly	-1.4	1.49666	[-2, 0, -3, -2, 0, -3, 2, -2, -2, -2]
+horridness	-2.3	1.26886	[-3, -3, -2, 1, -3, -3, -3, -3, -1, -3]
+horridnesses	-3.0	1.09545	[-2, -3, -4, -4, -4, -4, -2, -2, -1, -4]
+horrific	-3.4	0.91652	[-2, -4, -4, -4, -2, -4, -2, -4, -4, -4]
+horrifically	-2.9	0.7	[-2, -3, -2, -4, -2, -4, -3, -3, -3, -3]
+horrified	-2.5	0.92195	[-2, -3, -2, -2, -1, -4, -2, -2, -3, -4]
+horrifies	-2.9	1.22066	[-1, -3, -2, -1, -4, -4, -4, -4, -2, -4]
+horrify	-2.5	0.67082	[-2, -2, -3, -2, -2, -2, -4, -2, -3, -3]
+horrifying	-2.7	0.9	[-3, -4, -3, -2, -3, -3, -4, -2, -2, -1]
+horrifyingly	-3.3	0.9	[-3, -3, -4, -4, -1, -4, -3, -3, -4, -4]
+horror	-2.7	1.1	[-3, -1, -4, -4, -4, -3, -1, -2, -3, -2]
+horrors	-2.7	0.64031	[-3, -3, -4, -3, -2, -2, -2, -3, -2, -3]
+hostile	-1.6	1.74356	[-4, -3, -3, -1, 1, -2, 2, -2, -2, -2]
+hostilely	-2.2	0.6	[-1, -3, -3, -2, -2, -2, -2, -2, -2, -3]
+hostiles	-1.3	1.9	[-3, -3, -3, -3, -1, 2, -3, -1, 1, 1]
+hostilities	-2.1	0.53852	[-2, -3, -2, -2, -2, -2, -1, -2, -3, -2]
+hostility	-2.5	0.80623	[-2, -2, -3, -3, -3, -2, -4, -2, -3, -1]
+huckster	-0.9	0.7	[-1, 0, -1, 0, -1, -2, -2, 0, -1, -1]
+hug	2.1	1.04403	[1, 3, 2, 1, 1, 2, 3, 3, 1, 4]
+huge	1.3	0.9	[0, 2, 2, 0, 0, 2, 2, 2, 1, 2]
+huggable	1.6	0.66332	[2, 2, 1, 1, 1, 3, 1, 2, 2, 1]
+hugged	1.7	0.78102	[2, 2, 2, 2, 3, 1, 1, 2, 0, 2]
+hugger	1.6	0.91652	[3, 2, 2, 2, 3, 1, 1, 1, 0, 1]
+huggers	1.8	0.6	[1, 3, 1, 2, 1, 2, 2, 2, 2, 2]
+hugging	1.8	0.74833	[2, 1, 1, 3, 3, 2, 2, 1, 2, 1]
+hugs	2.2	0.74833	[3, 2, 1, 2, 2, 2, 3, 1, 3, 3]
+humerous	1.4	1.11355	[-1, 2, 2, 3, 1, 1, 2, 0, 2, 2]
+humiliate	-2.5	1.28452	[-3, -3, -3, -3, -2, -2, -4, -3, 1, -3]
+humiliated	-1.4	2.498	[3, -3, -4, -3, -3, -4, -3, 0, 1, 2]
+humiliates	-1.0	2.09762	[1, -2, -3, -3, -3, -2, -3, 1, 2, 2]
+humiliating	-1.2	1.8868	[-4, -1, -3, -1, 2, -1, 2, -3, -2, -1]
+humiliatingly	-2.6	0.4899	[-3, -3, -2, -2, -3, -3, -3, -3, -2, -2]
+humiliation	-2.7	0.78102	[-2, -3, -4, -2, -2, -2, -3, -2, -4, -3]
+humiliations	-2.4	0.66332	[-3, -2, -2, -2, -2, -2, -2, -3, -2, -4]
+humor	1.1	0.53852	[1, 0, 2, 2, 1, 1, 1, 1, 1, 1]
+humoral	0.6	1.0198	[2, 0, 0, 0, 0, 0, 3, 1, 0, 0]
+humored	1.2	0.87178	[1, 1, 2, 2, 1, 1, 2, 1, 2, -1]
+humoresque	1.2	0.6	[1, 1, 1, 2, 1, 2, 2, 1, 1, 0]
+humoresques	0.9	1.04403	[1, 0, 2, 0, 0, 1, 2, 0, 3, 0]
+humoring	2.1	0.7	[3, 2, 2, 2, 1, 2, 2, 1, 3, 3]
+humorist	1.2	0.74833	[1, 2, 1, 1, 2, 1, 2, 0, 0, 2]
+humoristic	1.5	0.80623	[3, 0, 2, 1, 2, 1, 2, 2, 1, 1]
+humorists	1.3	0.78102	[2, 1, 1, 1, 0, 1, 2, 3, 1, 1]
+humorless	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -2]
+humorlessness	-1.4	1.11355	[1, -3, -3, -1, -1, -2, -1, -1, -2, -1]
+humorous	1.6	0.4899	[1, 2, 1, 2, 2, 1, 2, 2, 1, 2]
+humorously	2.3	0.78102	[3, 3, 2, 2, 1, 3, 3, 1, 2, 3]
+humorousness	2.4	0.66332	[1, 2, 3, 2, 3, 2, 3, 3, 2, 3]
+humors	1.6	0.4899	[2, 1, 2, 2, 2, 2, 1, 2, 1, 1]
+humour	2.1	0.9434	[1, 2, 2, 4, 2, 1, 1, 3, 3, 2]
+humoured	1.1	0.53852	[1, 0, 1, 2, 2, 1, 1, 1, 1, 1]
+humouring	1.7	0.78102	[2, 3, 1, 2, 1, 0, 2, 2, 2, 2]
+humourous	2.0	0.7746	[1, 2, 3, 2, 2, 3, 3, 2, 1, 1]
+hunger	-1.0	1.67332	[-4, 0, 2, -2, -1, -2, 1, -2, 0, -2]
+hurrah	2.6	0.8	[3, 2, 3, 3, 1, 3, 4, 2, 2, 3]
+hurrahed	1.9	0.53852	[2, 2, 1, 1, 2, 2, 3, 2, 2, 2]
+hurrahing	2.4	0.4899	[3, 2, 2, 2, 3, 2, 3, 3, 2, 2]
+hurrahs	2.1	1.44568	[2, 3, 0, 3, 2, 3, -1, 2, 3, 4]
+hurray	2.7	0.78102	[3, 2, 3, 3, 1, 3, 4, 2, 3, 3]
+hurrayed	1.8	1.32665	[3, 3, 2, 3, 3, 3, 0, 0, 1, 0]
+hurraying	1.2	1.66132	[2, -3, 2, 3, 0, 2, 2, 2, 0, 2]
+hurrays	2.4	1.11355	[2, 3, 2, 4, 0, 3, 2, 2, 2, 4]
+hurt	-2.4	0.8	[-3, -3, -2, -2, -4, -3, -2, -1, -2, -2]
+hurter	-2.3	0.78102	[-2, -4, -1, -2, -3, -3, -2, -2, -2, -2]
+hurters	-1.9	1.04403	[-2, -3, -1, -2, -1, 0, -3, -3, -3, -1]
+hurtful	-2.4	1.0198	[-2, -4, -2, -2, -1, -3, -2, -3, -1, -4]
+hurtfully	-2.6	0.66332	[-3, -2, -3, -2, -2, -3, -4, -3, -2, -2]
+hurtfulness	-1.9	1.51327	[2, -2, -2, -2, -3, -1, -2, -3, -4, -2]
+hurting	-1.7	0.78102	[-3, -1, -1, -2, -1, -1, -3, -2, -2, -1]
+hurtle	-0.3	1.1	[-2, 1, 0, -1, -1, -1, 0, 2, 0, -1]
+hurtled	-0.6	0.8	[0, -2, 0, 0, 0, 0, -1, -1, -2, 0]
+hurtles	-1.0	0.63246	[-1, -2, 0, 0, -1, -1, -1, -1, -2, -1]
+hurtless	0.3	1.55242	[-1, -3, 2, 1, 2, 1, 0, 0, -1, 2]
+hurtling	-1.4	0.8	[-3, -2, -1, -1, -1, -1, -1, -2, 0, -2]
+hurts	-2.1	0.83066	[-4, -2, -2, -2, -3, -1, -2, -2, -2, -1]
+hypocritical	-2.0	0.89443	[-4, -2, -1, -3, -2, -1, -2, -1, -2, -2]
+hysteria	-1.9	0.7	[-1, -3, -1, -2, -2, -2, -2, -2, -1, -3]
+hysterical	-0.1	1.97231	[2, 0, 0, 3, -2, -2, 3, -1, -2, -2]
+hysterics	-1.8	1.77764	[-3, -3, -3, -1, -3, -1, -2, 3, -3, -2]
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+idealised	2.1	0.83066	[1, 4, 1, 3, 2, 2, 2, 2, 2, 2]
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+idealising	0.6	0.4899	[0, 1, 1, 1, 1, 1, 1, 0, 0, 0]
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+idealist	1.6	1.56205	[2, 3, -2, 1, 3, 3, 1, 0, 2, 3]
+idealistic	1.8	0.9798	[2, 1, 0, 2, 4, 2, 2, 2, 1, 2]
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+idealize	1.2	0.9798	[1, 2, 2, 0, 0, 1, 3, 0, 2, 1]
+idealized	1.8	0.74833	[2, 3, 1, 1, 2, 1, 3, 1, 2, 2]
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+idealizing	1.4	1.0198	[1, 1, 2, 3, 0, 1, 3, 0, 2, 1]
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+ignorable	-1.0	0.63246	[-1, -1, -1, -2, 0, -1, 0, -1, -2, -1]
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+ignoramus	-1.9	0.83066	[-1, -2, -1, -3, -1, -3, -1, -3, -2, -2]
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+ignorantly	-1.6	0.91652	[-1, -2, -2, -2, -2, -2, -2, 1, -2, -2]
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+ignored	-1.3	0.45826	[-2, -1, -2, -1, -1, -2, -1, -1, -1, -1]
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+ignoring	-1.7	0.64031	[-1, -1, -1, -2, -2, -3, -2, -1, -2, -2]
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+immoralities	-1.1	1.51327	[-2, -1, -4, -3, 1, 1, -1, 0, -1, -1]
+immorality	-0.6	2.2891	[3, -3, 1, 2, 2, -2, -4, -1, -2, -2]
+immorally	-2.1	0.7	[-1, -1, -2, -2, -3, -2, -3, -2, -2, -3]
+immortal	1.0	1.73205	[3, 3, 2, 2, -2, -2, 2, 1, 1, 0]
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+impatiens	-0.2	0.6	[0, 0, -1, 0, 0, 0, 1, -1, -1, 0]
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+impatiently	-1.7	0.64031	[-1, -1, -2, -3, -1, -2, -1, -2, -2, -2]
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+impolite	-1.6	0.66332	[-2, -1, -3, -1, -1, -1, -1, -2, -2, -2]
+impolitely	-1.8	0.6	[-2, -2, -1, -1, -2, -1, -2, -2, -3, -2]
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+impolitenesses	-2.3	0.78102	[-3, -2, -2, -1, -1, -3, -3, -2, -3, -3]
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+importancy	1.4	0.66332	[2, 1, 2, 2, 1, 2, 1, 0, 2, 1]
+important	0.8	1.07703	[0, 0, 0, 2, 1, 0, 0, 3, 2, 0]
+importantly	1.3	0.78102	[2, 1, 2, 1, 2, 2, 0, 0, 1, 2]
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+imposed	-0.3	1.41774	[2, -1, -1, -1, 1, 0, -2, 2, -2, -1]
+imposes	-0.4	1.42829	[-2, -1, 1, -2, -1, -1, -2, 1, 2, 1]
+imposing	-0.4	1.0198	[1, -1, -2, -1, 1, 1, 0, -1, -1, -1]
+impotent	-1.1	0.3	[-1, -1, -1, -2, -1, -1, -1, -1, -1, -1]
+impress	1.9	0.53852	[2, 2, 1, 2, 2, 2, 2, 1, 2, 3]
+impressed	2.1	0.3	[2, 2, 2, 2, 2, 2, 3, 2, 2, 2]
+impresses	2.1	0.3	[2, 2, 2, 2, 2, 2, 3, 2, 2, 2]
+impressibility	1.2	1.249	[-1, 2, 0, 2, 0, 2, 2, 3, 2, 0]
+impressible	0.8	1.16619	[2, -1, 1, 0, -1, 2, 1, 0, 2, 2]
+impressing	2.5	0.92195	[3, 4, 1, 2, 3, 2, 3, 1, 3, 3]
+impression	0.9	0.9434	[0, 1, 0, 0, 2, 2, 0, 2, 0, 2]
+impressionable	0.2	1.07703	[0, 0, -1, 1, -1, -1, 0, 2, 0, 2]
+impressionism	0.8	1.07703	[0, 2, 3, 0, 0, 2, 0, 0, 1, 0]
+impressionisms	0.5	0.80623	[0, 0, 0, 0, 0, 2, 0, 1, 0, 2]
+impressionist	1.0	1.09545	[0, 2, 3, 0, 0, 2, 2, 0, 1, 0]
+impressionistic	1.5	1.20416	[2, 2, 0, 0, 1, 0, 2, 2, 4, 2]
+impressionistically	1.6	0.8	[2, 0, 1, 1, 2, 2, 3, 2, 2, 1]
+impressionists	0.5	1.43178	[2, 0, 0, 1, 1, 2, -2, 2, 1, -2]
+impressions	0.9	1.13578	[2, 0, 0, 3, 0, 2, 0, 2, 0, 0]
+impressive	2.3	0.78102	[1, 2, 3, 2, 3, 2, 3, 3, 3, 1]
+impressively	2.0	0.89443	[3, 1, 1, 2, 2, 2, 2, 4, 2, 1]
+impressiveness	1.7	0.64031	[2, 1, 2, 3, 1, 2, 2, 2, 1, 1]
+impressment	-0.4	1.85472	[-2, 1, 3, -2, -1, -3, 0, 0, 2, -2]
+impressments	0.5	1.20416	[2, 0, 0, 1, 2, 2, 0, -2, 0, 0]
+impressure	0.6	1.0198	[-1, 0, 0, 0, 0, 2, 0, 2, 1, 2]
+imprisoned	-2.0	1.0	[-4, -2, -3, -1, -3, -2, -1, -2, -1, -1]
+improve	1.9	0.7	[2, 3, 3, 2, 1, 1, 2, 2, 1, 2]
+improved	2.1	0.7	[3, 1, 2, 3, 2, 3, 1, 2, 2, 2]
+improvement	2.0	0.63246	[2, 3, 3, 2, 1, 1, 2, 2, 2, 2]
+improvements	1.3	0.64031	[0, 2, 2, 1, 2, 2, 1, 1, 1, 1]
+improver	1.8	0.6	[2, 1, 2, 1, 2, 3, 1, 2, 2, 2]
+improvers	1.3	0.78102	[1, 2, 2, 1, 2, 2, 0, 0, 1, 2]
+improves	1.8	1.07703	[3, -1, 2, 2, 2, 3, 1, 2, 2, 2]
+improving	1.8	0.4	[2, 2, 1, 1, 2, 2, 2, 2, 2, 2]
+inability	-1.7	0.9	[-2, -2, -3, 0, -2, -3, -2, -1, -1, -1]
+inaction	-1.0	0.63246	[-2, -1, 0, -1, -1, 0, -1, -2, -1, -1]
+inadequacies	-1.7	0.64031	[-1, -3, -2, -1, -2, -1, -2, -2, -1, -2]
+inadequacy	-1.7	0.78102	[-1, -3, -1, -1, -3, -2, -2, -1, -2, -1]
+inadequate	-1.7	0.64031	[-2, -1, -1, -3, -1, -1, -2, -2, -2, -2]
+inadequately	-1.0	1.26491	[-3, -1, -1, -2, 2, -1, -2, -1, 0, -1]
+inadequateness	-1.7	0.45826	[-2, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+inadequatenesses	-1.6	0.91652	[-1, -1, -2, -1, -2, -4, -2, -1, -1, -1]
+incapable	-1.6	0.4899	[-1, -2, -1, -1, -2, -1, -2, -2, -2, -2]
+incapacitated	-1.9	0.9434	[-2, -2, -1, -1, -2, -4, -1, -1, -2, -3]
+incensed	-2.0	1.0	[-2, -1, -4, 0, -2, -2, -2, -3, -2, -2]
+incentive	1.5	1.0247	[1, 2, 1, 2, 1, 0, 4, 2, 1, 1]
+incentives	1.3	1.34536	[2, 2, 1, 1, 3, 1, -2, 3, 1, 1]
+incompetence	-2.3	0.45826	[-3, -2, -2, -3, -2, -3, -2, -2, -2, -2]
+incompetent	-2.1	0.83066	[-1, -1, -2, -2, -3, -3, -2, -3, -1, -3]
+inconsiderate	-1.9	0.7	[-2, -1, -1, -1, -2, -2, -2, -3, -3, -2]
+inconvenience	-1.5	0.5	[-1, -2, -1, -1, -1, -2, -2, -1, -2, -2]
+inconvenient	-1.4	0.4899	[-2, -2, -1, -2, -1, -2, -1, -1, -1, -1]
+increase	1.3	0.64031	[1, 2, 2, 1, 2, 0, 1, 1, 2, 1]
+increased	1.1	1.04403	[2, 0, 3, 2, 2, 1, 0, 1, 0, 0]
+indecision	-0.8	0.6	[-1, 0, -1, 0, -1, -1, -2, 0, -1, -1]
+indecisions	-1.1	0.53852	[-1, -1, -1, -1, -2, -1, -2, -1, 0, -1]
+indecisive	-1.0	0.44721	[0, -1, -1, -1, -1, -2, -1, -1, -1, -1]
+indecisively	-0.7	1.18743	[-2, -1, -1, -1, -1, -1, -2, 2, 1, -1]
+indecisiveness	-1.3	0.64031	[-1, -3, -1, -2, -1, -1, -1, -1, -1, -1]
+indecisivenesses	-0.9	0.53852	[-1, -1, 0, -1, -1, 0, -1, -2, -1, -1]
+indestructible	0.6	1.85472	[3, 4, -1, -2, 1, 1, 2, 0, -1, -1]
+indifference	-0.2	0.74833	[0, -1, 0, 0, 0, 1, -2, 0, 0, 0]
+indifferent	-0.8	0.6	[-1, 0, 0, -1, -2, -1, -1, 0, -1, -1]
+indignant	-1.8	0.74833	[-1, -3, -2, -2, -2, -1, -1, -1, -3, -2]
+indignation	-2.4	0.8	[-2, -1, -2, -3, -3, -3, -1, -3, -3, -3]
+indoctrinate	-1.4	0.91652	[-1, -3, -1, 0, -2, -1, -2, -2, 0, -2]
+indoctrinated	-0.4	1.35647	[1, -2, -3, 1, -1, 1, 1, -1, -1, 0]
+indoctrinates	-0.6	1.2	[1, -1, -3, 1, -1, 1, -1, -1, -1, -1]
+indoctrinating	-0.7	1.41774	[-1, 0, -3, -1, -2, -1, 2, -2, 0, 1]
+ineffective	-0.5	1.74642	[-2, -1, -1, -1, -2, 2, -2, 1, 3, -2]
+ineffectively	-1.3	0.9	[-2, -2, -2, 1, -1, -1, -1, -2, -1, -2]
+ineffectiveness	-1.3	0.45826	[-1, -1, -2, -1, -1, -2, -1, -1, -2, -1]
+ineffectual	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+ineffectuality	-1.6	0.66332	[-2, -1, -1, -1, -2, -1, -3, -2, -2, -1]
+ineffectually	-1.1	0.9434	[-1, -2, -2, -1, 0, -1, -2, -1, 1, -2]
+ineffectualness	-1.3	0.45826	[-2, -1, -1, -1, -1, -2, -1, -1, -2, -1]
+infatuated	0.2	1.72047	[3, 2, 0, 3, -1, -1, -2, 0, -1, -1]
+infatuation	0.6	1.74356	[1, -1, -1, 2, -1, 1, 4, 2, 1, -2]
+infected	-2.2	0.6	[-3, -2, -2, -2, -2, -2, -3, -1, -2, -3]
+inferior	-1.7	0.78102	[-1, -2, -2, -1, -1, -3, -2, -1, -1, -3]
+inferiorities	-1.9	0.7	[-2, -3, -1, -2, -2, -3, -1, -1, -2, -2]
+inferiority	-1.1	1.7	[-2, -3, -2, -2, -2, -3, 2, 1, -1, 1]
+inferiorly	-2.0	0.63246	[-3, -2, -2, -2, -2, -3, -1, -2, -1, -2]
+inferiors	-0.5	1.43178	[-1, -1, -1, -2, -1, 0, 3, -1, 1, -2]
+inflamed	-1.4	1.28062	[-2, -2, -1, -2, -2, -1, 2, -3, -2, -1]
+influential	1.9	1.04403	[3, 1, 2, 3, 4, 1, 1, 2, 1, 1]
+infringement	-2.1	0.83066	[-3, -1, -2, -1, -2, -1, -3, -3, -2, -3]
+infuriate	-2.2	0.87178	[-2, -1, -3, -3, -2, -3, -3, -1, -1, -3]
+infuriated	-3.0	0.7746	[-1, -4, -3, -3, -3, -3, -3, -3, -3, -4]
+infuriates	-2.6	0.8	[-4, -2, -1, -3, -3, -3, -2, -3, -3, -2]
+infuriating	-2.4	1.42829	[-1, -3, -3, -3, -3, -4, 0, 0, -4, -3]
+inhibin	-0.2	0.4	[-1, 0, 0, 0, 0, 0, 0, 0, -1, 0]
+inhibit	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -2]
+inhibited	-0.4	0.4899	[0, 0, -1, 0, -1, -1, 0, -1, 0, 0]
+inhibiting	-0.4	1.42829	[1, -1, -1, -1, -2, -1, 2, -2, 2, -1]
+inhibition	-1.5	0.67082	[-1, -1, -1, -1, -2, -1, -1, -2, -2, -3]
+inhibitions	-0.8	0.74833	[-2, -1, -2, 0, 0, 0, 0, -1, -1, -1]
+inhibitive	-1.4	0.4899	[-2, -2, -1, -1, -2, -1, -2, -1, -1, -1]
+inhibitor	-0.3	1.00499	[-2, 1, 1, -1, 1, 0, -1, -1, 0, -1]
+inhibitors	-1.0	0.7746	[-1, 0, -2, -1, -2, -2, 0, 0, -1, -1]
+inhibitory	-1.0	0.7746	[0, -1, -2, -2, -1, -2, 0, 0, -1, -1]
+inhibits	-0.9	0.53852	[-1, -1, -2, -1, -1, 0, -1, -1, -1, 0]
+injured	-1.7	0.64031	[-2, -1, -1, -1, -2, -1, -2, -2, -3, -2]
+injury	-1.8	0.6	[-2, -2, -1, -2, -1, -1, -2, -3, -2, -2]
+injustice	-2.7	0.64031	[-3, -2, -3, -4, -3, -3, -2, -2, -3, -2]
+innocence	1.6	0.91652	[3, 1, 1, 1, 2, 2, 0, 3, 2, 1]
+innocency	1.9	0.83066	[3, 1, 2, 0, 2, 2, 2, 3, 2, 2]
+innocent	1.4	1.2	[1, -1, 2, 2, 2, 0, 1, 3, 3, 1]
+innocenter	0.9	1.37477	[1, 1, 1, 2, 2, 1, 1, -3, 1, 2]
+innocently	1.4	0.8	[0, 2, 1, 1, 1, 1, 3, 2, 2, 1]
+innocents	1.1	1.04403	[0, 0, 2, 2, 2, -1, 1, 1, 2, 2]
+innovate	2.2	0.74833	[2, 4, 3, 2, 2, 1, 2, 2, 2, 2]
+innovates	2.0	0.89443	[2, 2, 2, 0, 1, 3, 3, 2, 3, 2]
+innovation	1.6	0.91652	[1, 0, 3, 2, 1, 2, 3, 2, 1, 1]
+innovative	1.9	0.83066	[1, 1, 2, 1, 2, 4, 2, 2, 2, 2]
+inquisition	-1.2	1.249	[-2, 1, -1, 0, 0, -3, -1, -3, -2, -1]
+inquisitive	0.7	1.18743	[2, 1, 1, 2, -2, -1, 1, 1, 1, 1]
+insane	-1.7	0.78102	[-2, 0, -2, -1, -2, -3, -2, -2, -1, -2]
+insanity	-2.7	1.00499	[-2, -4, -1, -1, -3, -4, -3, -3, -3, -3]
+insecure	-1.8	0.74833	[-1, -2, -2, -1, -3, -2, -3, -2, -1, -1]
+insecurely	-1.4	0.66332	[-3, -1, -1, -1, -2, -1, -2, -1, -1, -1]
+insecureness	-1.8	0.87178	[-1, -1, -1, -3, -3, -3, -2, -2, -1, -1]
+insecurities	-1.8	0.6	[-3, -2, -2, -2, -1, -2, -1, -1, -2, -2]
+insecurity	-1.8	0.74833	[-2, -2, -2, -1, -3, -3, -2, -1, -1, -1]
+insensitive	-0.9	1.81384	[2, -3, -2, -1, 2, -3, -2, 1, -1, -2]
+insensitivity	-1.8	0.6	[-2, -2, -1, -3, -2, -2, -1, -2, -1, -2]
+insignificant	-1.4	0.8	[-3, -2, -1, -2, -1, -2, 0, -1, -1, -1]
+insincere	-1.8	0.6	[-2, -1, -2, -1, -2, -2, -2, -2, -1, -3]
+insincerely	-1.9	0.7	[-2, -1, -2, -2, -1, -3, -2, -3, -1, -2]
+insincerity	-1.4	1.35647	[-1, -1, -3, -2, -1, 2, -2, -1, -2, -3]
+insipid	-2.0	0.7746	[-1, -2, -2, -1, -3, -3, -3, -2, -2, -1]
+inspiration	2.4	0.8	[3, 3, 3, 3, 1, 3, 1, 3, 2, 2]
+inspirational	2.3	0.64031	[2, 3, 2, 3, 2, 3, 2, 3, 1, 2]
+inspirationally	2.3	0.64031	[3, 2, 2, 3, 3, 1, 2, 2, 3, 2]
+inspirations	2.1	0.53852	[2, 2, 2, 2, 1, 2, 2, 3, 3, 2]
+inspirator	1.9	1.22066	[2, 2, 3, 0, 3, 4, 0, 2, 1, 2]
+inspirators	1.2	0.74833	[3, 1, 1, 2, 1, 1, 1, 1, 0, 1]
+inspiratory	1.5	0.67082	[2, 2, 3, 1, 1, 1, 1, 1, 2, 1]
+inspire	2.7	0.78102	[2, 3, 3, 3, 3, 3, 3, 1, 4, 2]
+inspired	2.2	0.87178	[3, 2, 1, 3, 1, 1, 3, 2, 3, 3]
+inspirer	2.2	1.07703	[3, 2, 2, 4, 0, 2, 3, 1, 3, 2]
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+inspires	1.9	1.04403	[2, 2, 2, 4, 0, 2, 3, 1, 1, 2]
+inspiring	1.8	1.07703	[2, 2, 2, -1, 2, 3, 2, 2, 1, 3]
+inspiringly	2.6	0.4899	[2, 3, 3, 2, 3, 3, 2, 3, 2, 3]
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+inspirited	1.3	1.18743	[2, 2, 0, 0, 3, 0, 2, 0, 3, 1]
+inspiriting	1.8	0.4	[1, 2, 1, 2, 2, 2, 2, 2, 2, 2]
+inspiritingly	2.1	1.44568	[3, 2, 2, 2, 4, 1, -1, 3, 4, 1]
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+insulted	-2.3	0.45826	[-2, -2, -2, -2, -3, -2, -2, -2, -3, -3]
+insulter	-2.0	0.63246	[-2, -1, -2, -2, -1, -3, -3, -2, -2, -2]
+insulters	-2.0	0.44721	[-2, -3, -2, -2, -2, -2, -2, -1, -2, -2]
+insulting	-2.2	0.74833	[-3, -2, -3, -3, -2, -3, -1, -2, -2, -1]
+insultingly	-2.3	0.78102	[-3, -3, -1, -2, -2, -3, -2, -1, -3, -3]
+insults	-1.8	0.6	[-2, -3, -2, -2, -1, -1, -1, -2, -2, -2]
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+intellectively	0.8	0.9798	[0, 0, 1, 1, 0, 3, 0, 1, 2, 0]
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+intellectualizing	0.8	1.77764	[0, 1, 2, 1, 0, 2, 2, -4, 2, 2]
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+intelligibly	1.2	0.87178	[1, 2, 1, 2, 1, -1, 2, 2, 1, 1]
+intense	0.3	0.45826	[0, 1, 1, 0, 0, 0, 0, 0, 1, 0]
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+interested	1.7	0.45826	[2, 1, 2, 2, 1, 2, 2, 2, 1, 2]
+interestedly	1.5	0.67082	[2, 2, 2, 1, 2, 1, 2, 1, 0, 2]
+interesting	1.7	0.78102	[1, 2, 1, 3, 1, 1, 1, 3, 2, 2]
+interestingly	1.7	0.45826	[2, 2, 2, 1, 2, 1, 1, 2, 2, 2]
+interestingness	1.8	0.87178	[2, 3, 1, 3, 1, 3, 2, 1, 1, 1]
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+interrogated	-1.6	1.0198	[-3, -1, -1, -1, -2, -1, -3, -1, -3, 0]
+interrupt	-1.4	0.4899	[-2, -1, -1, -1, -2, -2, -1, -1, -2, -1]
+interrupted	-1.2	0.6	[-1, -2, -1, 0, -1, -1, -2, -1, -2, -1]
+interrupter	-1.1	0.53852	[-1, -2, -1, 0, -1, -1, -1, -1, -2, -1]
+interrupters	-1.3	0.45826	[-1, -2, -1, -1, -1, -1, -2, -1, -2, -1]
+interruptible	-1.3	1.00499	[-2, -1, 0, -2, 0, -3, -2, -1, 0, -2]
+interrupting	-1.2	0.4	[-2, -1, -1, -1, -1, -2, -1, -1, -1, -1]
+interruption	-1.5	0.67082	[-1, -1, -2, -3, -2, -1, -1, -1, -2, -1]
+interruptions	-1.7	0.45826	[-2, -2, -2, -2, -2, -1, -1, -1, -2, -2]
+interruptive	-1.4	0.66332	[-2, -2, -1, -2, -2, 0, -1, -1, -1, -2]
+interruptor	-1.3	0.64031	[-2, -1, -1, -1, 0, -2, -2, -2, -1, -1]
+interrupts	-1.3	0.64031	[-1, -1, -2, -1, -1, -1, -1, -1, -3, -1]
+intimidate	-0.8	1.46969	[-1, -2, -2, -2, -2, -1, 2, 1, 1, -2]
+intimidated	-1.9	0.7	[-2, -1, -3, -3, -1, -2, -2, -1, -2, -2]
+intimidates	-1.3	0.78102	[-2, -1, -1, -1, -3, -2, -1, -1, -1, 0]
+intimidating	-1.9	1.04403	[0, -2, -1, -3, -2, -1, -1, -3, -3, -3]
+intimidatingly	-1.1	1.64012	[2, -2, -3, -1, -2, -2, 2, -2, -1, -2]
+intimidation	-1.8	1.249	[1, -2, -3, -1, -2, -3, -1, -3, -1, -3]
+intimidations	-1.4	1.49666	[1, -2, -2, -2, -1, -1, -1, -4, 1, -3]
+intimidator	-1.6	0.4899	[-1, -1, -2, -2, -1, -2, -2, -1, -2, -2]
+intimidators	-1.6	0.8	[-1, -1, -3, -2, -1, -1, -3, -1, -2, -1]
+intimidatory	-1.1	1.22066	[-1, -2, -3, -1, -1, -1, -2, 2, -1, -1]
+intricate	0.6	0.66332	[1, 0, 2, 1, 0, 1, 1, 0, 0, 0]
+intrigues	0.9	0.9434	[2, -1, 2, 1, 2, 0, 1, 1, 0, 1]
+invigorate	1.9	0.83066	[2, 2, 2, 0, 2, 3, 3, 2, 1, 2]
+invigorated	0.8	1.8868	[-2, 3, 2, 2, -2, -2, 2, 2, 1, 2]
+invigorates	2.1	0.53852	[3, 2, 3, 2, 1, 2, 2, 2, 2, 2]
+invigorating	2.1	0.7	[2, 1, 1, 3, 3, 3, 2, 2, 2, 2]
+invigoratingly	2.0	0.63246	[2, 2, 1, 2, 1, 3, 2, 2, 2, 3]
+invigoration	1.5	1.36015	[2, 2, 1, -2, 1, 3, 3, 2, 1, 2]
+invigorations	1.2	0.87178	[1, -1, 2, 2, 1, 1, 2, 1, 2, 1]
+invigorator	1.1	1.3	[3, 1, 0, 2, 2, -2, 1, 1, 2, 1]
+invigorators	1.2	0.87178	[1, 1, 1, 1, 3, 2, 0, 0, 1, 2]
+invincible	2.2	1.77764	[4, 1, 3, 2, 4, 1, 4, -1, 0, 4]
+invite	0.6	0.66332	[2, 1, 1, 0, 0, 0, 0, 1, 1, 0]
+inviting	1.3	0.45826	[1, 1, 1, 2, 1, 2, 2, 1, 1, 1]
+invulnerable	1.3	1.73494	[2, 3, 4, 2, 0, 3, 0, 1, -2, 0]
+irate	-2.9	0.53852	[-3, -3, -3, -2, -3, -4, -3, -3, -2, -3]
+ironic	-0.5	1.28452	[1, 0, 0, 0, 0, 0, -4, -1, -1, 0]
+irony	-0.2	1.07703	[-1, 0, -3, 0, 0, 0, 1, 0, 1, 0]
+irrational	-1.4	0.4899	[-1, -1, -1, -2, -2, -2, -1, -1, -2, -1]
+irrationalism	-1.5	0.5	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -2]
+irrationalist	-2.1	0.9434	[-1, -4, -2, -2, -3, -3, -2, -1, -1, -2]
+irrationalists	-1.5	0.92195	[-2, -2, -1, -2, -2, 1, -1, -2, -2, -2]
+irrationalities	-1.5	0.80623	[-2, -2, 0, -1, -1, -1, -2, -3, -1, -2]
+irrationality	-1.7	0.9	[-3, -3, -1, -2, -1, -1, -1, -1, -3, -1]
+irrationally	-1.6	0.4899	[-1, -2, -1, -2, -1, -2, -2, -2, -1, -2]
+irrationals	-1.1	0.83066	[-2, 0, -1, 0, -1, -1, -3, -1, -1, -1]
+irresistible	1.4	2.2	[2, 3, 2, 3, 4, 4, 1, -1, -2, -2]
+irresolute	-1.4	0.66332	[-2, -2, -1, -2, -1, -1, -1, -2, -2, 0]
+irresponsible	-1.9	0.3	[-2, -2, -2, -2, -2, -2, -1, -2, -2, -2]
+irreversible	-0.8	0.87178	[-2, -2, 0, -1, 0, 0, 0, -1, -2, 0]
+irritabilities	-1.7	0.64031	[-2, -2, -2, -1, -1, -1, -1, -2, -3, -2]
+irritability	-1.4	1.28062	[-2, -1, -2, -1, 2, -2, -2, -2, -1, -3]
+irritable	-2.1	0.7	[-2, -2, -3, -1, -2, -1, -3, -2, -3, -2]
+irritableness	-1.7	0.64031	[-2, -2, -2, -1, -2, -1, -1, -3, -1, -2]
+irritably	-1.8	0.6	[-2, -2, -1, -1, -3, -2, -1, -2, -2, -2]
+irritant	-2.3	0.78102	[-3, -3, -3, -3, -3, -1, -2, -2, -2, -1]
+irritants	-2.1	0.83066	[-2, -3, -1, -4, -2, -1, -2, -2, -2, -2]
+irritate	-1.8	0.6	[-3, -2, -2, -2, -1, -2, -1, -2, -1, -2]
+irritated	-2.0	0.63246	[-1, -2, -2, -2, -3, -2, -2, -3, -1, -2]
+irritates	-1.7	0.78102	[-1, -2, -1, -1, -3, -2, -2, -3, -1, -1]
+irritating	-2.0	0.63246	[-2, -2, -2, -1, -1, -3, -2, -2, -3, -2]
+irritatingly	-2.0	0.44721	[-2, -2, -2, -3, -1, -2, -2, -2, -2, -2]
+irritation	-2.3	0.78102	[-3, -2, -2, -2, -1, -3, -3, -1, -3, -3]
+irritations	-1.5	0.67082	[-2, -2, -1, -1, -1, -1, -1, -2, -3, -1]
+irritative	-2.0	0.63246	[-3, -2, -3, -2, -1, -2, -2, -2, -1, -2]
+isolatable	0.2	1.249	[1, 0, -2, 0, -1, -1, 2, 0, 2, 1]
+isolate	-0.8	0.74833	[-1, -1, -1, 0, 0, 0, 0, -2, -1, -2]
+isolated	-1.3	0.64031	[-1, -1, -1, -1, -1, -1, -2, -1, -3, -1]
+isolates	-1.3	0.64031	[-1, -1, -1, -1, -2, -1, -3, -1, -1, -1]
+isolation	-1.7	0.78102	[-1, -3, -1, -2, -2, -1, -3, -1, -2, -1]
+isolationism	0.4	1.62481	[2, 0, -1, -2, -1, 3, 0, 2, -1, 2]
+isolationist	0.7	1.55242	[2, 0, 0, -1, -1, 3, 0, 2, -1, 3]
+isolations	-0.5	1.11803	[-1, -2, -2, -1, 1, 1, -1, 0, 1, -1]
+isolator	-0.4	0.66332	[0, 0, -1, 0, -1, 0, -2, 0, 0, 0]
+isolators	-0.4	1.42829	[-2, -1, -1, -2, 2, 2, -1, 1, -1, -1]
+itchy	-1.1	0.53852	[-1, -1, -1, -1, -2, 0, -1, -1, -2, -1]
+jackass	-1.8	1.07703	[-1, 0, -3, -2, -2, -3, 0, -2, -2, -3]
+jackasses	-2.8	0.9798	[-2, -2, -4, -3, -4, -4, -3, -1, -2, -3]
+jaded	-1.6	0.66332	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -3]
+jailed	-2.2	0.87178	[-4, -3, -2, -2, -1, -2, -2, -3, -1, -2]
+jaunty	1.2	0.6	[2, 1, 0, 2, 1, 1, 1, 2, 1, 1]
+jealous	-2.0	0.63246	[-2, -2, -3, -2, -3, -2, -1, -1, -2, -2]
+jealousies	-2.0	0.63246	[-2, -3, -2, -1, -2, -3, -2, -1, -2, -2]
+jealously	-2.0	0.89443	[-1, -3, -1, -4, -2, -2, -1, -2, -2, -2]
+jealousness	-1.7	0.45826	[-1, -2, -2, -2, -2, -1, -1, -2, -2, -2]
+jealousy	-1.3	1.73494	[-2, -3, -2, -2, -2, 2, -3, -1, 2, -2]
+jeopardy	-2.1	0.9434	[-3, -3, -3, -1, -1, -3, -2, -1, -1, -3]
+jerk	-1.4	0.8	[-1, -1, -1, -2, -3, 0, -2, -1, -1, -2]
+jerked	-0.8	0.74833	[0, -1, -1, 0, -2, -1, 0, -1, 0, -2]
+jerks	-1.1	1.51327	[-2, -2, -1, -2, -1, 0, -2, 3, -2, -2]
+jewel	1.5	1.20416	[1, 3, 2, 0, 2, 1, 3, 0, 3, 0]
+jewels	2.0	1.34164	[3, 1, 0, 0, 4, 3, 3, 2, 3, 1]
+jocular	1.2	1.249	[0, 1, 2, -2, 1, 2, 2, 2, 2, 2]
+join	1.2	0.74833	[2, 2, 1, 2, 1, 0, 1, 2, 0, 1]
+joke	1.2	0.74833	[1, 1, 1, 1, 1, 1, 0, 2, 1, 3]
+joked	1.3	0.64031	[1, 1, 2, 2, 0, 2, 1, 1, 2, 1]
+joker	0.5	0.92195	[1, 1, -1, 1, 2, -1, 1, 1, 0, 0]
+jokes	1.0	0.7746	[1, 1, -1, 1, 1, 2, 1, 1, 2, 1]
+jokester	1.5	0.67082	[2, 2, 2, 2, 1, 1, 0, 1, 2, 2]
+jokesters	0.9	0.83066	[0, 0, 2, 1, 1, 2, 2, 0, 1, 0]
+jokey	1.1	0.3	[1, 1, 2, 1, 1, 1, 1, 1, 1, 1]
+joking	0.9	0.53852	[1, 2, 1, 1, 1, 0, 1, 1, 0, 1]
+jollied	2.4	0.66332	[3, 3, 2, 2, 3, 3, 2, 2, 1, 3]
+jollier	2.4	0.4899	[2, 2, 3, 3, 2, 2, 2, 3, 2, 3]
+jollies	2.0	0.63246	[1, 2, 3, 2, 2, 2, 1, 2, 2, 3]
+jolliest	2.9	0.7	[3, 3, 2, 4, 3, 2, 3, 4, 2, 3]
+jollification	2.2	0.74833	[2, 3, 3, 1, 2, 1, 3, 2, 3, 2]
+jollifications	2.0	0.7746	[2, 3, 2, 2, 2, 2, 3, 2, 0, 2]
+jollify	2.1	0.53852	[2, 3, 2, 2, 2, 2, 2, 3, 1, 2]
+jollily	2.7	0.64031	[3, 3, 3, 3, 3, 3, 3, 1, 3, 2]
+jolliness	2.5	0.67082	[3, 1, 2, 3, 2, 3, 3, 3, 2, 3]
+jollities	1.7	0.64031	[2, 1, 2, 2, 1, 2, 2, 3, 1, 1]
+jollity	1.8	1.6	[3, 2, 1, 1, 4, 3, 1, 2, 3, -2]
+jolly	2.3	1.00499	[4, 3, 3, 1, 1, 1, 3, 2, 3, 2]
+jollying	2.3	0.64031	[2, 3, 3, 1, 3, 3, 2, 2, 2, 2]
+jovial	1.9	0.53852	[2, 2, 1, 2, 1, 2, 3, 2, 2, 2]
+joy	2.8	0.74833	[3, 2, 3, 4, 3, 3, 3, 1, 3, 3]
+joyance	2.3	0.9	[1, 3, 4, 2, 2, 1, 2, 3, 2, 3]
+joyed	2.9	0.3	[3, 3, 3, 3, 3, 3, 3, 2, 3, 3]
+joyful	2.9	0.53852	[3, 2, 3, 3, 2, 3, 4, 3, 3, 3]
+joyfuller	2.4	0.66332	[2, 4, 3, 2, 2, 2, 3, 2, 2, 2]
+joyfully	2.5	0.67082	[2, 2, 3, 3, 2, 2, 3, 4, 2, 2]
+joyfulness	2.7	1.00499	[4, 3, 1, 3, 3, 3, 4, 2, 1, 3]
+joying	2.5	0.67082	[2, 2, 1, 3, 3, 3, 3, 3, 3, 2]
+joyless	-2.5	0.67082	[-1, -2, -3, -3, -3, -3, -2, -2, -3, -3]
+joylessly	-1.7	1.1	[-2, -2, -3, -3, -2, -1, 1, -2, -1, -2]
+joylessness	-2.7	0.9	[-4, -3, -3, -3, -3, -3, -3, -1, -1, -3]
+joyous	3.1	0.7	[3, 4, 3, 2, 4, 3, 3, 4, 2, 3]
+joyously	2.9	0.7	[2, 3, 4, 3, 4, 2, 2, 3, 3, 3]
+joyousness	2.8	0.74833	[3, 3, 1, 3, 3, 3, 4, 2, 3, 3]
+joypop	-0.2	1.93907	[-3, 1, 2, 2, -3, -1, -2, -1, 1, 2]
+joypoppers	-0.1	1.22066	[2, -1, 1, -1, -1, 1, 1, 0, -2, -1]
+joyridden	0.6	1.8	[-2, -1, 4, 0, 0, 2, 1, -1, 0, 3]
+joyride	1.1	1.22066	[-1, 1, 2, 0, 2, 0, 2, 2, 3, 0]
+joyrider	0.7	1.26886	[2, -2, 1, 2, 0, 2, -1, 1, 1, 1]
+joyriders	1.3	1.18743	[1, 0, 0, 1, 4, 3, 1, 1, 1, 1]
+joyrides	0.8	1.32665	[2, -2, 1, 2, 0, 2, -1, 1, 2, 1]
+joyriding	0.9	1.04403	[1, -1, 1, 1, 0, 2, 0, 1, 3, 1]
+joyrode	1.0	1.48324	[4, 0, -2, 0, 2, 1, 2, 1, 1, 1]
+joys	2.2	0.4	[2, 2, 2, 2, 2, 3, 2, 3, 2, 2]
+joystick	0.7	0.78102	[1, 0, 2, 2, 0, 0, 1, 1, 0, 0]
+joysticks	0.2	0.4	[0, 0, 0, 0, 1, 0, 0, 1, 0, 0]
+jubilant	3.0	0.63246	[3, 3, 4, 3, 3, 2, 3, 4, 2, 3]
+jumpy	-1.0	0.63246	[0, 0, -2, -1, -1, -1, -1, -1, -2, -1]
+justice	2.4	1.0198	[3, 2, 1, 2, 3, 2, 4, 4, 2, 1]
+justifiably	1.0	0.7746	[0, 1, 0, 1, 1, 1, 0, 2, 2, 2]
+justified	1.7	0.64031	[1, 2, 2, 3, 1, 1, 1, 2, 2, 2]
+keen	1.5	0.67082	[1, 1, 3, 1, 2, 1, 1, 2, 2, 1]
+keened	0.3	1.00499	[-2, 0, 1, 0, 1, 1, 0, 2, 0, 0]
+keener	0.5	1.20416	[-1, -1, 0, -1, 2, 1, 2, 2, 1, 0]
+keeners	0.6	0.4899	[1, 0, 0, 1, 1, 0, 1, 1, 0, 1]
+keenest	1.9	0.83066	[3, 3, 1, 1, 3, 2, 2, 1, 2, 1]
+keening	-0.7	1.41774	[0, -3, -1, -1, -3, 1, -1, 1, 1, -1]
+keenly	1.0	0.7746	[2, 1, 1, 0, 1, 0, 2, 1, 2, 0]
+keenness	1.4	0.4899	[1, 1, 2, 2, 1, 1, 1, 2, 2, 1]
+keens	0.1	1.22066	[1, -3, 0, 0, 0, 2, 1, 0, 0, 0]
+kewl	1.3	0.45826	[2, 1, 1, 1, 2, 1, 2, 1, 1, 1]
+kidding	0.4	0.8	[0, 1, 0, -1, 1, 1, 1, 1, -1, 1]
+kill	-3.7	0.45826	[-4, -4, -4, -4, -3, -4, -4, -4, -3, -3]
+killdeer	-1.1	1.04403	[-3, 0, 0, -1, -2, 0, -1, -2, -2, 0]
+killdeers	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
+killdees	-0.6	0.66332	[-2, 0, 0, 0, -1, 0, -1, -1, -1, 0]
+killed	-3.5	0.67082	[-3, -3, -2, -4, -4, -4, -3, -4, -4, -4]
+killer	-3.3	0.64031	[-4, -4, -3, -3, -4, -4, -3, -3, -2, -3]
+killers	-3.3	0.45826	[-3, -3, -4, -3, -3, -3, -4, -3, -4, -3]
+killick	0.1	0.3	[0, 1, 0, 0, 0, 0, 0, 0, 0, 0]
+killie	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
+killifish	-0.1	0.7	[0, 0, 0, 0, -2, 0, 0, 0, 1, 0]
+killifishes	-0.1	0.3	[0, -1, 0, 0, 0, 0, 0, 0, 0, 0]
+killing	-3.4	1.2	[-4, 0, -4, -4, -4, -3, -4, -3, -4, -4]
+killingly	-2.6	1.0198	[-3, -2, -4, -2, -1, -3, -4, -3, -3, -1]
+killings	-3.5	0.67082	[-4, -3, -4, -4, -2, -3, -4, -4, -3, -4]
+killjoy	-2.1	0.83066	[-1, -2, -3, -2, -1, -3, -2, -1, -3, -3]
+killjoys	-1.7	0.9	[-1, -3, -3, -1, -2, -1, -2, 0, -2, -2]
+killock	-0.3	0.64031	[0, 0, 0, 0, -2, 0, 0, 0, -1, 0]
+killocks	-0.4	0.66332	[0, 0, 0, -2, -1, 0, -1, 0, 0, 0]
+kills	-2.5	0.92195	[-2, -3, -2, -3, -4, -1, -3, -3, -1, -3]
+kind	2.4	0.66332	[2, 2, 3, 3, 2, 3, 3, 2, 1, 3]
+kinder	2.2	0.6	[3, 3, 3, 2, 2, 2, 2, 1, 2, 2]
+kindly	2.2	0.4	[2, 2, 2, 3, 2, 2, 2, 2, 2, 3]
+kindness	2.0	0.63246	[2, 1, 3, 3, 2, 1, 2, 2, 2, 2]
+kindnesses	2.3	0.64031	[3, 1, 3, 2, 3, 2, 3, 2, 2, 2]
+kiss	1.8	1.6	[4, 0, 3, 3, 2, 0, 4, 2, 0, 0]
+kissable	2.0	0.89443	[2, 2, 2, 2, 4, 2, 3, 1, 1, 1]
+kissably	1.9	1.04403	[1, 3, 4, 1, 2, 1, 3, 2, 1, 1]
+kissed	1.6	1.11355	[2, 4, 1, 1, 1, 2, 3, 0, 1, 1]
+kisser	1.7	1.34536	[2, 4, 1, 2, -1, 2, 3, 0, 2, 2]
+kissers	1.5	0.80623	[1, 1, 1, 0, 2, 2, 3, 2, 1, 2]
+kisses	2.3	0.9	[2, 4, 2, 2, 1, 2, 4, 2, 2, 2]
+kissing	2.7	0.78102	[3, 3, 4, 1, 3, 2, 2, 3, 3, 3]
+kissy	1.8	0.6	[2, 2, 2, 3, 1, 1, 2, 2, 1, 2]
+kudos	2.3	0.64031	[2, 4, 2, 3, 2, 2, 2, 2, 2, 2]
+lack	-1.3	0.45826	[-1, -1, -1, -1, -2, -1, -2, -1, -1, -2]
+lackadaisical	-1.6	0.66332	[-1, -1, -2, -1, -2, -2, -3, -1, -2, -1]
+lag	-1.4	0.66332	[-1, -1, -1, -1, -1, -3, -1, -2, -2, -1]
+lagged	-1.2	0.6	[-2, -2, -1, -2, -1, -1, 0, -1, -1, -1]
+lagging	-1.1	0.83066	[-2, -2, -2, -1, 0, 0, -1, 0, -1, -2]
+lags	-1.5	0.67082	[-2, -1, -1, -2, -1, -3, -1, -2, -1, -1]
+laidback	0.5	1.28452	[1, -1, 1, -2, -1, 1, 2, 1, 1, 2]
+lame	-1.8	0.74833	[-1, -3, -1, -2, -2, -1, -2, -3, -1, -2]
+lamebrain	-1.6	0.91652	[-3, -2, -1, 0, -3, -1, -1, -2, -2, -1]
+lamebrained	-2.5	0.67082	[-3, -3, -2, -2, -2, -2, -4, -3, -2, -2]
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+lown	0.9	1.13578	[2, 2, 1, -1, 0, 1, 2, -1, 1, 2]
+lowness	-1.3	0.45826	[-1, -2, -2, -1, -1, -2, -1, -1, -1, -1]
+lowrider	-0.2	0.4	[0, 0, 0, -1, -1, 0, 0, 0, 0, 0]
+lowriders	0.1	0.53852	[0, 0, 0, 0, 1, 0, -1, 0, 1, 0]
+lows	-0.8	0.9798	[0, -1, -1, -1, 0, 1, -3, -1, -1, -1]
+lowse	-0.7	0.78102	[0, -1, 1, -1, -1, -1, 0, -1, -2, -1]
+loyal	2.1	0.7	[3, 2, 1, 1, 2, 2, 3, 2, 3, 2]
+loyalism	1.0	0.89443	[1, 2, 1, -1, 0, 1, 2, 1, 1, 2]
+loyalisms	0.9	0.83066	[2, 0, 0, 1, 1, 0, 2, 2, 1, 0]
+loyalist	1.5	0.92195	[1, 0, 2, 2, 3, 0, 2, 2, 1, 2]
+loyalists	1.1	0.83066	[1, 1, 1, 3, 0, 2, 1, 0, 1, 1]
+loyally	2.1	0.7	[3, 2, 2, 2, 1, 3, 1, 2, 3, 2]
+loyalties	1.9	0.7	[3, 1, 2, 2, 2, 3, 2, 1, 1, 2]
+loyalty	2.5	0.67082	[1, 3, 3, 3, 3, 2, 2, 2, 3, 3]
+luck	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
+lucked	1.9	0.7	[2, 2, 2, 1, 1, 2, 3, 3, 1, 2]
+luckie	1.6	0.66332	[1, 1, 1, 2, 2, 1, 1, 2, 2, 3]
+luckier	1.9	0.7	[1, 3, 1, 2, 2, 1, 2, 3, 2, 2]
+luckiest	2.9	0.7	[3, 3, 4, 2, 2, 4, 3, 3, 2, 3]
+luckily	2.3	0.45826	[2, 2, 3, 2, 2, 3, 2, 2, 2, 3]
+luckiness	1.0	1.61245	[2, 2, 1, -2, 3, 1, 1, 2, 2, -2]
+lucking	1.2	0.6	[2, 1, 1, 0, 1, 1, 1, 2, 2, 1]
+luckless	-1.3	0.45826	[-2, -1, -2, -1, -1, -1, -2, -1, -1, -1]
+lucks	1.6	0.91652	[0, 3, 1, 1, 3, 2, 2, 1, 2, 1]
+lucky	1.8	0.74833	[2, 1, 1, 1, 3, 2, 1, 2, 2, 3]
+ludicrous	-1.5	1.36015	[2, -2, -2, -1, -1, -1, -3, -3, -2, -2]
+ludicrously	-0.2	1.83303	[3, -1, 0, -2, -1, 0, 3, -3, -1, 0]
+ludicrousness	-1.9	1.57797	[-1, 2, -2, -3, -2, -2, -3, -4, -1, -3]
+lugubrious	-2.1	1.37477	[-3, -2, -3, -3, -3, 1, -2, -3, 0, -3]
+lulz	2.0	1.0	[2, 2, 2, 3, 4, 1, 3, 1, 1, 1]
+lunatic	-2.2	1.32665	[-2, -3, -4, -2, -3, -2, -1, -3, 1, -3]
+lunatics	-1.6	1.95959	[-4, -2, -3, -4, -2, 2, -1, -3, 1, 0]
+lurk	-0.8	0.87178	[-1, -1, 0, -3, -1, 0, -1, 0, -1, 0]
+lurking	-0.5	1.11803	[1, -1, -1, 0, -1, -2, 1, -2, 1, -1]
+lurks	-0.9	1.04403	[-1, -1, -1, -2, -2, -1, -1, -1, 2, -1]
+lying	-2.4	0.8	[-2, -4, -3, -1, -2, -2, -3, -2, -2, -3]
+mad	-2.2	0.74833	[-3, -3, -1, -1, -2, -3, -2, -2, -3, -2]
+maddening	-2.2	0.74833	[-3, -3, -1, -1, -3, -2, -2, -3, -2, -2]
+madder	-1.2	1.16619	[-2, 0, -3, 0, 0, -1, -3, -1, -2, 0]
+maddest	-2.8	1.16619	[-4, -4, -4, -4, -1, -3, -2, -1, -2, -3]
+madly	-1.7	1.1	[-2, 0, -2, -2, -2, -1, -4, -2, 0, -2]
+madness	-1.9	0.53852	[-1, -2, -1, -3, -2, -2, -2, -2, -2, -2]
+magnific	2.3	1.1	[2, 2, 0, 2, 4, 4, 2, 2, 3, 2]
+magnifical	2.4	1.28062	[1, 4, 1, 2, 4, 3, 1, 1, 4, 3]
+magnifically	2.4	1.2	[3, 3, 3, 2, 4, 0, 1, 2, 2, 4]
+magnification	1.0	0.89443	[2, 3, 1, 0, 0, 1, 1, 1, 0, 1]
+magnifications	1.2	1.249	[-1, 0, 0, 2, 2, 2, 0, 2, 3, 2]
+magnificence	2.4	1.0198	[3, 2, 1, 3, 2, 1, 4, 4, 2, 2]
+magnificences	2.3	0.9	[3, 4, 3, 1, 3, 2, 1, 2, 2, 2]
+magnificent	2.9	0.7	[2, 4, 2, 4, 3, 3, 3, 3, 2, 3]
+magnificently	3.4	0.66332	[3, 3, 3, 4, 4, 2, 4, 4, 3, 4]
+magnifico	1.8	0.87178	[2, 1, 1, 2, 1, 1, 3, 3, 3, 1]
+magnificoes	1.4	0.8	[2, 2, 0, 2, 1, 1, 3, 1, 1, 1]
+mandatory	0.3	0.9	[1, 0, -1, 0, -1, 0, 1, 2, 0, 1]
+maniac	-2.1	0.7	[-1, -2, -2, -2, -3, -3, -1, -2, -2, -3]
+maniacal	-0.3	1.73494	[2, -1, -3, -3, 0, 2, -1, 1, 1, -1]
+maniacally	-1.7	0.78102	[-1, -2, -1, -2, -3, -2, -1, -3, -1, -1]
+maniacs	-1.2	1.8868	[-3, 1, -2, 1, -3, -2, 0, 2, -3, -3]
+manipulated	-1.6	0.4899	[-2, -1, -1, -2, -1, -2, -2, -1, -2, -2]
+manipulating	-1.5	0.80623	[-1, -1, -1, -2, -2, -1, -2, -2, -3, 0]
+manipulation	-1.2	1.72047	[2, -3, -2, -3, -1, -1, -2, 2, -2, -2]
+marvel	1.8	0.6	[2, 1, 1, 2, 1, 2, 3, 2, 2, 2]
+marvelous	2.9	0.7	[2, 2, 3, 2, 3, 3, 4, 3, 4, 3]
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+masochism	-1.6	1.11355	[-1, 0, -2, -2, -2, -2, 0, -4, -1, -2]
+masochisms	-1.1	1.57797	[3, -3, -2, -2, -1, -1, -2, -1, 0, -2]
+masochist	-1.7	0.9	[-1, 0, -3, -1, -2, -2, -2, -2, -1, -3]
+masochistic	-2.2	1.16619	[-1, -1, -1, -2, -3, -2, -4, -3, -4, -1]
+masochistically	-1.6	1.35647	[-1, -1, -3, -3, -3, -3, 0, -2, 1, -1]
+masochists	-1.2	1.07703	[1, -2, 0, -2, -3, -1, -2, -1, -1, -1]
+masterpiece	3.1	0.83066	[3, 4, 4, 4, 2, 2, 2, 4, 3, 3]
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+meaningless	-1.9	0.7	[-1, -2, -2, -2, -1, -1, -2, -3, -3, -2]
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+meh	-0.3	0.78102	[-1, 0, -1, 0, -1, -1, 1, 0, 1, -1]
+melancholia	-0.5	1.28452	[0, -2, -2, 0, 1, -1, 2, -2, 0, -1]
+melancholiac	-2.0	0.63246	[-2, -2, -3, -2, -2, -3, -1, -1, -2, -2]
+melancholias	-1.6	0.8	[-1, -2, -3, -2, 0, -2, -1, -1, -2, -2]
+melancholic	-0.3	1.18743	[0, 2, -2, 0, 1, -1, 0, -2, 0, -1]
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+melancholies	-1.1	0.83066	[-1, 0, -1, 0, -3, -1, -2, -1, -1, -1]
+melancholy	-1.9	1.13578	[-3, -2, -3, -2, -3, -2, -2, 1, -1, -2]
+menace	-2.2	0.87178	[-3, -3, -2, -1, -1, -2, -3, -1, -3, -3]
+menaced	-1.7	1.48661	[-3, -2, -2, -3, -3, -1, 1, -3, 1, -2]
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+merit	1.8	0.74833	[2, 2, 2, 2, 0, 2, 3, 2, 2, 1]
+merited	1.4	0.4899	[1, 2, 2, 1, 1, 1, 2, 1, 2, 1]
+meriting	1.1	1.13578	[1, 2, 1, -2, 1, 1, 2, 2, 1, 2]
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+meritoriously	1.3	1.95192	[3, -1, 3, -2, 2, 0, -1, 3, 3, 3]
+meritoriousness	1.7	1.18743	[4, 1, 2, 1, 2, 0, 3, 2, 2, 0]
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+offend	-1.2	1.4	[-2, -2, -2, -2, -1, -2, -2, 1, 2, -2]
+offended	-1.0	1.41421	[-2, -2, -2, -2, -1, 0, -2, 2, 1, -2]
+offender	-1.5	1.28452	[-3, -2, -2, -2, -2, -2, -2, 1, 1, -2]
+offenders	-1.5	1.28452	[-2, -1, -2, -2, -2, -2, 2, -3, -2, -1]
+offending	-2.3	0.64031	[-2, -2, -3, -2, -2, -4, -2, -2, -2, -2]
+offends	-2.0	0.7746	[-3, -1, -1, -2, -2, -2, -3, -1, -2, -3]
+offense	-1.0	1.61245	[-2, 1, -1, -2, -2, -2, -3, 2, 1, -2]
+offenseless	0.7	1.79165	[3, 1, 0, 2, 1, 2, 1, 0, -4, 1]
+offenses	-1.5	1.5	[-1, -2, -2, -4, -1, -2, 1, -3, 1, -2]
+offensive	-2.0	1.48324	[-3, -3, -3, -2, -1, -2, 2, -2, -3, -3]
+offensively	-2.8	0.87178	[-2, -4, -3, -3, -2, -4, -4, -2, -2, -2]
+offensiveness	-2.3	0.45826	[-2, -2, -2, -2, -2, -3, -2, -3, -3, -2]
+offensives	-0.8	1.249	[0, 0, -1, -2, 0, 2, -2, -1, -2, -2]
+offline	-0.5	0.92195	[0, 0, 0, 0, -3, 0, -1, 0, -1, 0]
+ok	1.2	0.4	[1, 2, 1, 1, 1, 1, 2, 1, 1, 1]
+okay	0.9	0.53852	[1, 1, 0, 0, 1, 1, 1, 2, 1, 1]
+okays	2.1	1.13578	[1, 1, 1, 4, 3, 2, 2, 1, 2, 4]
+ominous	-1.4	1.49666	[-3, -2, -1, -2, -2, -1, -1, 1, 1, -4]
+once-in-a-lifetime	1.8	1.4	[4, 2, 1, 0, 1, 1, 4, 3, 2, 0]
+openness	1.4	0.8	[2, 1, 1, 2, 2, 1, 1, 1, 3, 0]
+opportune	1.7	0.78102	[2, 2, 0, 1, 2, 3, 2, 2, 1, 2]
+opportunely	1.5	1.0247	[1, 1, 4, 1, 2, 1, 1, 2, 2, 0]
+opportuneness	1.2	1.249	[0, 1, 2, 2, 2, 2, 2, 2, -2, 1]
+opportunism	0.4	1.11355	[-1, -1, 0, -1, 1, 2, 0, 1, 2, 1]
+opportunisms	0.2	1.4	[2, -1, 0, -1, 1, -2, 2, 2, -1, 0]
+opportunist	0.2	0.9798	[-1, -1, 0, -1, 0, 2, 0, 1, 1, 1]
+opportunistic	-0.1	2.11896	[-2, 1, -1, 0, -4, 2, -1, 4, 1, -1]
+opportunistically	0.9	1.51327	[1, -3, 1, 3, 2, 2, 1, 0, 1, 1]
+opportunists	0.3	1.34536	[0, -1, -1, 2, 1, 3, -1, -1, 1, 0]
+opportunities	1.6	0.4899	[1, 1, 2, 2, 2, 1, 2, 2, 1, 2]
+opportunity	1.8	0.6	[2, 2, 2, 2, 3, 1, 2, 1, 1, 2]
+oppressed	-2.1	0.53852	[-2, -2, -2, -1, -2, -2, -3, -2, -2, -3]
+oppressive	-1.7	1.34536	[-3, -2, -1, -2, -2, -2, -3, 2, -2, -2]
+optimal	1.5	0.67082	[1, 2, 1, 3, 1, 1, 1, 2, 2, 1]
+optimality	1.9	0.7	[3, 3, 2, 1, 2, 1, 2, 2, 1, 2]
+optimally	1.3	0.9	[0, 3, 0, 1, 1, 2, 1, 1, 2, 2]
+optimisation	1.6	0.8	[3, 1, 1, 1, 2, 1, 1, 3, 2, 1]
+optimisations	1.8	0.6	[3, 1, 1, 2, 1, 2, 2, 2, 2, 2]
+optimise	1.9	0.83066	[1, 2, 3, 2, 3, 3, 2, 1, 1, 1]
+optimised	1.7	1.26886	[2, 4, 1, 2, 1, 2, 3, 2, 1, -1]
+optimises	1.6	1.0198	[3, 1, 1, 1, 1, 3, 2, 0, 3, 1]
+optimising	1.7	1.00499	[1, 2, 3, 3, 1, 2, 1, 3, 0, 1]
+optimism	2.5	0.67082	[2, 2, 3, 3, 3, 4, 2, 2, 2, 2]
+optimisms	2.0	0.63246	[2, 3, 1, 3, 1, 2, 2, 2, 2, 2]
+optimist	2.4	0.4899	[3, 2, 3, 2, 3, 3, 2, 2, 2, 2]
+optimistic	1.3	1.48661	[2, 2, -3, 2, 2, 2, 1, 2, 1, 2]
+optimistically	2.1	0.53852	[3, 2, 2, 2, 3, 2, 1, 2, 2, 2]
+optimists	1.6	0.66332	[3, 2, 2, 1, 2, 1, 2, 1, 1, 1]
+optimization	1.6	0.8	[2, 3, 1, 1, 1, 2, 0, 2, 2, 2]
+optimizations	0.9	1.04403	[0, 2, 0, 2, 1, 0, 3, 1, 0, 0]
+optimize	2.2	0.87178	[2, 3, 3, 2, 1, 2, 4, 2, 2, 1]
+optimized	2.0	0.44721	[1, 3, 2, 2, 2, 2, 2, 2, 2, 2]
+optimizer	1.5	0.67082	[1, 3, 1, 1, 2, 2, 1, 2, 1, 1]
+optimizers	2.1	0.7	[3, 3, 1, 3, 2, 2, 1, 2, 2, 2]
+optimizes	1.8	0.6	[1, 3, 2, 1, 2, 2, 1, 2, 2, 2]
+optimizing	2.0	0.7746	[1, 1, 2, 2, 1, 3, 3, 3, 2, 2]
+optionless	-1.7	0.64031	[-2, -1, -2, -3, -1, -2, -2, -2, -1, -1]
+original	1.3	0.9	[0, 2, 0, 2, 2, 0, 2, 1, 2, 2]
+outcry	-2.3	0.64031	[-3, -2, -2, -3, -2, -1, -3, -2, -2, -3]
+outgoing	1.2	1.16619	[1, 1, 1, 2, -1, 1, 3, 3, 0, 1]
+outmaneuvered	0.5	1.36015	[-2, 2, 0, 0, 3, 1, 1, 0, 1, -1]
+outrage	-2.3	1.00499	[-2, -2, -4, -3, -1, -3, -3, -1, -1, -3]
+outraged	-2.5	0.92195	[-3, -2, -2, -1, -3, -3, -1, -4, -3, -3]
+outrageous	-2.0	1.34164	[-3, 0, -2, -1, -3, 0, -3, -3, -4, -1]
+outrageously	-1.2	1.32665	[-1, -1, -3, -3, -2, -1, 2, -1, -1, -1]
+outrageousness	-1.2	1.249	[-2, 0, 1, -2, -1, -1, -3, 0, -1, -3]
+outrageousnesses	-1.3	1.67631	[-1, -3, -2, 1, 0, 1, 0, -3, -2, -4]
+outrages	-2.3	1.00499	[-3, -2, -2, -1, -3, -3, -1, -4, -1, -3]
+outraging	-2.0	1.18322	[-4, -1, -2, -3, -1, 0, -1, -3, -3, -2]
+outreach	1.1	0.7	[2, 1, 0, 0, 2, 1, 1, 1, 2, 1]
+outstanding	3.0	0.89443	[3, 1, 3, 3, 4, 4, 2, 3, 4, 3]
+overjoyed	2.7	0.78102	[4, 3, 3, 4, 2, 2, 2, 2, 3, 2]
+overload	-1.5	0.67082	[-2, 0, -1, -2, -2, -1, -1, -2, -2, -2]
+overlooked	-0.1	1.44568	[-1, -2, -1, -1, 2, 0, -1, 2, -1, 2]
+overreact	-1.0	1.73205	[-2, -2, -2, -2, 0, -3, 1, 3, -1, -2]
+overreacted	-1.7	0.64031	[-2, -2, -2, -1, -1, -1, -1, -3, -2, -2]
+overreaction	-0.7	1.34536	[-2, -1, 0, -1, -1, 3, -2, -1, -1, -1]
+overreacts	-2.2	0.87178	[-2, -2, -2, -3, -4, -1, -3, -1, -2, -2]
+oversell	-0.9	0.7	[0, -1, -1, 0, -2, -1, -1, -1, -2, 0]
+overselling	-0.8	1.16619	[0, -1, 0, -1, -2, -1, -1, -2, -2, 2]
+oversells	0.3	1.26886	[-1, -1, 0, 0, 2, 2, 2, -1, 1, -1]
+oversimplification	0.2	1.53623	[-1, 1, -1, -1, 1, -1, -2, 1, 2, 3]
+oversimplifies	0.1	1.37477	[3, 0, 0, -1, 1, -1, 2, -1, -1, -1]
+oversimplify	-0.6	1.35647	[-3, -1, 0, -2, 0, 1, 2, -1, -1, -1]
+overstatement	-1.1	0.7	[-2, 0, -1, -2, -1, 0, -1, -1, -2, -1]
+overstatements	-0.7	1.34536	[-1, -1, -3, -1, 2, 0, -1, -1, -2, 1]
+overweight	-1.5	0.67082	[-3, -2, -1, -1, -1, -2, -1, -2, -1, -1]
+overwhelm	-0.7	1.26886	[-1, 2, -1, -1, -2, -2, 1, 0, -1, -2]
+overwhelmed	0.2	1.53623	[-2, -1, 2, -2, 2, 1, -1, 2, 1, 0]
+overwhelmingly	-0.5	1.28452	[0, -2, -1, 0, -2, -1, -2, 0, 1, 2]
+overwhelms	-0.8	1.249	[-2, -2, -1, -1, -1, -2, 2, 1, -1, -1]
+oxymoron	-0.5	0.80623	[0, 0, -1, -1, -1, -2, 1, 0, 0, -1]
+pain	-2.3	0.64031	[-2, -3, -2, -2, -2, -2, -2, -2, -2, -4]
+pained	-1.8	0.6	[-1, -2, -3, -2, -2, -2, -2, -1, -1, -2]
+painful	-1.9	0.9434	[-2, -1, -1, -3, -4, -1, -1, -2, -2, -2]
+painfuller	-1.7	1.34536	[-2, -2, -2, 2, -1, -3, -2, -2, -3, -2]
+painfully	-2.4	0.4899	[-2, -3, -2, -3, -3, -2, -2, -2, -2, -3]
+painfulness	-2.7	0.64031	[-3, -4, -3, -2, -3, -3, -3, -2, -2, -2]
+paining	-1.7	0.45826	[-1, -2, -2, -2, -2, -2, -1, -2, -1, -2]
+painless	1.2	0.87178	[1, 2, -1, 1, 2, 1, 2, 1, 2, 1]
+painlessly	1.1	0.3	[1, 1, 1, 1, 1, 1, 1, 1, 1, 2]
+painlessness	0.4	1.0198	[1, 1, 1, 1, -1, 1, -2, 0, 1, 1]
+pains	-1.8	0.6	[-2, -2, -1, -1, -1, -2, -2, -2, -3, -2]
+palatable	1.6	0.8	[2, 1, 2, 1, 2, 1, 3, 0, 2, 2]
+palatableness	0.8	0.87178	[2, 1, 1, 0, -1, 2, 0, 1, 1, 1]
+palatably	1.1	0.83066	[2, 1, 2, 1, 1, 1, 2, -1, 1, 1]
+panic	-2.3	0.64031	[-3, -2, -1, -2, -2, -2, -3, -3, -2, -3]
+panicked	-2.0	1.61245	[-2, -4, -3, -3, -3, 1, -2, -2, 1, -3]
+panicking	-1.9	0.53852	[-2, -2, -3, -2, -2, -2, -2, -2, -1, -1]
+panicky	-1.5	0.67082	[-2, -2, -1, -1, -1, -1, -1, -2, -3, -1]
+panicle	0.5	0.67082	[2, 0, 0, 0, 0, 0, 0, 1, 1, 1]
+panicled	0.1	0.83066	[2, 0, 0, 0, 0, -1, 0, -1, 1, 0]
+panicles	-0.2	0.6	[1, 0, 0, 0, 0, -1, 0, -1, -1, 0]
+panics	-1.9	1.3	[-2, -3, -2, -3, -1, -2, 1, -4, -1, -2]
+paniculate	0.1	0.3	[0, 0, 0, 1, 0, 0, 0, 0, 0, 0]
+panicums	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+paradise	3.2	0.9798	[4, 1, 4, 2, 4, 4, 3, 3, 3, 4]
+paradox	-0.4	0.66332	[-1, -1, 0, 0, -1, 0, -1, 0, 1, -1]
+paranoia	-1.0	1.48324	[1, -2, -2, -3, -1, 0, -2, -1, -2, 2]
+paranoiac	-1.3	1.61555	[-2, -3, -2, -2, 1, -3, 2, -2, 0, -2]
+paranoiacs	-0.7	1.18743	[-1, 0, -1, -1, -3, 1, -2, 0, 1, -1]
+paranoias	-1.5	1.0247	[-2, -3, -2, 0, -1, -3, 0, -1, -1, -2]
+paranoid	-1.0	1.41421	[0, -3, -3, -2, -1, -1, 0, 1, -2, 1]
+paranoids	-1.6	0.91652	[-2, -1, -1, -2, -2, -1, -1, -1, -4, -1]
+pardon	1.3	0.45826	[1, 2, 1, 2, 1, 2, 1, 1, 1, 1]
+pardoned	0.9	0.9434	[1, 1, 1, 1, 1, 1, 1, 0, 3, -1]
+pardoning	1.7	0.78102	[3, 2, 2, 2, 1, 1, 2, 2, 0, 2]
+pardons	1.2	0.6	[2, 1, 1, 1, 1, 2, 1, 2, 0, 1]
+parley	-0.4	0.66332	[0, -2, 0, 0, -1, -1, 0, 0, 0, 0]
+partied	1.4	1.11355	[2, 3, 1, 1, 1, 2, 3, -1, 1, 1]
+partier	1.4	0.8	[2, 2, 1, 1, 0, 2, 3, 1, 1, 1]
+partiers	0.7	1.00499	[0, 0, 3, 0, 0, 0, 2, 1, 0, 1]
+parties	1.7	0.78102	[2, 3, 1, 1, 1, 2, 3, 1, 2, 1]
+party	1.7	0.78102	[3, 2, 2, 1, 3, 2, 1, 1, 1, 1]
+partyer	1.2	1.07703	[1, 3, 1, 0, 1, 0, 2, 1, 3, 0]
+partyers	1.1	0.83066	[1, 2, 0, 3, 1, 1, 1, 0, 1, 1]
+partying	1.6	1.11355	[0, 3, 1, 0, 3, 2, 3, 1, 2, 1]
+passion	2.0	0.44721	[2, 2, 1, 3, 2, 2, 2, 2, 2, 2]
+passional	1.6	0.8	[2, 1, 3, 0, 2, 1, 1, 2, 2, 2]
+passionate	2.4	1.35647	[0, 4, 3, 3, 4, 2, 0, 2, 3, 3]
+passionately	2.4	0.91652	[3, 0, 3, 3, 2, 3, 2, 3, 2, 3]
+passionateness	2.3	0.64031	[1, 3, 2, 3, 2, 3, 2, 3, 2, 2]
+passionflower	0.3	0.45826	[0, 0, 0, 0, 1, 0, 1, 1, 0, 0]
+passionflowers	0.4	0.66332	[0, 0, 0, 0, 2, 1, 1, 0, 0, 0]
+passionless	-1.9	0.7	[-3, -2, -2, -2, -1, -1, -1, -3, -2, -2]
+passions	2.2	0.6	[3, 3, 3, 2, 2, 1, 2, 2, 2, 2]
+passive	0.8	1.46969	[4, 1, 1, 0, -2, 0, 1, 1, 2, 0]
+passively	-0.7	0.64031	[0, -1, 0, 0, -1, -2, 0, -1, -1, -1]
+pathetic	-2.7	1.48661	[-3, -4, -3, -4, -2, 1, -2, -2, -4, -4]
+pathetical	-1.2	1.249	[-2, -1, -2, -1, -2, 1, -3, 1, -1, -2]
+pathetically	-1.8	1.72047	[-3, -4, -2, 0, -3, -2, -3, -3, 1, 1]
+pay	-0.4	0.91652	[0, 0, -3, 0, 0, 0, 0, 0, -1, 0]
+peace	2.5	1.0247	[3, 2, 1, 4, 2, 3, 4, 1, 3, 2]
+peaceable	1.7	0.45826	[2, 2, 1, 2, 1, 2, 2, 1, 2, 2]
+peaceableness	1.8	1.16619	[2, 2, 4, 2, 2, 2, 2, 1, 2, -1]
+peaceably	2.0	0.63246	[2, 3, 2, 2, 1, 2, 3, 1, 2, 2]
+peaceful	2.2	0.74833	[4, 2, 1, 2, 2, 2, 3, 2, 2, 2]
+peacefuller	1.9	0.7	[2, 2, 2, 1, 3, 3, 2, 2, 1, 1]
+peacefullest	3.1	0.7	[3, 3, 2, 3, 4, 2, 4, 3, 4, 3]
+peacefully	2.4	0.66332	[3, 2, 2, 2, 4, 2, 2, 3, 2, 2]
+peacefulness	2.1	0.83066	[3, 2, 1, 2, 3, 1, 3, 3, 1, 2]
+peacekeeper	1.6	1.11355	[1, 1, 0, 2, 1, 1, 4, 3, 2, 1]
+peacekeepers	1.6	1.11355	[4, 1, 1, 2, 1, 1, 2, 3, 0, 1]
+peacekeeping	2.0	0.63246	[2, 1, 1, 2, 3, 3, 2, 2, 2, 2]
+peacekeepings	1.6	0.8	[0, 1, 1, 2, 2, 3, 2, 2, 2, 1]
+peacemaker	2.0	0.89443	[2, 1, 2, 4, 2, 2, 1, 3, 1, 2]
+peacemakers	2.4	1.0198	[0, 3, 4, 2, 3, 2, 3, 3, 2, 2]
+peacemaking	1.7	0.78102	[1, 1, 1, 3, 3, 1, 2, 2, 2, 1]
+peacenik	0.8	0.87178	[1, 1, 0, 1, 2, 0, 1, 1, -1, 2]
+peaceniks	0.7	1.00499	[2, 0, 0, 1, 0, 2, 1, -1, 2, 0]
+peaces	2.1	0.83066	[2, 2, 2, 2, 3, 0, 3, 3, 2, 2]
+peacetime	2.2	1.16619	[3, 1, 4, 2, 4, 3, 1, 1, 2, 1]
+peacetimes	2.1	0.83066	[3, 2, 2, 4, 1, 2, 2, 2, 1, 2]
+peculiar	0.6	1.2	[-1, 0, -1, 1, 2, -1, 2, 1, 2, 1]
+peculiarities	0.1	1.37477	[-1, -1, 0, -1, -1, 1, 3, 2, -1, 0]
+peculiarity	0.6	1.2	[-1, 1, -1, 0, 2, -1, 1, 2, 2, 1]
+peculiarly	-0.4	1.2	[-1, 2, -2, -1, 0, 0, -2, 1, -1, 0]
+penalty	-2.0	0.63246	[-2, -3, -2, -2, -1, -2, -3, -2, -2, -1]
+pensive	0.3	1.1	[1, 0, 0, 1, 0, -1, 3, 0, -1, 0]
+perfect	2.7	0.78102	[2, 4, 2, 3, 4, 2, 3, 2, 3, 2]
+perfecta	1.4	1.42829	[1, 0, 0, 3, 1, 0, 0, 4, 3, 2]
+perfectas	0.6	1.11355	[0, 0, -1, 1, 0, 2, 3, 0, 1, 0]
+perfected	2.7	0.78102	[1, 3, 3, 4, 2, 3, 3, 2, 3, 3]
+perfecter	1.8	0.9798	[2, 1, 3, 1, 2, 1, 2, 4, 1, 1]
+perfecters	1.4	1.11355	[2, 1, 3, 0, 0, 3, 2, 0, 1, 2]
+perfectest	3.1	1.04403	[2, 4, 4, 4, 3, 2, 1, 3, 4, 4]
+perfectibilities	2.1	1.04403	[3, 2, 2, 3, 4, 1, 2, 2, 0, 2]
+perfectibility	1.8	1.249	[4, 3, 3, 0, 1, 0, 1, 2, 2, 2]
+perfectible	1.5	0.67082	[1, 2, 1, 1, 2, 1, 1, 3, 2, 1]
+perfecting	2.3	0.9	[1, 2, 3, 3, 1, 2, 2, 4, 2, 3]
+perfection	2.7	1.1	[3, 3, 3, 1, 2, 4, 4, 1, 2, 4]
+perfectionism	1.3	1.26886	[3, -1, 2, 1, 2, 2, 2, -1, 1, 2]
+perfectionist	1.5	1.20416	[3, -1, 3, 1, 2, 2, 2, 0, 1, 2]
+perfectionistic	0.7	1.67631	[-1, 0, 2, 0, 1, 0, 3, -1, 4, -1]
+perfectionists	0.1	1.22066	[1, -1, 1, -1, 0, 0, -1, 0, 3, -1]
+perfections	2.5	1.43178	[2, 4, 4, 3, 3, 4, -1, 2, 2, 2]
+perfective	1.2	0.87178	[1, 0, 1, 1, 3, 2, 2, 0, 1, 1]
+perfectively	2.1	1.13578	[3, 3, 1, 4, 0, 2, 1, 2, 2, 3]
+perfectiveness	0.9	1.51327	[-2, 3, -1, 0, 2, 0, 2, 2, 2, 1]
+perfectives	0.9	0.83066	[0, 2, 1, 1, 1, 0, 2, 0, 2, 0]
+perfectivity	2.2	0.9798	[3, 2, 0, 3, 1, 2, 3, 3, 2, 3]
+perfectly	3.2	0.4	[3, 4, 4, 3, 3, 3, 3, 3, 3, 3]
+perfectness	3.0	0.63246	[4, 3, 3, 3, 3, 2, 4, 2, 3, 3]
+perfecto	1.3	1.34536	[1, 0, 0, 2, 0, 0, 1, 4, 3, 2]
+perfects	1.6	1.11355	[1, 1, 1, 2, 1, 0, 1, 4, 3, 2]
+peril	-1.7	1.67631	[-3, -2, -2, 3, -3, -2, -3, -2, -1, -2]
+perjury	-1.9	0.9434	[-3, -2, -3, -2, -2, 0, -1, -2, -3, -1]
+perpetrator	-2.2	0.74833	[-2, -3, -2, -2, -2, -2, -4, -2, -1, -2]
+perpetrators	-1.0	1.67332	[-1, -2, -2, -2, -2, 2, 0, -4, 1, 0]
+perplexed	-1.3	0.64031	[-1, -1, -2, -1, -1, -1, 0, -2, -2, -2]
+persecute	-2.1	1.37477	[-2, -3, -2, 1, -1, -4, -2, -2, -2, -4]
+persecuted	-1.3	1.61555	[-2, -1, -2, -1, -2, 2, -4, 1, -2, -2]
+persecutes	-1.2	1.4	[-2, -1, -2, 0, -2, 1, -3, 1, -1, -3]
+persecuting	-1.5	1.62788	[-3, -2, -2, 0, -4, -3, -2, -1, 1, 1]
+perturbed	-1.4	0.8	[-2, -1, -1, 0, -2, -2, -2, 0, -2, -2]
+perverse	-1.8	1.8868	[-2, -4, -3, 1, -2, -4, 1, 0, -1, -4]
+perversely	-2.2	0.87178	[-1, -2, -2, -2, -1, -3, -2, -3, -4, -2]
+perverseness	-2.1	1.22066	[-3, -3, 1, -2, -3, -2, -3, -2, -1, -3]
+perversenesses	-0.5	1.74642	[-2, 3, -1, -2, 1, 0, 1, 0, -2, -3]
+perversion	-1.3	1.34536	[-3, -2, -2, 1, 1, -3, -1, -2, -1, -1]
+perversions	-1.2	1.83303	[-2, 0, -4, -2, -3, -3, 0, 1, -1, 2]
+perversities	-1.1	1.22066	[-2, -1, -2, 0, -2, -2, -2, 1, 1, -2]
+perversity	-2.6	0.8	[-2, -3, -2, -2, -4, -3, -3, -1, -3, -3]
+perversive	-2.1	0.7	[-3, -1, -3, -2, -2, -2, -2, -1, -3, -2]
+pervert	-2.3	0.9	[-2, -2, -1, -3, -4, -2, -3, -1, -3, -2]
+perverted	-2.5	1.56525	[-2, -4, -2, -4, -3, -4, 1, -2, -1, -4]
+pervertedly	-1.2	1.77764	[-3, -2, -1, -2, 2, -3, 1, -3, 1, -2]
+pervertedness	-1.2	1.46969	[1, -2, -3, -2, 0, -2, -3, 1, 0, -2]
+perverter	-1.7	1.48661	[-3, -4, -2, -2, -1, -1, 2, -2, -2, -2]
+perverters	-0.6	1.68523	[-2, -2, -1, 0, -1, 2, -3, 1, 2, -2]
+perverting	-1.0	2.09762	[4, -2, -2, -4, -2, 1, 0, -1, -2, -2]
+perverts	-2.8	0.6	[-3, -3, -2, -3, -3, -2, -2, -4, -3, -3]
+pesky	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
+pessimism	-1.5	1.36015	[-2, -3, 1, -2, -2, -1, 1, -3, -2, -2]
+pessimisms	-2.0	1.0	[-3, -1, -2, -2, -3, -1, 0, -2, -3, -3]
+pessimist	-1.5	1.36015	[-1, -3, 1, -2, -2, -2, 1, -3, -2, -2]
+pessimistic	-1.5	1.43178	[-3, -1, -1, 1, -3, -3, -2, -2, -2, 1]
+pessimistically	-2.0	1.0	[-1, -1, -3, -4, -2, -1, -1, -3, -2, -2]
+pessimists	-1.0	1.26491	[-1, 1, -1, 0, -2, -2, -2, -3, -1, 1]
+petrifaction	-1.9	1.3	[-3, -2, -1, -4, -3, 0, -1, 0, -2, -3]
+petrifactions	-0.3	1.00499	[0, -1, 0, 0, 0, 0, 0, 0, -3, 1]
+petrification	-0.1	1.44568	[-1, 2, -1, -1, 0, 2, 2, -2, -1, -1]
+petrifications	-0.4	0.8	[0, 0, -2, 0, 0, 0, 0, 0, -2, 0]
+petrified	-2.5	0.92195	[-4, -3, -2, -1, -2, -3, -2, -2, -2, -4]
+petrifies	-2.3	1.00499	[-4, -3, -2, -1, -2, -2, -1, -2, -2, -4]
+petrify	-1.7	0.9	[-2, -3, -1, -2, -1, -1, -2, -3, 0, -2]
+petrifying	-2.6	0.8	[-2, -3, -3, -2, -4, -2, -3, -1, -3, -3]
+pettier	-0.3	1.41774	[-1, -1, -1, -1, 2, 0, 2, -2, 1, -2]
+pettiest	-1.3	1.95192	[1, -3, -3, -3, -2, -1, 2, -1, 1, -4]
+petty	-0.8	1.32665	[1, -3, -2, -1, -1, -1, -1, -1, 2, -1]
+phobia	-1.6	1.0198	[-2, -2, 1, -2, -3, -1, -1, -2, -2, -2]
+phobias	-2.0	1.0	[-3, -2, -2, -3, -3, 0, -1, -2, -1, -3]
+phobic	-1.2	1.16619	[-2, -2, 1, -1, -2, -1, 1, -2, -2, -2]
+phobics	-1.3	0.64031	[-1, -1, -1, -2, -2, -1, 0, -2, -2, -1]
+picturesque	1.6	1.11355	[4, 1, 1, 2, 1, 2, 1, 0, 3, 1]
+pileup	-1.1	1.13578	[-2, 1, 0, -1, 0, -1, -3, -2, -2, -1]
+pique	-1.1	1.13578	[-2, -2, -2, 0, 0, -1, 1, -1, -1, -3]
+piqued	0.1	1.04403	[0, -2, 0, 1, 1, 1, -1, 1, -1, 1]
+piss	-1.7	0.9	[-2, -1, -1, -2, -1, -3, -3, 0, -2, -2]
+pissant	-1.5	1.5	[-1, -3, -3, 1, -3, -1, -1, -2, 1, -3]
+pissants	-2.5	0.80623	[-4, -3, -3, -2, -3, -1, -2, -3, -2, -2]
+pissed	-3.2	0.6	[-3, -3, -4, -3, -2, -4, -4, -3, -3, -3]
+pisser	-2.0	1.09545	[-2, -4, -1, -3, -2, -3, -1, -2, -2, 0]
+pissers	-1.4	2.00998	[-1, -1, -4, -2, -3, 4, -2, -1, -2, -2]
+pisses	-1.4	0.8	[-2, -2, -1, -3, -1, -1, -1, -2, -1, 0]
+pissing	-1.7	1.26886	[0, 0, -2, -2, -3, 0, -3, -1, -3, -3]
+pissoir	-0.8	1.4	[-2, 0, 0, -2, -1, -3, 0, -2, 0, 2]
+piteous	-1.2	1.46969	[-2, -1, -2, -2, -2, -1, 3, -1, -2, -2]
+pitiable	-1.1	1.22066	[-1, 0, -1, -1, 1, -2, -4, -1, -1, -1]
+pitiableness	-1.1	1.64012	[-2, -1, -1, -2, -4, 2, 1, 0, -2, -2]
+pitiably	-1.1	0.9434	[-1, 0, 0, -2, 0, -2, -3, -1, -1, -1]
+pitied	-1.3	1.1	[-2, -1, -3, -1, 1, 0, -2, -2, -1, -2]
+pitier	-1.2	1.32665	[-3, -1, -2, -3, -1, -1, 1, 1, -2, -1]
+pitiers	-1.3	0.9	[0, -1, -2, -2, -1, -1, -1, -3, -2, 0]
+pities	-1.2	1.249	[-2, -1, -2, -3, -1, -1, 1, 1, -2, -2]
+pitiful	-2.2	0.9798	[-3, -2, -1, -3, -2, -2, -3, -3, -3, 0]
+pitifuller	-1.8	1.07703	[-1, -1, -2, -3, -4, 0, -2, -2, -1, -2]
+pitifullest	-1.1	2.11896	[-2, 1, -1, -4, -4, -1, -3, -1, 2, 2]
+pitifully	-1.2	1.249	[-2, -1, -3, -2, -1, -1, -2, -1, 2, -1]
+pitifulness	-1.2	1.77764	[-3, -2, -1, -3, -2, -1, 3, 1, -2, -2]
+pitiless	-1.8	0.87178	[-2, 0, -2, -2, -2, -3, -1, -3, -1, -2]
+pitilessly	-2.1	0.7	[-2, -2, -1, -3, -3, -1, -3, -2, -2, -2]
+pitilessness	-0.5	1.62788	[1, 3, 1, -3, -2, -1, -1, -1, -1, -1]
+pity	-1.2	0.4	[-2, -2, -1, -1, -1, -1, -1, -1, -1, -1]
+pitying	-1.4	0.91652	[-1, -3, -1, -3, -2, -1, 0, -1, -1, -1]
+pityingly	-1.0	1.26491	[-2, -2, -1, -2, -2, 0, 0, -1, 2, -2]
+pityriasis	-0.8	0.87178	[-2, 0, 0, 0, -1, 0, -2, -1, -2, 0]
+play	1.4	1.0198	[2, 0, 1, 1, 1, 2, 1, 4, 1, 1]
+played	1.4	1.42829	[2, 1, 1, 1, 4, 0, 1, 0, 4, 0]
+playful	1.9	0.83066	[4, 2, 2, 2, 1, 1, 1, 2, 2, 2]
+playfully	1.6	0.4899	[2, 1, 1, 2, 1, 2, 2, 2, 1, 2]
+playfulness	1.2	0.87178	[2, 1, 2, -1, 1, 2, 1, 2, 1, 1]
+playing	0.8	0.87178	[0, 2, 2, 1, 0, 0, 2, 0, 0, 1]
+plays	1.0	1.09545	[0, 2, 0, 2, 0, 1, 0, 2, 3, 0]
+pleasant	2.3	0.64031	[2, 3, 3, 3, 2, 1, 2, 2, 3, 2]
+pleasanter	1.5	0.67082	[2, 2, 2, 1, 0, 1, 1, 2, 2, 2]
+pleasantest	2.6	0.8	[3, 3, 3, 1, 2, 4, 3, 2, 2, 3]
+pleasantly	2.1	0.53852	[1, 2, 3, 2, 2, 2, 2, 2, 3, 2]
+pleasantness	2.3	0.9	[3, 2, 3, 3, 3, 1, 1, 3, 1, 3]
+pleasantnesses	2.3	0.78102	[3, 1, 2, 3, 1, 2, 3, 3, 2, 3]
+pleasantries	1.3	0.45826	[1, 1, 1, 1, 1, 2, 1, 2, 2, 1]
+pleasantry	2.0	0.7746	[2, 2, 1, 1, 4, 2, 2, 2, 2, 2]
+please	1.3	0.78102	[2, 1, 2, 2, 2, 0, 2, 1, 0, 1]
+pleased	1.9	0.53852	[2, 2, 2, 2, 1, 1, 2, 3, 2, 2]
+pleaser	1.7	0.45826	[2, 2, 2, 2, 1, 1, 1, 2, 2, 2]
+pleasers	1.0	1.0	[1, 1, 2, 0, 1, 3, 1, 1, -1, 1]
+pleases	1.7	0.45826	[2, 1, 2, 2, 1, 1, 2, 2, 2, 2]
+pleasing	2.4	0.91652	[2, 3, 2, 2, 2, 2, 4, 4, 1, 2]
+pleasurability	1.9	0.83066	[1, 2, 2, 2, 2, 0, 2, 3, 3, 2]
+pleasurable	2.4	0.4899	[2, 3, 3, 2, 3, 3, 2, 2, 2, 2]
+pleasurableness	2.4	0.91652	[2, 3, 2, 1, 2, 3, 4, 3, 1, 3]
+pleasurably	2.6	0.4899	[2, 2, 2, 3, 3, 3, 3, 2, 3, 3]
+pleasure	2.7	0.9	[4, 4, 3, 2, 2, 3, 2, 1, 3, 3]
+pleasured	2.3	0.64031	[3, 2, 3, 2, 3, 3, 1, 2, 2, 2]
+pleasureless	-1.6	0.8	[-1, -1, -1, -1, -2, -3, -3, -2, -1, -1]
+pleasures	1.9	1.37477	[3, -2, 3, 2, 3, 2, 2, 2, 2, 2]
+pleasuring	2.8	0.4	[3, 2, 3, 3, 3, 3, 3, 2, 3, 3]
+poised	1.0	0.44721	[1, 1, 1, 1, 1, 1, 0, 1, 1, 2]
+poison	-2.5	0.92195	[-4, -3, -2, -4, -2, -2, -2, -3, -1, -2]
+poisoned	-2.2	0.9798	[-4, -1, -4, -1, -2, -2, -2, -2, -2, -2]
+poisoner	-2.7	0.78102	[-2, -3, -3, -4, -4, -2, -2, -2, -2, -3]
+poisoners	-3.1	0.83066	[-3, -4, -3, -4, -3, -4, -3, -3, -1, -3]
+poisoning	-2.8	1.249	[-4, -4, -2, 0, -2, -3, -4, -3, -2, -4]
+poisonings	-2.4	1.11355	[-2, 0, -2, -1, -4, -3, -3, -3, -3, -3]
+poisonous	-2.7	0.78102	[-3, -3, -4, -2, -1, -3, -3, -3, -3, -2]
+poisonously	-2.9	0.53852	[-3, -2, -3, -3, -2, -3, -3, -4, -3, -3]
+poisons	-2.7	0.9	[-3, -4, -3, -1, -2, -3, -3, -2, -2, -4]
+poisonwood	-1.0	0.89443	[0, -2, 0, 0, 0, -1, -2, -2, -2, -1]
+pollute	-2.3	0.64031	[-3, -2, -2, -2, -2, -3, -3, -1, -3, -2]
+polluted	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -2, -3, -2]
+polluter	-1.8	0.6	[-2, -1, -2, -1, -2, -2, -3, -1, -2, -2]
+polluters	-2.0	0.44721	[-2, -2, -2, -2, -2, -3, -2, -1, -2, -2]
+pollutes	-2.2	0.87178	[-2, -1, -2, -1, -3, -1, -3, -3, -3, -3]
+poor	-2.1	1.13578	[-2, -2, -1, -4, -2, 0, -2, -4, -2, -2]
+poorer	-1.5	1.56525	[-2, -3, -2, -2, -2, -2, 3, -2, -1, -2]
+poorest	-2.5	0.80623	[-2, -3, -3, -1, -2, -3, -3, -4, -2, -2]
+popular	1.8	0.74833	[2, 3, 1, 2, 2, 1, 3, 1, 2, 1]
+popularise	1.6	0.66332	[1, 1, 2, 2, 3, 2, 1, 2, 1, 1]
+popularised	1.1	0.9434	[1, 1, 0, 0, 3, 2, 1, 2, 1, 0]
+popularises	0.5	0.67082	[1, 0, 0, 0, 0, 1, 1, 2, 0, 0]
+popularising	1.2	0.6	[1, 0, 2, 2, 1, 1, 1, 2, 1, 1]
+popularities	1.6	0.8	[2, 1, 1, 2, 0, 2, 1, 2, 3, 2]
+popularity	2.1	1.04403	[2, 1, 1, 1, 3, 2, 3, 4, 3, 1]
+popularization	1.3	0.78102	[1, 2, 1, 2, 1, 0, 1, 1, 3, 1]
+popularizations	0.9	0.7	[1, 1, 1, 0, 2, 0, 1, 1, 2, 0]
+popularize	1.3	0.64031	[2, 2, 0, 2, 1, 1, 1, 1, 2, 1]
+popularized	1.9	0.83066	[3, 2, 3, 2, 1, 0, 2, 2, 2, 2]
+popularizer	1.8	0.74833	[2, 2, 3, 2, 1, 0, 2, 2, 2, 2]
+popularizers	1.0	0.89443	[0, 0, 1, 2, 1, 1, 1, 1, 3, 0]
+popularizes	1.4	0.8	[2, 1, 3, 2, 1, 0, 1, 2, 1, 1]
+popularizing	1.5	0.67082	[2, 2, 1, 1, 1, 2, 2, 0, 2, 2]
+popularly	1.8	0.74833	[1, 3, 2, 1, 3, 1, 2, 1, 2, 2]
+positive	2.6	0.91652	[2, 1, 2, 2, 3, 3, 4, 3, 4, 2]
+positively	2.4	0.66332	[2, 2, 3, 3, 4, 2, 2, 2, 2, 2]
+positiveness	2.3	1.18743	[2, 1, 4, 3, 4, 2, 0, 3, 2, 2]
+positivenesses	2.2	0.74833	[3, 3, 2, 2, 2, 2, 1, 3, 1, 3]
+positiver	2.3	0.78102	[1, 4, 2, 2, 2, 3, 2, 2, 2, 3]
+positives	2.4	0.4899	[3, 3, 2, 2, 2, 2, 3, 2, 3, 2]
+positivest	2.9	1.04403	[4, 3, 2, 1, 3, 4, 4, 4, 2, 2]
+positivism	1.6	1.35647	[3, 0, 2, 1, 2, 0, 3, 4, 1, 0]
+positivisms	1.8	0.9798	[4, 1, 2, 2, 2, 0, 2, 2, 1, 2]
+positivist	2.0	1.0	[3, 1, 2, 2, 2, 0, 2, 4, 2, 2]
+positivistic	1.9	0.83066	[2, 3, 1, 3, 1, 1, 3, 2, 1, 2]
+positivists	1.7	1.1	[1, 2, 1, 4, 2, 1, 3, 0, 1, 2]
+positivities	2.6	0.91652	[2, 2, 4, 3, 2, 3, 4, 3, 1, 2]
+positivity	2.3	0.9	[2, 2, 2, 3, 3, 3, 3, 0, 3, 2]
+possessive	-0.9	1.22066	[-1, -1, -2, -2, 0, -1, 0, -2, 2, -2]
+postpone	-0.9	0.83066	[1, -1, -2, -1, -1, -2, -1, -1, 0, -1]
+postponed	-0.8	0.4	[-1, -1, 0, 0, -1, -1, -1, -1, -1, -1]
+postpones	-1.1	0.83066	[-1, -1, -1, 0, -1, 0, -2, -1, -3, -1]
+postponing	-0.5	0.5	[0, -1, 0, -1, 0, 0, 0, -1, -1, -1]
+poverty	-2.3	1.00499	[-2, -4, -2, -4, -3, -1, -2, -2, -1, -2]
+powerful	1.8	0.9798	[4, 0, 2, 1, 2, 2, 2, 2, 1, 2]
+powerless	-2.2	0.6	[-2, -3, -2, -2, -3, -2, -3, -2, -1, -2]
+praise	2.6	0.8	[2, 4, 3, 3, 2, 1, 3, 3, 2, 3]
+praised	2.2	0.6	[3, 2, 2, 2, 2, 3, 1, 3, 2, 2]
+praiser	2.0	0.89443	[3, 1, 3, 1, 1, 2, 1, 3, 2, 3]
+praisers	2.0	0.63246	[2, 2, 1, 3, 3, 2, 1, 2, 2, 2]
+praises	2.4	0.4899	[3, 2, 2, 3, 2, 3, 2, 3, 2, 2]
+praiseworthily	1.9	0.7	[2, 1, 1, 3, 2, 2, 2, 3, 1, 2]
+praiseworthiness	2.4	0.8	[1, 3, 2, 4, 2, 2, 3, 2, 3, 2]
+praiseworthy	2.6	0.4899	[3, 3, 3, 3, 2, 2, 3, 2, 3, 2]
+praising	2.5	0.67082	[2, 3, 3, 2, 2, 3, 3, 3, 1, 3]
+pray	1.3	1.18743	[0, 3, 2, 1, 1, 1, -1, 3, 1, 2]
+praying	1.5	0.92195	[2, 2, 0, 3, 1, 3, 1, 1, 1, 1]
+prays	1.4	1.0198	[2, 0, 2, 0, 1, 1, 3, 1, 3, 1]
+prblm	-1.6	0.8	[-1, -1, -1, -1, -1, -3, -3, -2, -2, -1]
+prblms	-2.3	1.00499	[-2, -2, -2, -2, -4, -4, -3, -1, -2, -1]
+precious	2.7	0.64031	[3, 3, 3, 3, 3, 1, 3, 3, 2, 3]
+preciously	2.2	0.74833	[3, 3, 3, 2, 2, 1, 1, 3, 2, 2]
+preciousness	1.9	0.83066	[2, 4, 2, 2, 2, 1, 1, 1, 2, 2]
+prejudice	-2.3	0.78102	[-2, -1, -2, -2, -3, -2, -2, -3, -4, -2]
+prejudiced	-1.9	0.53852	[-2, -3, -1, -2, -1, -2, -2, -2, -2, -2]
+prejudices	-1.8	0.74833	[-2, -3, -1, -2, -1, -3, -2, -1, -1, -2]
+prejudicial	-2.6	0.8	[-3, -3, -2, -2, -3, -4, -2, -1, -3, -3]
+prejudicially	-1.5	1.74642	[-3, -1, -1, -3, -3, -1, -3, 1, 2, -3]
+prejudicialness	-2.4	1.42829	[-2, -3, 1, -3, -2, -4, -4, -3, -1, -3]
+prejudicing	-1.8	1.07703	[-2, -2, -2, -3, -2, -1, 1, -3, -2, -2]
+prepared	0.9	0.3	[1, 1, 1, 1, 1, 0, 1, 1, 1, 1]
+pressure	-1.2	0.6	[-1, -1, -1, -1, -2, -2, -1, -2, 0, -1]
+pressured	-0.9	1.04403	[-2, -1, -2, -1, 2, -1, -1, -1, -1, -1]
+pressureless	1.0	1.26491	[2, 0, 1, -1, -1, 2, 1, 2, 1, 3]
+pressures	-1.3	0.64031	[-2, -1, -1, -1, -3, -1, -1, -1, -1, -1]
+pressuring	-1.4	0.91652	[-3, -1, -1, -1, -1, -1, -1, -3, -2, 0]
+pressurise	-0.6	1.0198	[0, -2, 0, 1, 0, -2, 0, -2, 0, -1]
+pressurised	-0.4	0.66332	[0, 0, 0, -1, 0, -1, 0, -2, 0, 0]
+pressurises	-0.8	0.6	[-1, -1, -1, 0, -1, -1, 0, -1, 0, -2]
+pressurising	-0.6	1.28062	[-1, 0, 0, 2, -1, -1, -3, 0, -2, 0]
+pressurizations	-0.3	1.00499	[0, 0, 1, -2, 0, 0, -1, -2, 0, 1]
+pressurize	-0.7	1.34536	[0, -2, -2, 0, 0, -1, -3, 2, -1, 0]
+pressurized	0.1	0.83066	[0, 0, 0, 2, 0, 0, -1, -1, 0, 1]
+pressurizer	0.1	0.83066	[0, 0, 0, 1, 0, 0, -1, -1, 0, 2]
+pressurizers	-0.7	0.9	[-1, 0, -2, -1, -2, -1, 0, 0, 1, -1]
+pressurizes	-0.2	0.87178	[0, 0, -1, 1, 0, 0, -1, -2, 0, 1]
+pressurizing	-0.2	0.9798	[1, 0, -1, -1, -1, 0, -1, 2, 0, -1]
+pretend	-0.4	0.91652	[0, 1, -1, -1, -2, 0, -1, -1, 1, 0]
+pretending	0.4	1.49666	[2, 0, -1, -1, 0, 3, -2, 1, 0, 2]
+pretends	-0.4	0.66332	[0, -1, 0, -1, 1, 0, 0, -1, -1, -1]
+prettied	1.6	0.66332	[2, 1, 1, 1, 1, 2, 3, 2, 1, 2]
+prettier	2.1	0.53852	[2, 2, 2, 2, 2, 2, 3, 1, 2, 3]
+pretties	1.7	0.78102	[2, 1, 1, 2, 1, 2, 3, 1, 1, 3]
+prettiest	2.7	0.78102	[4, 3, 4, 2, 2, 2, 3, 2, 2, 3]
+pretty	2.2	0.6	[3, 2, 2, 2, 3, 1, 2, 2, 2, 3]
+prevent	0.1	1.22066	[-2, 1, 0, 0, -1, 2, -1, 2, 0, 0]
+prevented	0.1	0.7	[0, -1, 0, 2, 0, 0, 0, 0, 0, 0]
+preventing	-0.1	1.51327	[-2, 0, -2, 3, 0, 0, -1, -1, 2, 0]
+prevents	0.3	1.34536	[0, -2, 0, 0, 0, 2, 0, -1, 3, 1]
+prick	-1.4	1.42829	[-2, -2, -2, -1, 1, -1, -4, -2, 1, -2]
+pricked	-0.6	1.0198	[-1, -1, -2, 1, 0, -1, -2, -1, 1, 0]
+pricker	-0.3	0.9	[-1, -1, 0, 2, 0, -1, -1, -1, 0, 0]
+prickers	-0.2	0.87178	[1, -1, -1, 0, 1, -1, 0, 1, -1, -1]
+pricket	-0.5	0.67082	[0, -1, -1, -2, 0, 0, 0, 0, -1, 0]
+prickets	0.3	0.64031	[0, 2, 0, 0, 0, 1, 0, 0, 0, 0]
+pricking	-0.9	1.22066	[-2, -1, -2, 2, -2, -2, -1, 0, -1, 0]
+prickle	-1.0	0.44721	[-1, -1, -1, -1, -1, -1, -2, 0, -1, -1]
+prickled	-0.2	1.53623	[-1, -1, 3, -1, -2, 2, 0, 0, 0, -2]
+prickles	-0.8	0.74833	[0, -1, -1, -1, -2, -1, 0, 0, 0, -2]
+pricklier	-1.6	0.8	[-1, -2, -2, -2, -2, -1, -2, -1, 0, -3]
+prickliest	-1.4	1.35647	[-4, -2, -1, 0, -3, -1, -1, 1, -2, -1]
+prickliness	-0.6	0.91652	[-2, -1, -1, -1, -1, 1, -1, 1, 0, -1]
+prickling	-0.8	0.6	[-2, -1, 0, -1, 0, 0, -1, -1, -1, -1]
+prickly	-0.9	1.04403	[-2, -1, -1, -2, -1, 1, -2, -1, 1, -1]
+pricks	-0.9	1.04403	[-2, 0, -1, -3, -1, 1, 0, -1, -1, -1]
+pricky	-0.6	1.2	[-2, 1, -1, -2, -1, 2, 0, -1, -1, -1]
+pride	1.4	1.11355	[0, 2, 2, 2, 3, 1, -1, 2, 2, 1]
+prison	-2.3	0.64031	[-3, -3, -2, -2, -1, -2, -3, -3, -2, -2]
+prisoner	-2.5	1.0247	[-3, -1, -4, -4, -3, -2, -3, -2, -1, -2]
+prisoners	-2.3	0.78102	[-3, -2, -3, -3, -1, -3, -2, -1, -2, -3]
+privilege	1.5	0.80623	[2, 1, 0, 1, 3, 1, 2, 2, 2, 1]
+privileged	1.9	0.9434	[2, 3, 3, 2, 3, 1, 1, 2, 0, 2]
+privileges	1.6	1.2	[2, 1, 3, 1, 2, 2, 0, 0, 4, 1]
+privileging	0.7	1.1	[1, 1, 2, 2, -1, 2, 1, 0, 0, -1]
+prize	2.3	1.1	[2, 2, 0, 4, 4, 3, 2, 2, 2, 2]
+prized	2.4	0.8	[3, 3, 3, 2, 3, 2, 1, 3, 1, 3]
+prizefight	-0.1	1.13578	[-2, 2, 0, 0, 0, -2, 0, 1, 0, 0]
+prizefighter	1.0	1.0	[0, 2, 0, 0, 0, 2, 0, 2, 2, 2]
+prizefighters	-0.1	1.04403	[0, 0, -3, 0, 0, 0, 0, 1, 1, 0]
+prizefighting	0.4	0.91652	[0, 0, 0, 1, 0, 3, 0, 0, 0, 0]
+prizefights	0.3	0.78102	[1, 2, 0, 0, -1, 0, 0, 1, 0, 0]
+prizer	1.0	1.0	[0, 3, 0, 0, 2, 1, 2, 1, 0, 1]
+prizers	0.8	0.9798	[2, 0, 0, 1, 3, 1, 0, 1, 0, 0]
+prizes	2.0	1.09545	[3, 3, 2, 0, 2, 1, 2, 4, 1, 2]
+prizewinner	2.3	1.00499	[3, 0, 3, 3, 2, 2, 2, 4, 2, 2]
+prizewinners	2.4	1.11355	[4, 2, 2, 2, 0, 4, 2, 3, 3, 2]
+prizewinning	3.0	0.7746	[3, 3, 3, 3, 3, 4, 3, 1, 3, 4]
+proactive	1.8	0.87178	[2, 3, 3, 1, 1, 1, 1, 3, 1, 2]
+problem	-1.7	0.64031	[-2, -2, -1, -1, -1, -3, -1, -2, -2, -2]
+problematic	-1.9	0.53852	[-1, -2, -2, -2, -2, -3, -2, -1, -2, -2]
+problematical	-1.8	0.6	[-3, -1, -1, -2, -2, -2, -2, -2, -1, -2]
+problematically	-2.0	1.0	[-2, -1, -3, -1, -1, -2, -4, -3, -1, -2]
+problematics	-1.3	1.1	[0, -1, -1, 0, -2, -1, -4, -1, -2, -1]
+problems	-1.7	0.78102	[-2, -1, -1, -3, -2, -1, -3, -1, -1, -2]
+profit	1.9	0.7	[2, 3, 2, 1, 2, 1, 3, 1, 2, 2]
+profitabilities	1.1	0.7	[1, 1, 3, 1, 1, 1, 1, 0, 1, 1]
+profitability	1.1	1.44568	[1, 1, -2, 2, 0, 3, 1, 3, 2, 0]
+profitable	1.9	0.9434	[2, 3, 0, 3, 1, 2, 1, 3, 2, 2]
+profitableness	2.4	1.11355	[1, 4, 2, 4, 2, 2, 4, 2, 1, 2]
+profitably	1.6	0.91652	[1, 2, 0, 3, 1, 3, 1, 1, 2, 2]
+profited	1.3	1.00499	[2, 2, 2, 1, 0, 0, 1, 3, 0, 2]
+profiteer	0.8	1.6	[2, -2, -1, 3, -1, 2, 1, 2, 0, 2]
+profiteered	-0.5	1.9105	[0, 0, 2, -2, -3, -2, 3, 0, -3, 0]
+profiteering	-0.6	2.05913	[-1, 2, -2, -4, -2, 2, 1, -2, 2, -2]
+profiteers	0.5	1.5	[-2, 1, -1, -1, 1, -1, 2, 2, 2, 2]
+profiter	0.7	1.55242	[2, 2, 2, 1, -1, 1, -1, 3, 0, -2]
+profiterole	0.4	0.66332	[0, 0, 0, 0, 0, 1, 0, 1, 2, 0]
+profiteroles	0.5	0.92195	[0, 0, -1, 2, 2, 0, 0, 1, 0, 1]
+profiting	1.6	0.91652	[1, 0, 3, 2, 1, 2, 3, 1, 1, 2]
+profitless	-1.5	0.92195	[-2, -2, -3, -1, -1, -1, 0, -1, -1, -3]
+profits	1.9	1.04403	[2, 2, 1, 0, 2, 1, 2, 4, 3, 2]
+profitwise	0.9	0.83066	[1, 2, 0, 0, 1, 2, 2, 0, 1, 0]
+progress	1.8	0.74833	[3, 2, 1, 2, 3, 1, 1, 2, 2, 1]
+prominent	1.3	0.45826	[2, 1, 1, 2, 1, 1, 1, 2, 1, 1]
+promiscuities	-0.8	1.32665	[-1, 0, -2, -2, -1, 2, -3, -1, 0, 0]
+promiscuity	-1.8	1.07703	[-1, -2, -4, -2, -3, -1, 0, -2, -1, -2]
+promiscuous	-0.3	1.34536	[2, -3, -1, -1, 0, -1, 0, -1, 1, 1]
+promiscuously	-1.5	1.28452	[-2, -1, -3, 2, -2, -2, -1, -2, -2, -2]
+promiscuousness	-0.9	1.37477	[-3, -1, 1, -2, -2, 1, 1, -1, -2, -1]
+promise	1.3	0.64031	[1, 0, 1, 1, 2, 2, 1, 1, 2, 2]
+promised	1.5	0.92195	[2, 1, 1, 0, 0, 2, 2, 3, 2, 2]
+promisee	0.8	0.87178	[2, 1, 0, 0, 0, 2, 0, 2, 1, 0]
+promisees	1.1	0.9434	[2, 0, 1, 0, 0, 0, 2, 2, 2, 2]
+promiser	1.3	0.9	[2, 1, 1, 0, 0, 2, 2, 3, 1, 1]
+promisers	1.6	0.4899	[2, 1, 2, 1, 2, 1, 2, 1, 2, 2]
+promises	1.6	0.8	[2, 1, 1, 0, 2, 1, 3, 2, 2, 2]
+promising	1.7	0.45826	[1, 2, 2, 1, 2, 2, 1, 2, 2, 2]
+promisingly	1.2	0.6	[2, 2, 1, 1, 1, 2, 1, 0, 1, 1]
+promisor	1.0	0.63246	[2, 2, 0, 1, 1, 1, 0, 1, 1, 1]
+promisors	0.4	0.8	[0, 0, 0, 2, 0, 2, 0, 0, 0, 0]
+promissory	0.9	1.13578	[2, 0, 0, 3, 0, 2, 2, 0, 0, 0]
+promote	1.6	0.8	[2, 1, 2, 3, 0, 1, 2, 2, 1, 2]
+promoted	1.8	0.74833	[2, 2, 1, 1, 1, 2, 2, 1, 3, 3]
+promotes	1.4	0.91652	[1, 2, 0, 0, 1, 2, 2, 1, 3, 2]
+promoting	1.5	0.67082	[1, 2, 2, 1, 2, 1, 2, 0, 2, 2]
+propaganda	-1.0	1.54919	[-2, -3, -2, -3, -2, 1, -1, 1, 0, 1]
+prosecute	-1.7	1.00499	[-2, -2, -2, -1, -1, -2, 0, -1, -4, -2]
+prosecuted	-1.6	1.95959	[-2, -2, -2, -3, -3, -3, -4, 2, 2, -1]
+prosecutes	-1.8	1.53623	[-2, -2, -2, -3, -2, -2, -4, 1, 1, -3]
+prosecution	-2.2	1.07703	[-4, -1, -2, -2, -3, -2, -1, -4, -1, -2]
+prospect	1.2	0.87178	[1, 3, 1, 0, 2, 2, 1, 0, 1, 1]
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+prosperous	2.1	1.86815	[-3, 3, 3, 2, 4, 2, 3, 3, 3, 1]
+protect	1.6	0.8	[1, 3, 1, 1, 1, 1, 3, 2, 1, 2]
+protected	1.9	0.7	[1, 1, 2, 3, 2, 2, 2, 1, 3, 2]
+protects	1.3	0.78102	[2, 2, 0, 2, 1, 1, 0, 2, 2, 1]
+protest	-1.0	1.34164	[-2, -1, -1, -2, -1, -2, 1, -2, 2, -2]
+protested	-0.5	1.62788	[-2, -3, -1, -1, 0, 2, 2, -2, 1, -1]
+protesters	-0.9	0.7	[0, 0, 0, -1, -2, -2, -1, -1, -1, -1]
+protesting	-1.8	0.74833	[-2, -2, -1, -2, -1, -1, -2, -1, -3, -3]
+protests	-0.9	1.57797	[-2, -2, 2, 0, -1, -2, -2, -2, 2, -2]
+proud	2.1	0.3	[2, 3, 2, 2, 2, 2, 2, 2, 2, 2]
+prouder	2.2	1.16619	[2, 3, 3, 4, 0, 1, 1, 3, 2, 3]
+proudest	2.6	0.66332	[4, 2, 2, 2, 2, 3, 2, 3, 3, 3]
+proudful	1.9	1.51327	[3, 3, 0, 1, -1, 1, 4, 3, 2, 3]
+proudhearted	1.4	0.91652	[2, -1, 1, 2, 2, 1, 2, 2, 2, 1]
+proudly	2.6	0.4899	[2, 2, 3, 3, 2, 3, 3, 3, 2, 3]
+provoke	-1.7	0.64031	[-2, -2, -1, -1, -1, -2, -2, -1, -3, -2]
+provoked	-1.1	0.83066	[-1, -1, 0, -2, -2, -2, -2, 0, 0, -1]
+provokes	-1.3	0.78102	[-2, -2, -1, -2, -1, -2, -2, 0, 0, -1]
+provoking	-0.8	1.249	[-2, -2, -1, -2, 1, -1, 1, 1, -1, -2]
+pseudoscience	-1.2	1.32665	[-1, -1, -3, -4, 0, 0, -2, 0, 0, -1]
+puke	-2.4	1.0198	[-1, -3, -3, -2, -4, -4, -2, -1, -2, -2]
+puked	-1.8	0.6	[-1, -2, -2, -3, -1, -1, -2, -2, -2, -2]
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+puking	-1.8	1.46969	[0, -2, -4, -3, -2, -3, 1, -1, -1, -3]
+pukka	2.8	0.4	[3, 2, 3, 3, 3, 2, 3, 3, 3, 3]
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+punishable	-1.9	0.7	[-3, -1, -1, -2, -2, -1, -3, -2, -2, -2]
+punished	-2.0	0.44721	[-2, -2, -1, -2, -2, -2, -2, -2, -3, -2]
+punisher	-1.9	0.53852	[-3, -1, -2, -2, -2, -2, -2, -1, -2, -2]
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+punishing	-2.6	0.8	[-2, -3, -3, -3, -4, -1, -3, -2, -2, -3]
+punishment	-2.2	0.6	[-2, -1, -2, -2, -3, -3, -2, -2, -2, -3]
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+punitive	-2.3	0.78102	[-4, -2, -3, -1, -2, -2, -2, -2, -3, -2]
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+questionable	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+questioned	-0.4	1.0198	[-2, 0, 0, -1, -1, 2, 0, 0, -1, -1]
+questioning	-0.4	0.66332	[0, -1, -1, 0, 0, 0, -2, 0, 0, 0]
+racism	-3.1	0.9434	[-4, -4, -4, -2, -3, -4, -2, -2, -2, -4]
+racist	-3.0	0.89443	[-1, -3, -3, -4, -3, -4, -4, -2, -3, -3]
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+radiancy	1.4	0.66332	[2, 1, 1, 3, 1, 1, 1, 1, 2, 1]
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+raged	-2.0	0.63246	[-2, -1, -1, -3, -3, -2, -2, -2, -2, -2]
+ragee	-0.4	1.42829	[-2, -1, 0, 3, 0, -2, -2, 0, 0, 0]
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+raging	-2.4	1.0198	[-1, -3, -3, -1, -3, -3, -1, -4, -2, -3]
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+rancid	-2.5	1.11803	[-3, -3, -3, -2, -3, 0, -3, -1, -4, -3]
+rancidity	-2.6	0.8	[-4, -3, -3, -2, -2, -2, -2, -2, -2, -4]
+rancidly	-2.5	1.20416	[-2, -1, -4, -3, -4, -1, -2, -3, -4, -1]
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+rancidnesses	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -2, -1, -2]
+rant	-1.4	0.66332	[-1, -2, -2, -1, -2, -2, -2, -1, 0, -1]
+ranter	-1.2	1.16619	[-1, -2, -2, -2, -1, -1, -1, -2, 2, -2]
+ranters	-1.2	0.87178	[-1, -1, -1, 0, -1, -1, -3, -2, 0, -2]
+rants	-1.3	0.45826	[-1, -1, -1, -2, -1, -1, -1, -2, -2, -1]
+rape	-3.7	0.64031	[-4, -2, -4, -4, -4, -4, -4, -4, -3, -4]
+raped	-3.6	0.4899	[-3, -3, -4, -4, -3, -4, -4, -4, -3, -4]
+raper	-3.4	0.66332	[-3, -3, -4, -4, -3, -3, -4, -4, -2, -4]
+rapers	-3.6	0.66332	[-2, -4, -4, -3, -4, -3, -4, -4, -4, -4]
+rapes	-3.5	0.67082	[-4, -3, -4, -4, -3, -4, -4, -3, -2, -4]
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+raping	-3.8	0.4	[-3, -4, -4, -4, -4, -4, -4, -4, -3, -4]
+rapist	-3.9	0.3	[-4, -4, -4, -4, -4, -4, -3, -4, -4, -4]
+rapists	-3.3	0.64031	[-3, -3, -4, -3, -4, -3, -4, -2, -4, -3]
+rapture	0.6	2.2891	[-2, 2, -2, 3, 3, 4, -1, -1, 2, -2]
+raptured	0.9	1.97231	[0, -2, 0, 2, 4, -1, 4, -1, 1, 2]
+raptures	0.7	2.05183	[0, -2, 0, 2, 4, -2, 4, -1, 1, 1]
+rapturous	1.7	1.95192	[3, 4, 0, 3, 2, 2, 4, -2, -1, 2]
+rash	-1.7	0.78102	[-2, -1, -1, -3, -2, -2, -1, -1, -1, -3]
+ratified	0.6	0.4899	[1, 0, 0, 1, 1, 0, 1, 1, 0, 1]
+reach	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
+reached	0.4	0.4899	[1, 0, 0, 0, 1, 1, 0, 1, 0, 0]
+reaches	0.2	0.4	[0, 0, 0, 1, 0, 1, 0, 0, 0, 0]
+reaching	0.8	0.6	[1, 0, 2, 0, 1, 0, 1, 1, 1, 1]
+readiness	1.0	0.63246	[1, 1, 1, 1, 0, 1, 2, 1, 2, 0]
+ready	1.5	1.0247	[2, 1, 1, 0, 2, 2, 1, 1, 1, 4]
+reassurance	1.5	0.5	[1, 1, 1, 1, 2, 1, 2, 2, 2, 2]
+reassurances	1.4	0.8	[0, 1, 1, 2, 1, 1, 1, 2, 3, 2]
+reassure	1.4	0.4899	[2, 2, 1, 1, 2, 1, 2, 1, 1, 1]
+reassured	1.7	0.45826	[2, 1, 1, 1, 2, 2, 2, 2, 2, 2]
+reassures	1.5	0.92195	[2, 1, 1, 2, 2, 2, -1, 2, 2, 2]
+reassuring	1.7	1.48661	[3, 3, 2, -2, 1, 3, 3, 2, 1, 1]
+reassuringly	1.8	0.87178	[1, 3, 2, 1, 2, 3, 3, 1, 1, 1]
+rebel	-0.6	1.49666	[-2, -1, -1, 0, -2, -1, 2, 1, 1, -3]
+rebeldom	-1.5	1.0247	[-2, -2, -1, -3, -2, -2, -1, 1, -1, -2]
+rebelled	-1.0	1.26491	[-2, -2, 0, -2, 0, -2, -2, -1, -1, 2]
+rebelling	-1.1	1.51327	[-3, -1, -2, -1, -2, -1, -1, -3, 2, 1]
+rebellion	-0.5	1.80278	[-2, -2, -1, -1, 3, -1, 1, -3, 2, -1]
+rebellions	-1.1	1.57797	[-2, -4, -3, 0, 0, -1, 1, -2, -1, 1]
+rebellious	-1.2	1.249	[-2, -1, -3, -1, -2, -2, 1, -1, 1, -2]
+rebelliously	-1.8	0.87178	[-3, 0, -2, -2, -1, -2, -3, -1, -2, -2]
+rebelliousness	-1.2	1.16619	[0, -3, -1, -2, 1, -1, -2, 0, -2, -2]
+rebels	-0.8	1.07703	[-1, 0, 0, -2, 0, -3, 0, 0, 0, -2]
+recession	-1.8	1.07703	[-3, -1, -4, -2, -1, -1, -1, -1, -3, -1]
+reckless	-1.7	0.64031	[-2, -1, -1, -3, -1, -2, -1, -2, -2, -2]
+recommend	1.5	0.67082	[1, 1, 1, 1, 2, 3, 2, 2, 1, 1]
+recommended	0.8	1.07703	[1, 1, 0, -2, 1, 2, 1, 2, 1, 1]
+recommends	0.9	0.9434	[1, 1, 2, 0, 0, 2, 1, -1, 2, 1]
+redeemed	1.3	0.9	[2, 1, 2, 2, 1, -1, 2, 1, 2, 1]
+reek	-2.4	0.66332	[-3, -3, -2, -3, -3, -2, -2, -2, -1, -3]
+reeked	-2.0	1.09545	[-4, -3, -2, -3, -1, -2, 0, -1, -2, -2]
+reeker	-1.7	1.1	[0, -2, -1, 0, -3, -3, -2, -1, -3, -2]
+reekers	-1.5	1.0247	[-3, 0, 0, 0, -2, -2, -2, -2, -2, -2]
+reeking	-2.0	1.48324	[2, -2, -2, -3, -3, -3, -1, -3, -3, -2]
+refuse	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -1, -2, -2, -1]
+refused	-1.2	0.74833	[0, -1, -1, -1, -1, -1, -2, -1, -3, -1]
+refusing	-1.7	0.64031	[-1, -1, -1, -2, -2, -2, -3, -1, -2, -2]
+regret	-1.8	0.6	[-2, -2, -2, -2, -1, -3, -1, -1, -2, -2]
+regretful	-1.9	0.83066	[-1, -2, -1, -2, -1, -2, -1, -3, -3, -3]
+regretfully	-1.9	0.83066	[-1, -1, -1, -3, -2, -3, -1, -3, -2, -2]
+regretfulness	-1.6	0.66332	[-1, -3, -1, -1, -1, -2, -1, -2, -2, -2]
+regrets	-1.5	0.5	[-2, -2, -2, -1, -2, -1, -1, -2, -1, -1]
+regrettable	-2.3	0.78102	[-3, -1, -2, -1, -3, -2, -3, -3, -2, -3]
+regrettably	-2.0	0.63246	[-2, -3, -1, -3, -2, -1, -2, -2, -2, -2]
+regretted	-1.6	0.4899	[-2, -1, -2, -2, -2, -2, -1, -1, -1, -2]
+regretter	-1.6	0.66332	[-2, -1, -2, -2, -3, -2, -1, -1, -1, -1]
+regretters	-2.0	0.89443	[-1, -2, -2, -2, -4, -3, -1, -1, -2, -2]
+regretting	-1.7	0.78102	[-3, -2, -2, -1, -3, -1, -1, -1, -2, -1]
+reinvigorate	2.3	0.78102	[3, 3, 3, 2, 3, 1, 2, 1, 2, 3]
+reinvigorated	1.9	1.13578	[2, 2, 3, 1, 2, 3, 3, -1, 2, 2]
+reinvigorates	1.8	0.9798	[2, 2, 3, 0, 2, 2, 3, 0, 2, 2]
+reinvigorating	1.7	0.64031	[1, 2, 1, 1, 2, 2, 2, 1, 3, 2]
+reinvigoration	2.2	0.4	[2, 2, 2, 3, 2, 3, 2, 2, 2, 2]
+reject	-1.7	0.64031	[-1, -2, -2, -2, -1, -3, -1, -1, -2, -2]
+rejected	-2.3	0.45826	[-3, -2, -3, -3, -2, -2, -2, -2, -2, -2]
+rejectee	-2.3	0.45826	[-3, -2, -2, -3, -2, -3, -2, -2, -2, -2]
+rejectees	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -2, -2, -1]
+rejecter	-1.6	0.66332	[-2, -1, -1, -3, -2, -2, -1, -1, -1, -2]
+rejecters	-1.8	0.6	[-2, -3, -1, -1, -2, -1, -2, -2, -2, -2]
+rejecting	-2.0	0.7746	[-1, -2, -3, -1, -2, -3, -2, -1, -3, -2]
+rejectingly	-1.7	0.64031	[-1, -2, -2, -2, -1, -2, -2, -1, -3, -1]
+rejection	-2.5	0.67082	[-3, -3, -2, -4, -3, -2, -2, -2, -2, -2]
+rejections	-2.1	0.53852	[-3, -2, -2, -2, -1, -2, -3, -2, -2, -2]
+rejective	-1.8	0.6	[-3, -2, -2, -2, -1, -1, -2, -2, -1, -2]
+rejector	-1.8	0.74833	[-2, -1, -2, -3, -1, -2, -1, -2, -3, -1]
+rejects	-2.2	0.4	[-3, -2, -2, -2, -2, -3, -2, -2, -2, -2]
+rejoice	1.9	0.9434	[2, 3, 1, 3, 1, 3, 1, 3, 1, 1]
+rejoiced	2.0	0.63246	[2, 1, 2, 3, 2, 2, 3, 1, 2, 2]
+rejoices	2.1	0.7	[2, 1, 2, 3, 2, 3, 3, 2, 2, 1]
+rejoicing	2.8	0.4	[3, 3, 2, 3, 3, 3, 2, 3, 3, 3]
+relax	1.9	1.13578	[2, 1, 1, 1, 4, 4, 2, 1, 1, 2]
+relaxant	1.0	0.89443	[2, 1, 0, 0, 1, 0, 1, 3, 1, 1]
+relaxants	0.7	0.9	[0, 1, 1, 0, -1, 2, 1, 2, 1, 0]
+relaxation	2.4	0.4899	[3, 2, 3, 2, 2, 3, 3, 2, 2, 2]
+relaxations	1.0	0.89443	[-1, 0, 2, 1, 1, 2, 1, 2, 1, 1]
+relaxed	2.2	0.87178	[2, 3, 1, 3, 3, 3, 1, 2, 1, 3]
+relaxedly	1.5	0.5	[2, 2, 1, 1, 2, 1, 2, 2, 1, 1]
+relaxedness	2.0	0.63246	[2, 2, 3, 1, 3, 2, 2, 2, 1, 2]
+relaxer	1.6	0.8	[0, 2, 1, 2, 1, 3, 1, 2, 2, 2]
+relaxers	1.4	0.4899	[2, 1, 1, 1, 2, 2, 2, 1, 1, 1]
+relaxes	1.5	0.5	[2, 1, 1, 1, 1, 2, 2, 2, 1, 2]
+relaxin	1.7	0.64031	[2, 2, 1, 2, 0, 2, 2, 2, 2, 2]
+relaxing	2.2	0.6	[1, 2, 2, 2, 2, 3, 3, 3, 2, 2]
+relaxins	1.2	1.4	[1, 3, 2, 1, 0, 1, -2, 3, 2, 1]
+relentless	0.2	1.07703	[3, -1, 0, -1, 0, 1, 0, 0, 0, 0]
+reliant	0.5	1.20416	[0, 2, -1, 1, 0, 1, 2, -1, 2, -1]
+relief	2.1	0.53852	[2, 2, 2, 3, 2, 3, 2, 1, 2, 2]
+reliefs	1.3	0.78102	[1, 2, 2, 2, 2, 2, 0, 0, 1, 1]
+relievable	1.1	1.22066	[1, -2, 1, 1, 1, 1, 3, 2, 1, 2]
+relieve	1.5	0.5	[1, 2, 1, 2, 1, 1, 2, 2, 1, 2]
+relieved	1.6	0.66332	[2, 1, 2, 1, 1, 3, 2, 1, 1, 2]
+relievedly	1.4	0.4899	[1, 2, 1, 1, 1, 2, 2, 2, 1, 1]
+reliever	1.5	0.80623	[2, 1, 2, 2, 1, 2, 0, 1, 1, 3]
+relievers	1.0	0.63246	[1, 1, 1, 1, 2, 0, 2, 0, 1, 1]
+relieves	1.5	0.80623	[2, 1, 2, 2, 1, 2, 0, 1, 1, 3]
+relieving	1.5	1.0247	[2, 2, 1, 2, 3, -1, 2, 1, 1, 2]
+relievo	1.3	1.00499	[0, 2, 1, 2, 2, -1, 2, 2, 2, 1]
+relishing	1.6	0.8	[1, 2, 1, 3, 2, 3, 1, 1, 1, 1]
+reluctance	-1.4	0.4899	[-2, -2, -1, -1, -1, -1, -2, -1, -2, -1]
+reluctancy	-1.6	0.8	[-3, -2, -1, -1, -1, -1, -2, -1, -3, -1]
+reluctant	-1.0	0.7746	[0, -1, 0, -1, -1, 0, -1, -2, -2, -2]
+reluctantly	-0.4	1.42829	[-1, 2, -1, -2, -2, -1, 1, -1, 2, -1]
+remarkable	2.6	1.0198	[3, 4, 3, 2, 2, 3, 3, 0, 3, 3]
+remorse	-1.1	1.51327	[-3, -1, -3, 1, 2, -2, -1, -1, -2, -1]
+remorseful	-0.9	2.07123	[-1, 1, -2, -3, 2, -1, -3, -2, 3, -3]
+remorsefully	-0.7	1.34536	[-1, -1, 0, -1, -2, -1, -1, 1, -3, 2]
+remorsefulness	-0.7	1.61555	[-1, -2, 2, -2, -2, -1, 0, -3, 2, 0]
+remorseless	-2.3	0.64031	[-4, -2, -2, -2, -3, -2, -2, -2, -2, -2]
+remorselessly	-2.0	1.09545	[-3, -3, -3, -2, -1, -1, -4, -1, -1, -1]
+remorselessness	-2.8	1.16619	[-3, -4, -2, -2, -3, -4, -1, -1, -4, -4]
+repetitive	-1.0	0.06325	[-1, -1, 0, -2, -1, -2, -1, -1, 0, -1]
+repress	-1.4	0.66332	[-1, -1, -3, -2, -1, -1, -2, -1, -1, -1]
+repressed	-1.3	0.78102	[-1, 0, -3, -1, -1, -2, -1, -1, -2, -1]
+represses	-1.3	1.00499	[-1, 0, -3, -1, 0, -3, -1, -1, -2, -1]
+repressible	-1.5	0.92195	[-1, -2, -3, -1, 0, -1, -3, -1, -2, -1]
+repressing	-1.8	0.6	[-1, -2, -2, -2, -1, -3, -2, -1, -2, -2]
+repression	-1.6	0.91652	[-2, -2, -1, -1, -1, -1, -4, -1, -2, -1]
+repressions	-1.7	1.00499	[-2, -3, -1, -2, -2, -3, -2, 0, 0, -2]
+repressive	-1.4	1.11355	[-3, -1, -1, -2, -1, -3, 1, -2, -1, -1]
+repressively	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -2, -2, -1, -1]
+repressiveness	-1.0	1.73205	[-2, -1, -2, -3, -1, -1, 1, -3, 3, -1]
+repressor	-1.4	1.28062	[-1, 0, -3, -1, -2, -4, 0, -1, 0, -2]
+repressors	-2.2	1.66132	[-2, -4, 0, -2, -1, -3, -4, -3, 1, -4]
+repressurize	-0.3	0.64031	[0, 0, 0, 0, 0, 0, -2, 0, -1, 0]
+repressurized	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+repressurizes	0.1	0.3	[0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
+repressurizing	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+repulse	-2.8	0.4	[-3, -3, -3, -3, -2, -3, -3, -3, -2, -3]
+repulsed	-2.2	0.9798	[0, -2, -2, -2, -3, -3, -1, -3, -3, -3]
+rescue	2.3	0.78102	[1, 3, 1, 3, 2, 3, 3, 2, 2, 3]
+rescued	1.8	1.53623	[3, 2, 2, -2, 3, 2, 1, 4, 1, 2]
+rescues	1.3	0.78102	[3, 2, 0, 2, 1, 1, 1, 1, 1, 1]
+resent	-0.7	1.26886	[-2, -2, 0, -1, -1, -1, -2, 1, 2, -1]
+resented	-1.6	1.35647	[-2, -3, -2, -2, -1, -1, 2, -3, -2, -2]
+resentence	-1.0	0.7746	[-1, 0, -1, -1, 0, -2, -1, 0, -2, -2]
+resentenced	-0.8	0.9798	[0, -2, -1, 0, -1, 0, 0, 0, -3, -1]
+resentences	-0.6	0.8	[0, -2, -1, 0, -1, 0, 0, 0, -2, 0]
+resentencing	0.2	0.87178	[-1, -1, 0, 1, 0, 0, 1, 2, 0, 0]
+resentful	-2.1	0.83066	[-3, -1, -2, -3, -1, -1, -3, -2, -2, -3]
+resentfully	-1.4	1.11355	[-1, -2, -1, -1, -3, 1, -1, -3, -1, -2]
+resentfulness	-2.0	0.7746	[-2, -2, -3, -3, -2, -3, -2, -1, -1, -1]
+resenting	-1.2	1.72047	[-2, -1, -2, -2, -1, -3, -3, 2, 2, -2]
+resentment	-1.9	0.83066	[-1, -3, -2, -3, -2, -3, -1, -1, -1, -2]
+resentments	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -2, -2, -1, -3]
+resents	-1.2	1.32665	[-2, -1, -1, -3, 1, -1, 1, -3, -2, -1]
+resign	-1.4	0.66332	[-2, -1, -3, -1, -1, -1, -1, -2, -1, -1]
+resignation	-1.2	0.4	[-1, -1, -1, -2, -1, -1, -1, -1, -2, -1]
+resignations	-1.2	0.6	[0, -1, -1, -2, -2, -2, -1, -1, -1, -1]
+resigned	-1.0	0.63246	[-2, -1, 0, -1, -2, -1, -1, -1, 0, -1]
+resignedly	-0.7	1.26886	[-3, -1, -1, -1, -1, 1, 1, 1, -2, -1]
+resignedness	-0.8	1.07703	[-1, -2, 1, -2, -1, -1, 0, -2, -1, 1]
+resigner	-1.2	0.6	[-2, -1, 0, -1, -2, -2, -1, -1, -1, -1]
+resigners	-1.0	1.09545	[-1, 0, -1, -3, -1, 0, 0, -1, -3, 0]
+resigning	-0.9	1.22066	[-1, -1, -1, -1, -1, 0, -1, -3, -2, 2]
+resigns	-1.3	0.9	[0, -1, -1, 0, -2, -1, -3, -1, -2, -2]
+resolute	1.1	0.53852	[2, 1, 0, 1, 1, 1, 2, 1, 1, 1]
+resolvable	1.0	0.0	[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
+resolve	1.6	0.66332	[2, 1, 1, 2, 2, 1, 3, 1, 1, 2]
+resolved	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
+resolvent	0.7	0.78102	[1, 0, 1, 2, 0, -1, 1, 1, 1, 1]
+resolvents	0.4	0.66332	[2, 0, 0, 1, 0, 0, 1, 0, 0, 0]
+resolver	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
+resolvers	1.4	0.4899	[2, 1, 2, 1, 1, 1, 2, 1, 2, 1]
+resolves	0.7	0.78102	[1, 2, 0, 1, 1, 0, 2, 0, 0, 0]
+resolving	1.6	0.4899	[2, 2, 1, 2, 2, 1, 1, 1, 2, 2]
+respect	2.1	0.53852	[2, 2, 2, 2, 3, 3, 2, 2, 1, 2]
+respectabilities	1.8	0.4	[2, 2, 2, 1, 2, 2, 2, 1, 2, 2]
+respectability	2.4	0.8	[4, 1, 3, 2, 3, 3, 2, 2, 2, 2]
+respectable	1.9	0.7	[2, 2, 2, 2, 1, 3, 3, 1, 1, 2]
+respectableness	1.2	1.32665	[2, 1, 1, 0, 3, 2, -2, 2, 2, 1]
+respectably	1.7	0.78102	[2, 2, 1, 3, 1, 3, 2, 1, 1, 1]
+respected	2.1	0.7	[2, 2, 1, 2, 3, 1, 2, 3, 3, 2]
+respecter	2.1	0.53852	[3, 2, 2, 2, 2, 2, 1, 3, 2, 2]
+respecters	1.6	0.8	[2, 1, 2, 2, 3, 1, 2, 2, 0, 1]
+respectful	2.0	0.7746	[1, 1, 3, 2, 2, 3, 1, 2, 3, 2]
+respectfully	1.7	0.64031	[1, 2, 1, 2, 2, 2, 1, 3, 1, 2]
+respectfulness	1.9	1.37477	[4, 2, 2, 1, 2, 4, -1, 1, 2, 2]
+respectfulnesses	1.3	1.18743	[1, 1, 2, 2, 2, 2, 2, 1, -2, 2]
+respecting	2.2	0.6	[1, 3, 2, 3, 2, 2, 3, 2, 2, 2]
+respective	1.8	1.16619	[2, 2, 3, 0, 1, 3, 3, 1, 0, 3]
+respectively	1.4	0.91652	[0, 0, 2, 2, 0, 2, 2, 2, 2, 2]
+respectiveness	1.1	1.04403	[0, 2, 1, 0, 1, 0, 2, 2, 0, 3]
+respects	1.3	1.00499	[2, 0, 0, 0, 2, 1, 2, 1, 2, 3]
+responsible	1.3	1.1	[1, 1, 0, 4, 2, 2, 1, 0, 1, 1]
+responsive	1.5	0.92195	[3, 1, 1, 0, 1, 1, 2, 3, 2, 1]
+restful	1.5	0.67082	[1, 1, 1, 1, 2, 1, 2, 1, 2, 3]
+restless	-1.1	0.3	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -1]
+restlessly	-1.4	0.91652	[-1, -4, -1, -1, -1, -2, -1, -1, -1, -1]
+restlessness	-1.2	0.74833	[-3, -1, -1, 0, -1, -2, -1, -1, -1, -1]
+restore	1.2	0.9798	[1, 1, 2, 2, 2, 2, 1, -1, 0, 2]
+restored	1.4	0.91652	[2, 2, 1, 2, 1, 2, 2, 1, -1, 2]
+restores	1.2	0.6	[2, 1, 1, 2, 1, 0, 1, 1, 2, 1]
+restoring	1.2	0.4	[2, 1, 1, 1, 1, 2, 1, 1, 1, 1]
+restrict	-1.6	0.8	[-3, -1, -1, -1, -3, -1, -2, -1, -1, -2]
+restricted	-1.6	0.4899	[-1, -2, -1, -1, -1, -2, -2, -2, -2, -2]
+restricting	-1.6	0.4899	[-2, -2, -2, -2, -1, -2, -1, -1, -2, -1]
+restriction	-1.1	0.9434	[-1, -1, -1, -1, -3, 1, -2, -1, -1, -1]
+restricts	-1.3	1.1	[-2, -2, -3, -1, -1, -2, 1, -1, -2, 0]
+retained	0.1	0.7	[-1, 1, 1, 1, 0, -1, 0, 0, 0, 0]
+retard	-2.4	0.8	[-2, -2, -2, -1, -3, -2, -4, -3, -3, -2]
+retarded	-2.7	1.26886	[-4, -1, -3, -3, -4, -4, -2, -1, -1, -4]
+retreat	0.8	1.07703	[2, 2, 0, 0, -1, 1, 2, 0, 2, 0]
+revenge	-2.4	0.66332	[-2, -3, -2, -3, -3, -3, -2, -1, -2, -3]
+revenged	-0.9	1.37477	[-2, -3, -2, -1, -1, 2, -1, 1, -1, -1]
+revengeful	-2.4	0.4899	[-2, -2, -2, -3, -3, -2, -3, -3, -2, -2]
+revengefully	-1.4	2.00998	[-3, -2, -2, -2, 3, 2, -3, -3, -2, -2]
+revengefulness	-2.2	0.87178	[-2, -3, -3, -2, -2, -2, -1, -4, -1, -2]
+revenger	-2.1	0.83066	[-2, -3, -2, -1, -1, -2, -3, -3, -1, -3]
+revengers	-2.0	0.44721	[-2, -2, -3, -2, -2, -2, -1, -2, -2, -2]
+revenges	-1.9	0.7	[-2, -3, -2, -1, -1, -2, -3, -2, -1, -2]
+revered	2.3	1.1	[3, 3, 1, 3, 3, 3, 0, 3, 3, 1]
+revive	1.4	1.11355	[4, 0, 2, 1, 1, 0, 2, 2, 1, 1]
+revives	1.6	0.4899	[1, 1, 2, 2, 1, 2, 2, 2, 1, 2]
+reward	2.7	0.78102	[3, 4, 1, 2, 3, 3, 2, 3, 3, 3]
+rewardable	2.0	1.0	[3, 1, 4, 3, 1, 2, 1, 2, 2, 1]
+rewarded	2.2	0.74833	[1, 2, 3, 2, 2, 4, 2, 2, 2, 2]
+rewarder	1.6	0.8	[1, 2, 3, 1, 1, 3, 2, 1, 1, 1]
+rewarders	1.9	0.83066	[1, 2, 2, 1, 3, 3, 1, 2, 1, 3]
+rewarding	2.4	0.8	[3, 4, 2, 2, 1, 3, 3, 2, 2, 2]
+rewardingly	2.4	0.8	[3, 2, 3, 4, 3, 2, 2, 2, 1, 2]
+rewards	2.1	0.83066	[2, 1, 3, 4, 2, 2, 2, 2, 1, 2]
+rich	2.6	0.8	[2, 3, 2, 4, 4, 3, 2, 2, 2, 2]
+richened	1.9	0.83066	[3, 2, 2, 1, 3, 1, 2, 3, 1, 1]
+richening	1.0	1.34164	[2, 2, 0, 0, -1, 1, 2, 3, -1, 2]
+richens	0.8	0.9798	[1, 0, 3, 0, 0, 0, 1, 2, 1, 0]
+richer	2.4	1.2	[1, 4, 2, 1, 2, 4, 4, 1, 3, 2]
+riches	2.4	1.0198	[2, 4, 1, 1, 2, 4, 3, 2, 3, 2]
+richest	2.4	1.11355	[4, 4, 2, 2, 3, 0, 2, 2, 3, 2]
+richly	1.9	0.53852	[2, 2, 2, 2, 3, 1, 2, 2, 1, 2]
+richness	2.2	0.74833	[2, 3, 2, 2, 2, 2, 2, 1, 4, 2]
+richnesses	2.1	0.9434	[2, 1, 2, 2, 3, 1, 3, 1, 4, 2]
+richweed	0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 1, 0, 0]
+richweeds	-0.1	0.3	[0, 0, 0, 0, 0, 0, 0, 0, 0, -1]
+ridicule	-2.0	0.63246	[-2, -2, -2, -2, -3, -2, -1, -2, -1, -3]
+ridiculed	-1.5	0.5	[-1, -1, -1, -2, -2, -2, -1, -2, -1, -2]
+ridiculer	-1.6	0.91652	[-1, -1, -1, -2, -2, 0, -1, -3, -2, -3]
+ridiculers	-1.6	0.66332	[-2, -1, -1, -2, -3, -2, -1, -2, -1, -1]
+ridicules	-1.8	0.6	[-1, -1, -2, -2, -2, -2, -1, -2, -2, -3]
+ridiculing	-1.8	0.6	[-2, -3, -2, -1, -1, -2, -2, -1, -2, -2]
+ridiculous	-1.5	0.67082	[-3, -2, -1, -1, -2, -1, -2, -1, -1, -1]
+ridiculously	-1.4	0.8	[-1, -2, -1, 0, -2, -1, -1, -3, -1, -2]
+ridiculousness	-1.1	1.51327	[-1, -1, -1, -2, -1, 3, -3, -2, -1, -2]
+ridiculousnesses	-1.6	1.11355	[-3, 0, -2, -2, -1, -1, -1, -4, -1, -1]
+rig	-0.5	1.0247	[0, 0, 0, 0, -2, 0, 0, 0, -3, 0]
+rigged	-1.5	1.0247	[-2, -3, -2, -1, -1, -2, 1, -1, -2, -2]
+rigid	-0.5	0.67082	[-2, -1, 0, 0, 0, 0, 0, -1, -1, 0]
+rigidification	-1.1	0.9434	[-1, -2, 0, 0, 0, -2, -2, -2, 0, -2]
+rigidifications	-0.8	0.9798	[-2, -1, 0, 0, -2, -1, 0, 1, -2, -1]
+rigidified	-0.7	1.00499	[0, -1, 0, 0, 0, 0, -2, 0, -1, -3]
+rigidifies	-0.6	0.8	[0, -1, 0, 0, 0, 0, -2, 0, -1, -2]
+rigidify	-0.3	0.64031	[0, 0, 0, 0, -1, 0, 0, 0, -2, 0]
+rigidities	-0.7	0.78102	[0, -1, 0, 0, 0, 0, -2, -1, -1, -2]
+rigidity	-0.7	0.64031	[-1, 0, -1, 0, -1, 0, -2, 0, -1, -1]
+rigidly	-0.7	0.45826	[-1, -1, -1, -1, 0, 0, -1, 0, -1, -1]
+rigidness	-0.3	1.00499	[0, -1, -1, 0, 2, -1, -1, -1, 1, -1]
+rigorous	-1.1	1.51327	[-2, -3, 1, 0, 1, 0, -1, -1, -3, -3]
+rigorously	-0.4	1.28062	[0, 2, 1, 0, -1, 0, -1, -1, -3, -1]
+riot	-2.6	1.0198	[-3, 0, -3, -2, -3, -3, -3, -4, -3, -2]
+riots	-2.3	0.78102	[-2, -3, -3, -2, -1, -1, -3, -2, -3, -3]
+risk	-1.1	0.7	[-1, -1, 0, -2, -1, 0, -2, -2, -1, -1]
+risked	-0.9	0.7	[-1, -2, 0, 0, -1, 0, -2, -1, -1, -1]
+risker	-0.8	0.4	[-1, -1, -1, 0, -1, 0, -1, -1, -1, -1]
+riskier	-1.4	0.91652	[0, -3, -1, 0, -1, -2, -1, -2, -2, -2]
+riskiest	-1.5	1.0247	[-2, -3, -1, -1, -3, 0, -1, -2, 0, -2]
+riskily	-0.7	1.34536	[-1, -2, -1, -1, 3, 0, -1, -1, -1, -2]
+riskiness	-1.3	1.00499	[-3, -1, -1, 0, -1, 0, -1, -3, -2, -1]
+riskinesses	-1.6	0.91652	[-2, -1, -1, 0, -3, -1, -2, -1, -3, -2]
+risking	-1.3	1.1	[0, 0, -2, 0, -1, -3, -3, -1, -2, -1]
+riskless	1.3	0.9	[2, 1, 0, 1, 1, 1, 2, 3, 0, 2]
+risks	-1.1	0.9434	[-1, 0, -1, -1, 0, 0, -2, -1, -3, -2]
+risky	-0.8	0.9798	[-1, 1, -1, -1, -1, 0, 0, -1, -3, -1]
+rob	-2.6	0.8	[-2, -4, -3, -2, -3, -4, -2, -2, -2, -2]
+robber	-2.6	1.0198	[-4, -1, -2, -3, -2, -1, -4, -3, -3, -3]
+robed	-0.7	0.9	[-2, 0, 0, 0, 0, -2, 0, -2, -1, 0]
+robing	-1.5	1.56525	[0, 0, 0, 0, -2, -3, -3, -4, -3, 0]
+robs	-2.0	1.0	[-2, -1, -3, -2, -2, -1, -4, -3, -1, -1]
+robust	1.4	1.42829	[1, 0, 0, 1, 4, 0, 2, 3, 3, 0]
+roflcopter	2.1	0.53852	[2, 2, 2, 1, 3, 2, 3, 2, 2, 2]
+romance	2.6	0.66332	[2, 3, 4, 2, 3, 2, 3, 2, 3, 2]
+romanced	2.2	0.87178	[2, 3, 2, 4, 2, 1, 2, 3, 1, 2]
+romancer	1.3	1.1	[0, 0, 2, 2, 2, 2, 3, 2, 0, 0]
+romancers	1.7	1.00499	[0, 2, 2, 2, 2, 2, 1, 3, 0, 3]
+romances	1.3	0.9	[0, 1, 2, 2, 2, 2, 2, 2, 0, 0]
+romancing	2.0	0.89443	[4, 1, 1, 2, 2, 2, 2, 1, 3, 2]
+romantic	1.7	0.78102	[2, 2, 2, 1, 2, 3, 2, 2, 0, 1]
+romantically	1.8	0.87178	[3, 1, 2, 0, 1, 2, 2, 2, 3, 2]
+romanticise	1.7	1.61555	[-1, 4, 2, 1, 3, 1, 3, 3, 2, -1]
+romanticised	1.7	0.9	[2, 2, 2, 2, 2, 2, 3, 0, 2, 0]
+romanticises	1.3	1.1	[2, 2, 1, 1, 1, 2, 3, -1, 2, 0]
+romanticising	2.7	0.78102	[3, 3, 3, 2, 1, 3, 2, 3, 4, 3]
+romanticism	2.2	1.32665	[1, 4, 2, 1, 3, 1, 3, 3, 4, 0]
+romanticisms	2.1	0.9434	[2, 3, 2, 1, 2, 3, 3, 2, 3, 0]
+romanticist	1.9	1.3	[1, 4, 2, 0, 3, 1, 2, 3, 3, 0]
+romanticists	1.3	1.00499	[2, 0, 0, 1, 3, 3, 1, 1, 1, 1]
+romanticization	1.5	1.36015	[1, 3, 2, 2, -1, 2, 0, 1, 4, 1]
+romanticizations	2.0	1.0	[4, 1, 3, 1, 2, 3, 1, 2, 2, 1]
+romanticize	1.8	0.9798	[2, 2, 1, 1, 2, 1, 3, 3, 3, 0]
+romanticized	0.9	1.22066	[0, 1, 1, 3, -1, 0, 1, 1, 3, 0]
+romanticizes	1.8	0.87178	[2, 3, 2, 1, 2, 3, 0, 1, 2, 2]
+romanticizing	1.2	1.07703	[0, 1, 2, 1, 3, 0, 1, 1, 0, 3]
+romantics	1.9	0.83066	[2, 3, 2, 1, 0, 2, 3, 2, 2, 2]
+rotten	-2.3	0.78102	[-2, -3, -1, -3, -3, -1, -3, -2, -3, -2]
+rude	-2.0	0.44721	[-2, -1, -3, -2, -2, -2, -2, -2, -2, -2]
+rudely	-2.2	0.87178	[-3, -2, -3, -1, -2, -4, -2, -2, -1, -2]
+rudeness	-1.5	0.67082	[-2, -1, -1, -1, -1, -3, -2, -2, -1, -1]
+ruder	-2.1	0.83066	[-2, -1, -4, -2, -3, -1, -2, -2, -2, -2]
+ruderal	-0.8	1.46969	[-3, 0, -1, -2, 0, -1, -3, 0, 2, 0]
+ruderals	-0.4	0.66332	[0, -1, 0, -2, 0, -1, 0, 0, 0, 0]
+rudesby	-2.0	0.7746	[-2, -3, -2, -2, -1, -3, -1, -1, -2, -3]
+rudest	-2.5	0.5	[-3, -2, -3, -3, -2, -2, -2, -3, -2, -3]
+ruin	-2.8	0.87178	[-3, -3, -1, -4, -4, -3, -3, -2, -2, -3]
+ruinable	-1.6	0.8	[-1, -2, -1, -3, -1, -3, -1, -1, -2, -1]
+ruinate	-2.8	0.87178	[-4, -4, -3, -3, -1, -3, -3, -3, -2, -2]
+ruinated	-1.5	1.56525	[0, -4, 0, -4, -1, -2, 0, -1, -3, 0]
+ruinates	-1.5	1.56525	[0, -4, 0, -4, -1, -2, 0, -1, -3, 0]
+ruinating	-1.5	1.20416	[-2, -2, -2, -3, 0, -1, 1, -3, -1, -2]
+ruination	-2.7	1.00499	[-4, -4, -3, -3, -2, -1, -3, -3, -3, -1]
+ruinations	-1.6	1.35647	[-2, -2, -3, -4, 0, -1, 1, -2, -1, -2]
+ruined	-2.1	0.7	[-3, -2, -2, -1, -2, -2, -3, -3, -1, -2]
+ruiner	-2.0	0.63246	[-1, -3, -2, -2, -1, -2, -3, -2, -2, -2]
+ruing	-1.6	0.91652	[-2, -1, -2, -1, -1, -1, -3, 0, -3, -2]
+ruining	-1.0	1.94936	[-3, -3, 0, -2, 1, -3, 2, -2, 2, -2]
+ruinous	-2.7	0.78102	[-2, -3, -3, -3, -3, -4, -2, -3, -1, -3]
+ruinously	-2.6	0.8	[-3, -2, -2, -3, -1, -3, -4, -2, -3, -3]
+ruinousness	-1.0	1.09545	[-1, -2, -3, -1, -1, -2, 1, 0, -1, 0]
+ruins	-1.9	0.9434	[-1, -2, -1, -2, -1, -2, -4, -1, -3, -2]
+sabotage	-2.4	0.91652	[-3, -3, -3, -2, -2, -4, -2, -3, -1, -1]
+sad	-2.1	0.9434	[-1, -1, -2, -2, -3, -2, -3, -2, -4, -1]
+sadden	-2.6	0.4899	[-2, -3, -2, -3, -2, -3, -2, -3, -3, -3]
+saddened	-2.4	0.4899	[-3, -2, -3, -2, -3, -3, -2, -2, -2, -2]
+saddening	-2.2	0.4	[-3, -2, -2, -2, -2, -2, -3, -2, -2, -2]
+saddens	-1.9	0.7	[-3, -1, -1, -1, -2, -2, -2, -2, -3, -2]
+sadder	-2.4	0.91652	[-2, -2, -3, -4, -3, -1, -3, -1, -2, -3]
+saddest	-3.0	0.63246	[-4, -3, -2, -3, -3, -2, -3, -4, -3, -3]
+sadly	-1.8	0.6	[-2, -2, -2, -1, -2, -3, -2, -1, -1, -2]
+sadness	-1.9	0.3	[-2, -1, -2, -2, -2, -2, -2, -2, -2, -2]
+safe	1.9	0.3	[2, 1, 2, 2, 2, 2, 2, 2, 2, 2]
+safecracker	-0.7	1.61555	[-3, -2, 0, -3, 0, -2, 0, 1, 2, 0]
+safecrackers	-0.9	1.04403	[-1, 0, -2, 0, -1, 0, 0, -3, 0, -2]
+safecracking	-0.9	0.9434	[0, 0, 0, 0, -2, 0, -1, -2, -2, -2]
+safecrackings	-0.7	1.67631	[-2, -1, -2, -4, 2, -1, -1, 0, 1, 1]
+safeguard	1.6	0.4899	[2, 2, 1, 1, 1, 2, 2, 2, 2, 1]
+safeguarded	1.5	0.92195	[1, 2, 2, 0, 2, 0, 3, 1, 2, 2]
+safeguarding	1.1	0.7	[2, 1, 1, 0, 1, 0, 2, 1, 1, 2]
+safeguards	1.4	0.66332	[1, 2, 1, 1, 0, 2, 2, 2, 2, 1]
+safekeeping	1.4	0.66332	[3, 1, 1, 2, 1, 1, 2, 1, 1, 1]
+safelight	1.1	1.22066	[0, 3, 0, 2, 0, 3, 0, 2, 1, 0]
+safelights	0.8	1.07703	[0, 3, 1, 0, 0, 2, 0, 2, 0, 0]
+safely	2.2	0.74833	[2, 2, 2, 3, 4, 2, 2, 1, 2, 2]
+safeness	1.5	0.67082	[1, 1, 1, 1, 3, 1, 2, 2, 2, 1]
+safer	1.8	0.6	[2, 1, 2, 3, 2, 2, 1, 1, 2, 2]
+safes	0.4	0.8	[0, 0, 2, 0, 0, 0, 0, 0, 2, 0]
+safest	1.7	1.61555	[2, 2, 2, 2, -3, 3, 3, 2, 2, 2]
+safeties	1.5	1.0247	[2, 0, 1, 3, 2, 1, 3, 1, 0, 2]
+safety	1.8	0.6	[2, 2, 2, 2, 1, 1, 2, 3, 1, 2]
+safetyman	0.3	0.64031	[0, 0, 0, 0, 2, 0, 1, 0, 0, 0]
+salient	1.1	1.22066	[1, 3, 0, -1, 0, 1, 2, 1, 1, 3]
+sappy	-1.0	1.18322	[-2, -1, 2, -2, -2, 0, -1, -1, -2, -1]
+sarcasm	-0.9	0.7	[0, -2, -1, -1, 0, 0, -1, -1, -2, -1]
+sarcasms	-0.9	0.7	[0, -1, 0, -1, -1, -2, 0, -1, -1, -2]
+sarcastic	-1.0	0.7746	[-1, -1, -1, -1, -1, -1, -1, -2, 1, -2]
+sarcastically	-1.1	1.37477	[-1, -4, 1, -1, -1, -2, 1, -2, -1, -1]
+satisfaction	1.9	0.9434	[1, 3, 2, 4, 2, 1, 1, 1, 2, 2]
+satisfactions	2.1	0.7	[3, 3, 3, 1, 2, 2, 1, 2, 2, 2]
+satisfactorily	1.6	1.11355	[1, 2, 2, -1, 2, 1, 3, 3, 1, 2]
+satisfactoriness	1.5	0.5	[1, 2, 1, 2, 2, 1, 2, 1, 2, 1]
+satisfactory	1.5	0.67082	[2, 3, 1, 1, 1, 2, 2, 1, 1, 1]
+satisfiable	1.9	0.83066	[3, 1, 2, 1, 2, 3, 1, 2, 3, 1]
+satisfied	1.8	0.6	[2, 2, 2, 1, 1, 2, 3, 1, 2, 2]
+satisfies	1.8	0.6	[3, 1, 2, 1, 1, 2, 2, 2, 2, 2]
+satisfy	2.0	0.63246	[3, 2, 2, 2, 2, 1, 1, 2, 3, 2]
+satisfying	2.0	1.48324	[2, 3, 2, 1, 3, 3, 3, 2, -2, 3]
+satisfyingly	1.9	0.9434	[1, 2, 2, 1, 2, 1, 4, 1, 3, 2]
+savage	-2.0	1.73205	[-3, -4, -3, 1, -2, -1, -3, -4, -2, 1]
+savaged	-2.0	1.34164	[-1, 0, -4, -3, -3, -3, -2, 0, -1, -3]
+savagely	-2.2	0.74833	[-2, -1, -3, -2, -2, -1, -2, -3, -3, -3]
+savageness	-2.6	1.0198	[-3, -1, -2, -3, -2, -1, -4, -4, -3, -3]
+savagenesses	-0.9	1.86815	[-2, 3, -1, -3, -2, 2, -3, -1, -1, -1]
+savageries	-1.9	1.75784	[-3, 1, -3, -4, -3, 1, -2, -3, 0, -3]
+savagery	-2.5	1.62788	[-2, -3, -3, -3, 2, -3, -3, -4, -4, -2]
+savages	-2.4	1.0198	[-2, -2, -3, -4, -3, -3, -2, 0, -2, -3]
+save	2.2	1.16619	[1, 3, 3, 1, 2, 1, 2, 4, 1, 4]
+saved	1.8	0.6	[1, 2, 2, 2, 1, 3, 2, 2, 1, 2]
+scam	-2.7	0.64031	[-2, -3, -3, -3, -2, -2, -4, -3, -3, -2]
+scams	-2.8	0.87178	[-3, -1, -3, -4, -4, -3, -2, -2, -3, -3]
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+scandalous	-2.4	0.8	[-2, -1, -3, -2, -4, -2, -3, -3, -2, -2]
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+sickeners	-2.2	0.6	[-3, -1, -2, -3, -2, -3, -2, -2, -2, -2]
+sickening	-2.4	0.91652	[-3, -4, -1, -3, -2, -2, -1, -3, -2, -3]
+sickeningly	-2.1	0.7	[-3, -3, -1, -2, -2, -1, -3, -2, -2, -2]
+sickens	-2.0	0.63246	[-2, -1, -2, -2, -3, -2, -1, -2, -3, -2]
+sigh	0.1	1.22066	[2, -1, -1, -1, 0, 2, 1, 1, -1, -1]
+significance	1.1	1.22066	[0, 0, 0, 1, 3, 2, 3, 2, 0, 0]
+significant	0.8	0.9798	[1, 0, 1, 3, 0, 1, 0, 0, 2, 0]
+silencing	-0.5	0.67082	[-2, -1, 0, 0, 0, 0, 0, -1, 0, -1]
+sillibub	-0.1	0.3	[0, 0, 0, 0, -1, 0, 0, 0, 0, 0]
+sillier	1.0	0.7746	[1, 1, 0, 2, 0, 1, 1, 2, 2, 0]
+sillies	0.8	0.74833	[2, 1, 0, 1, 0, 1, 0, 2, 1, 0]
+silliest	0.8	0.9798	[0, 1, 1, 1, 1, 0, 3, 1, -1, 1]
+sillily	-0.1	1.04403	[1, -1, -1, -1, 2, 1, -1, 0, 0, -1]
+sillimanite	0.1	0.3	[1, 0, 0, 0, 0, 0, 0, 0, 0, 0]
+sillimanites	0.2	0.6	[0, 0, 0, 0, 2, 0, 0, 0, 0, 0]
+silliness	-0.9	1.22066	[1, -3, -1, 0, 1, -1, -2, -1, -2, -1]
+sillinesses	-1.2	1.46969	[-3, -2, -3, 0, -2, 0, 1, -2, -2, 1]
+silly	0.1	1.04403	[1, 1, 0, 0, 0, 2, -1, -2, 0, 0]
+sin	-2.6	0.8	[-2, -4, -3, -2, -2, -2, -4, -3, -2, -2]
+sincere	1.7	0.78102	[1, 2, 3, 0, 2, 2, 2, 2, 1, 2]
+sincerely	2.1	1.04403	[1, 3, 2, 4, 2, 3, 1, 1, 3, 1]
+sincereness	1.8	0.74833	[3, 1, 1, 2, 2, 3, 1, 2, 2, 1]
+sincerer	2.0	1.0	[1, 3, 3, 2, 3, 2, 1, 3, 0, 2]
+sincerest	2.0	1.34164	[0, 3, 1, 1, 4, 2, 1, 4, 1, 3]
+sincerities	1.5	0.67082	[2, 1, 1, 1, 1, 1, 3, 2, 2, 1]
+sinful	-2.6	0.8	[-4, -3, -3, -2, -1, -2, -3, -2, -3, -3]
+singleminded	1.2	0.87178	[1, 2, 0, 0, 3, 2, 1, 1, 1, 1]
+sinister	-2.9	1.13578	[-4, -4, -1, -3, -1, -4, -3, -3, -2, -4]
+sins	-2.0	1.0	[-2, -1, -2, -3, -1, -4, -3, -2, -1, -1]
+skeptic	-0.9	1.13578	[0, 0, -1, -1, -1, 0, -2, -2, 1, -3]
+skeptical	-1.3	0.9	[0, -3, -2, -2, -1, -2, 0, -1, -1, -1]
+skeptically	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -1, -2]
+skepticism	-1.0	0.89443	[0, 0, -1, -1, -1, -1, 0, -1, -3, -2]
+skepticisms	-1.2	0.9798	[1, -2, 0, -1, -2, -1, -2, -2, -1, -2]
+skeptics	-0.4	0.91652	[-2, 0, 0, -1, -1, 1, -1, 0, 1, -1]
+slam	-1.6	1.11355	[-2, -1, -3, -1, -3, -2, -1, -2, 1, -2]
+slash	-1.1	1.22066	[-2, -3, -2, 0, -2, 0, -1, -2, 0, 1]
+slashed	-0.9	0.83066	[-2, -1, -2, -1, -1, 0, 1, -1, -1, -1]
+slashes	-0.8	0.6	[0, -1, -2, -1, 0, 0, -1, -1, -1, -1]
+slashing	-1.1	1.86815	[-3, -2, -3, -3, 3, 1, 0, -1, -2, -1]
+slavery	-3.8	0.4	[-4, -3, -4, -3, -4, -4, -4, -4, -4, -4]
+sleeplessness	-1.6	1.49666	[-3, -4, -2, -1, -2, -2, -2, 2, -1, -1]
+slicker	0.4	1.28062	[-2, 1, -1, 2, 0, 0, 2, 2, 0, 0]
+slickest	0.3	1.00499	[1, 0, -1, 0, -1, 0, 0, 0, 2, 2]
+sluggish	-1.7	0.64031	[-1, -2, -1, -3, -2, -2, -1, -2, -1, -2]
+slut	-2.8	0.87178	[-4, -2, -2, -1, -3, -3, -3, -3, -4, -3]
+sluts	-2.7	1.48661	[-3, -3, -4, -4, -3, -4, -1, -3, 1, -3]
+sluttier	-2.7	1.18743	[-2, -2, -4, -3, -4, -4, -1, -1, -2, -4]
+sluttiest	-3.1	0.83066	[-3, -4, -3, -4, -3, -4, -2, -2, -4, -2]
+sluttish	-2.2	0.87178	[-2, -3, -3, -2, -2, -4, -2, -1, -1, -2]
+sluttishly	-2.1	1.13578	[-2, 0, -2, -3, -1, -2, -3, -1, -3, -4]
+sluttishness	-2.5	0.92195	[-2, -1, -3, -4, -2, -1, -3, -3, -3, -3]
+sluttishnesses	-2.0	1.09545	[0, -2, -1, -3, -3, -1, -3, -1, -3, -3]
+slutty	-2.3	0.9	[-3, -1, -3, -3, -3, -2, -1, -3, -1, -3]
+smart	1.7	0.78102	[2, 2, 1, 2, 1, 3, 2, 0, 2, 2]
+smartass	-2.1	0.83066	[-1, -1, -2, -3, -2, -1, -2, -3, -3, -3]
+smartasses	-1.7	2.05183	[-1, -2, -3, -3, -3, -1, -2, -3, 4, -3]
+smarted	0.7	1.41774	[2, 1, -2, 1, 1, 2, 2, 2, -1, -1]
+smarten	1.9	0.7	[3, 1, 2, 1, 2, 2, 2, 3, 1, 2]
+smartened	1.5	0.67082	[2, 2, 1, 3, 1, 1, 1, 1, 2, 1]
+smartening	1.7	0.9	[1, 3, 3, 1, 1, 1, 2, 1, 1, 3]
+smartens	1.5	0.5	[2, 2, 1, 1, 1, 1, 2, 2, 2, 1]
+smarter	2.0	0.7746	[2, 2, 1, 1, 2, 2, 2, 2, 4, 2]
+smartest	3.0	1.0	[4, 3, 4, 3, 2, 2, 4, 3, 1, 4]
+smartie	1.3	0.9	[1, 4, 1, 1, 1, 1, 1, 1, 1, 1]
+smarties	1.7	0.9	[1, 1, 2, 4, 2, 2, 1, 2, 1, 1]
+smarting	-0.7	1.9	[2, 3, -1, -2, 1, -2, -1, -3, -2, -2]
+smartly	1.5	0.67082	[2, 1, 1, 1, 1, 2, 1, 3, 1, 2]
+smartness	2.0	0.89443	[1, 3, 3, 1, 2, 1, 2, 3, 1, 3]
+smartnesses	1.5	0.92195	[1, 0, 1, 1, 1, 2, 1, 2, 3, 3]
+smarts	1.6	0.66332	[2, 1, 3, 1, 2, 1, 2, 1, 2, 1]
+smartweed	0.2	0.6	[0, 0, 0, 0, 0, 2, 0, 0, 0, 0]
+smartweeds	0.1	0.53852	[0, 0, -1, 0, 0, 0, 1, 0, 0, 1]
+smarty	1.1	0.53852	[0, 2, 1, 2, 1, 1, 1, 1, 1, 1]
+smear	-1.5	1.20416	[-2, -1, -1, -2, -3, 0, 0, -4, -1, -1]
+smilax	0.6	0.66332	[0, 2, 1, 0, 0, 0, 1, 1, 1, 0]
+smilaxes	0.3	0.78102	[0, 0, 0, 0, 1, 2, 1, -1, 0, 0]
+smile	1.5	0.67082	[2, 1, 1, 1, 2, 2, 3, 1, 1, 1]
+smiled	2.5	0.80623	[3, 2, 3, 2, 1, 2, 3, 4, 3, 2]
+smileless	-1.4	0.4899	[-1, -1, -1, -1, -2, -1, -2, -1, -2, -2]
+smiler	1.7	0.78102	[1, 1, 3, 1, 3, 2, 2, 2, 1, 1]
+smiles	2.1	1.04403	[2, 4, 2, 1, 3, 1, 1, 3, 1, 3]
+smiley	1.7	0.78102	[1, 2, 1, 2, 2, 0, 2, 3, 2, 2]
+smileys	1.5	0.92195	[1, 2, 1, 3, 1, 0, 1, 3, 1, 2]
+smiling	2.0	1.18322	[2, 1, 1, 1, 2, 3, 4, 1, 4, 1]
+smilingly	2.3	0.64031	[3, 2, 3, 2, 3, 1, 2, 2, 2, 3]
+smog	-1.2	0.6	[-1, -1, -2, -1, -1, -2, -2, -1, 0, -1]
+smother	-1.8	0.87178	[-2, -2, -3, -1, -2, -1, -2, -2, -3, 0]
+smothered	-0.9	1.7	[2, -4, 0, -1, -3, -2, 0, -1, 1, -1]
+smothering	-1.4	1.56205	[-2, -3, -1, -4, 0, -2, -1, 2, -1, -2]
+smothers	-1.9	1.04403	[-1, -1, -3, -1, -2, -3, 0, -2, -3, -3]
+smothery	-1.1	0.7	[-2, 0, -2, -1, -2, -1, 0, -1, -1, -1]
+smug	0.8	1.16619	[-1, 2, 0, 2, 1, -1, 2, 1, 0, 2]
+smugger	-1.0	0.89443	[1, -2, -1, -2, -1, -1, -1, 0, -2, -1]
+smuggest	-1.5	1.28452	[-1, -1, -1, 1, -1, -3, -4, -2, -1, -2]
+smuggle	-1.6	1.11355	[-2, -1, -1, -1, -2, 0, -1, -1, -3, -4]
+smuggled	-1.5	0.92195	[-1, -1, -2, -1, -1, -1, -2, -1, -1, -4]
+smuggler	-2.1	1.22066	[-1, -3, -3, -1, -1, -1, -4, -1, -2, -4]
+smugglers	-1.4	1.56205	[-2, -3, -4, 1, -2, 0, -2, 1, -1, -2]
+smuggles	-1.7	1.00499	[-1, -2, -2, -1, -1, -1, -3, -1, -1, -4]
+smuggling	-2.1	0.83066	[-3, -2, -2, -1, -2, -2, -1, -2, -4, -2]
+smugly	0.2	1.249	[-1, 2, -1, -1, 1, 1, -1, 1, 2, -1]
+smugness	-1.4	1.11355	[-1, -1, -1, -3, -3, -2, 1, -1, -2, -1]
+smugnesses	-1.7	0.78102	[-1, -1, -2, -1, -3, -1, -2, -2, -3, -1]
+sneaky	-0.9	0.7	[-1, -1, -1, -2, -1, -1, -1, 1, -1, -1]
+snob	-2.0	0.63246	[-2, -2, -2, -2, -2, -1, -3, -1, -3, -2]
+snobbery	-2.0	0.63246	[-1, -2, -2, -2, -2, -3, -2, -1, -3, -2]
+snobbier	-0.7	1.00499	[-1, 2, -1, -1, -1, -1, -1, 0, -2, -1]
+snobbiest	-0.5	1.11803	[-2, -2, 1, -1, 1, -1, 0, -1, 1, -1]
+snobbily	-1.6	1.11355	[-1, -2, -2, -2, -1, -3, -3, -1, 1, -2]
+snobbish	-0.9	1.37477	[-2, -1, 1, -1, 1, -2, -3, -2, 1, -1]
+snobbishly	-1.2	1.249	[-2, 1, -2, -1, -2, -3, -1, -2, -1, 1]
+snobbishness	-1.1	1.22066	[-1, -2, -2, -1, -3, -1, -1, -1, 2, -1]
+snobbishnesses	-1.7	0.78102	[-2, -1, -3, -2, -1, -1, -2, -1, -3, -1]
+snobbism	-1.0	1.41421	[-2, -1, 1, -1, 1, -2, -3, -2, 1, -2]
+snobbisms	-0.3	1.18743	[1, -1, -1, 0, -1, -1, 1, -2, 2, -1]
+snobby	-1.7	1.00499	[-1, -1, -1, -3, -2, -2, 0, -3, -3, -1]
+snobs	-1.4	1.0198	[-2, -1, -1, -2, -2, -3, -1, -2, 1, -1]
+snub	-1.8	0.4	[-2, -2, -1, -2, -2, -2, -2, -2, -1, -2]
+snubbed	-2.0	0.7746	[-2, -2, 0, -2, -3, -2, -2, -2, -3, -2]
+snubbing	-0.9	1.13578	[-2, -1, -1, -1, 1, -1, -3, 1, -1, -1]
+snubs	-2.1	0.9434	[-2, -1, -1, -1, -3, -2, -4, -3, -2, -2]
+sob	-1.0	1.34164	[-1, -2, -2, -2, -1, -1, 2, 1, -2, -2]
+sobbed	-1.9	1.3	[-2, -4, 1, -1, -3, -1, -3, -2, -2, -2]
+sobbing	-1.6	1.49666	[1, -2, -3, -1, -1, -3, 1, -2, -3, -3]
+sobering	-0.8	1.32665	[2, -2, 0, -2, -1, -1, -2, 1, -1, -2]
+sobs	-2.5	0.67082	[-3, -3, -2, -2, -3, -3, -3, -1, -2, -3]
+sociabilities	1.2	0.9798	[1, 3, 1, 2, 0, 1, 0, 2, 2, 0]
+sociability	1.1	0.9434	[0, 1, 1, 1, 0, 2, 1, 0, 2, 3]
+sociable	1.9	0.7	[1, 1, 2, 3, 1, 2, 2, 2, 3, 2]
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+sociably	1.6	0.91652	[3, 2, 0, 1, 3, 2, 1, 1, 2, 1]
+sok	1.3	1.1	[0, 1, 2, 1, 1, 0, 1, 4, 2, 1]
+solemn	-0.3	1.1	[-1, -2, -1, 0, -1, 2, 0, -1, 1, 0]
+solemnified	-0.5	0.67082	[0, 0, 0, 0, -1, -1, -1, 0, -2, 0]
+solemnifies	-0.5	0.67082	[0, 0, 0, 0, -1, -2, -1, 0, -1, 0]
+solemnify	0.3	1.18743	[2, 1, 2, 1, 0, 0, -2, -1, 0, 0]
+solemnifying	0.1	1.3	[2, -1, 0, -3, 0, 1, 1, 1, 0, 0]
+solemnities	0.3	0.78102	[0, 1, -1, 0, 0, 0, 2, 1, 0, 0]
+solemnity	-1.1	0.9434	[0, -2, 0, -2, -2, -1, -2, 0, 0, -2]
+solemnization	0.7	1.34536	[-1, -1, 0, 2, 2, 0, 3, 2, 0, 0]
+solemnize	0.3	0.78102	[1, -1, 0, 2, 0, 0, 1, 0, 0, 0]
+solemnized	-0.7	0.9	[0, 0, 0, -1, -1, -1, -1, 0, 0, -3]
+solemnizes	0.6	0.91652	[0, 0, 0, 0, 0, 0, 2, 2, 2, 0]
+solemnizing	-0.6	0.8	[0, 0, -1, -1, 0, 0, -2, -2, 0, 0]
+solemnly	0.8	0.9798	[0, 2, 0, 1, 1, 2, -1, 2, 1, 0]
+solid	0.6	0.8	[0, 2, 1, 2, 0, 1, 0, 0, 0, 0]
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+solution	1.3	0.64031	[1, 2, 1, 2, 1, 1, 2, 2, 0, 1]
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+solved	1.1	0.53852	[1, 2, 1, 0, 1, 1, 1, 2, 1, 1]
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+solving	1.4	0.8	[0, 3, 1, 2, 1, 1, 2, 1, 2, 1]
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+son-of-a-bitch	-2.7	0.64031	[-3, -3, -3, -1, -2, -3, -3, -3, -3, -3]
+soothe	1.5	0.92195	[3, 2, 2, 1, 2, 0, 2, 0, 2, 1]
+soothed	0.5	1.43178	[2, -3, 1, 1, 0, 1, 1, 1, 2, -1]
+soothing	1.3	0.64031	[2, 1, 2, 1, 1, 1, 2, 0, 2, 1]
+sophisticated	2.6	0.91652	[3, 4, 3, 3, 3, 1, 2, 1, 3, 3]
+sore	-1.5	0.5	[-2, -2, -2, -1, -1, -1, -2, -1, -1, -2]
+sorrow	-2.4	0.8	[-2, -2, -2, -1, -2, -3, -2, -4, -3, -3]
+sorrowed	-2.4	0.8	[-1, -2, -3, -3, -2, -3, -2, -4, -2, -2]
+sorrower	-2.3	0.78102	[-1, -2, -1, -3, -3, -2, -2, -3, -3, -3]
+sorrowful	-2.2	0.6	[-3, -3, -2, -2, -2, -2, -3, -1, -2, -2]
+sorrowfully	-2.3	0.64031	[-3, -3, -2, -1, -2, -2, -3, -2, -2, -3]
+sorrowfulness	-2.5	0.67082	[-4, -3, -2, -3, -2, -3, -2, -2, -2, -2]
+sorrowing	-1.7	1.26886	[-2, -2, 1, -1, -1, -2, -4, -3, -2, -1]
+sorrows	-1.6	0.66332	[-1, -1, -2, -1, -2, -2, -1, -2, -1, -3]
+sorry	-0.3	1.61555	[-1, 0, -1, -2, -1, -1, 4, 1, -1, -1]
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+spam	-1.5	1.0247	[-1, -1, -1, -2, 1, -2, -3, -2, -2, -2]
+spammer	-2.2	0.6	[-3, -2, -2, -1, -2, -3, -2, -2, -3, -2]
+spammers	-1.6	1.11355	[-2, -1, -2, -3, -2, -1, -2, -1, 1, -3]
+spamming	-2.1	0.83066	[-3, -3, -1, -3, -2, -1, -2, -2, -1, -3]
+spark	0.9	1.04403	[0, 2, 1, 1, 0, 1, 3, -1, 1, 1]
+sparkle	1.8	0.74833	[0, 2, 2, 2, 1, 2, 3, 2, 2, 2]
+sparkles	1.3	1.18743	[3, 2, 0, 0, 3, 0, 2, 0, 1, 2]
+sparkling	1.2	0.4	[1, 1, 1, 2, 1, 1, 1, 2, 1, 1]
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+spirited	1.3	1.00499	[1, 1, 0, 1, 1, 3, 2, 3, 0, 1]
+spiritless	-1.3	0.64031	[-2, -1, -1, -2, -2, -1, 0, -1, -2, -1]
+spite	-2.4	0.8	[-2, -2, -3, -2, -3, -2, -4, -1, -3, -2]
+spited	-2.4	0.91652	[-2, -3, -3, -4, -2, -1, -2, -1, -3, -3]
+spiteful	-1.9	1.75784	[-2, 3, -2, -3, -2, -3, -2, -2, -4, -2]
+spitefully	-2.3	0.78102	[-2, -2, -1, -3, -3, -2, -2, -2, -4, -2]
+spitefulness	-1.5	1.74642	[-3, -2, 1, -3, -3, -3, -2, 2, 0, -2]
+spitefulnesses	-2.3	0.9	[-1, -4, -2, -3, -3, -2, -2, -3, -1, -2]
+spites	-1.4	1.28062	[0, -2, -2, -3, -2, -1, 1, 0, -3, -2]
+splendent	2.7	0.78102	[3, 2, 1, 3, 2, 3, 4, 3, 3, 3]
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+splendidly	2.1	1.22066	[1, 4, 1, 3, 3, 4, 1, 2, 1, 1]
+splendidness	2.3	0.9	[2, 1, 3, 3, 4, 2, 1, 3, 2, 2]
+splendiferous	2.6	1.95959	[4, 4, 3, -3, 3, 3, 4, 2, 3, 3]
+splendiferously	1.9	1.3	[2, 4, 4, 3, 0, 1, 1, 1, 2, 1]
+splendiferousness	1.7	1.18743	[1, 2, 3, 1, 2, 3, 3, 2, -1, 1]
+splendor	3.0	0.63246	[3, 3, 3, 3, 3, 2, 4, 4, 3, 2]
+splendorous	2.2	0.87178	[4, 2, 1, 2, 2, 3, 3, 1, 2, 2]
+splendors	2.0	0.44721	[2, 2, 2, 2, 3, 2, 2, 2, 1, 2]
+splendour	2.2	0.6	[2, 2, 2, 3, 3, 1, 2, 3, 2, 2]
+splendours	2.2	1.249	[3, 0, 2, 1, 4, 3, 2, 4, 1, 2]
+splendrous	2.2	1.16619	[4, 4, 3, 2, 1, 1, 3, 1, 2, 1]
+sprightly	2.0	0.89443	[0, 2, 3, 2, 2, 1, 2, 3, 3, 2]
+squelched	-1.0	0.63246	[-1, -1, -1, -1, 0, -2, -1, 0, -1, -2]
+stab	-2.8	0.6	[-3, -2, -2, -3, -3, -3, -3, -2, -4, -3]
+stabbed	-1.9	1.22066	[-2, -1, -3, -2, -2, 1, -3, -3, -1, -3]
+stable	1.2	0.74833	[1, 2, 2, 0, 1, 2, 1, 1, 2, 0]
+stabs	-1.9	1.13578	[-3, -3, -4, 0, -1, -2, -2, -2, -1, -1]
+stall	-0.8	0.74833	[-1, 0, -1, 0, -1, 0, -2, 0, -2, -1]
+stalled	-0.8	0.87178	[-2, -1, 0, -1, -1, 0, 1, -2, -1, -1]
+stalling	-0.8	1.4	[-3, -2, -1, -1, 0, 2, 1, -2, -1, -1]
+stamina	1.2	0.9798	[1, 0, 3, 0, 1, 2, 2, 1, 2, 0]
+stammer	-0.9	0.3	[-1, 0, -1, -1, -1, -1, -1, -1, -1, -1]
+stammered	-0.9	0.7	[-2, -1, -1, -1, 1, -1, -1, -1, -1, -1]
+stammerer	-1.1	0.3	[-1, -2, -1, -1, -1, -1, -1, -1, -1, -1]
+stammerers	-0.8	0.4	[-1, -1, -1, -1, -1, 0, 0, -1, -1, -1]
+stammering	-1.0	0.63246	[-2, -1, 0, -1, -1, -2, 0, -1, -1, -1]
+stammers	-0.8	0.4	[-1, -1, -1, 0, -1, -1, -1, 0, -1, -1]
+stampede	-1.8	1.07703	[-2, -3, -2, -3, 0, 0, -2, -1, -2, -3]
+stank	-1.9	1.04403	[-2, -2, -2, -1, -2, -4, -3, 0, -1, -2]
+startle	-1.3	0.64031	[-1, -1, -1, -1, -1, -2, -1, -1, -3, -1]
+startled	-0.7	0.78102	[-2, -1, -1, 0, 1, -1, -1, 0, -1, -1]
+startlement	-0.5	1.20416	[-1, 0, 0, 1, -1, -1, 2, -2, -1, -2]
+startlements	0.2	1.32665	[2, 2, 0, 0, -1, 2, 0, -2, -1, 0]
+startler	-0.8	0.74833	[-2, -1, -1, 0, 1, -1, -1, -1, -1, -1]
+startlers	-0.5	0.80623	[0, 0, 0, 0, -1, -1, -1, 1, -1, -2]
+startles	-0.5	1.36015	[-2, 2, -1, 0, 2, -1, -1, -2, -1, -1]
+startling	0.3	1.41774	[-2, 2, -1, 0, -1, 2, -1, 1, 1, 2]
+startlingly	-0.3	0.9	[-1, -1, 0, -2, 1, 0, 1, 0, -1, 0]
+starve	-1.9	2.02237	[2, -3, -4, -1, -3, -4, -1, -2, 1, -4]
+starved	-2.6	1.11355	[-3, -4, -1, -3, -3, -4, -1, -1, -3, -3]
+starves	-2.3	0.78102	[-3, -2, -2, -3, -2, -3, -1, -1, -3, -3]
+starving	-1.8	2.03961	[-2, -2, -4, -4, -3, -3, 2, 2, -2, -2]
+steadfast	1.0	1.0	[0, 0, 2, 1, 1, 2, 3, 0, 1, 0]
+steal	-2.2	0.6	[-2, -2, -2, -3, -3, -3, -1, -2, -2, -2]
+stealable	-1.7	1.00499	[-3, -1, -2, -1, -2, -1, -1, -1, -4, -1]
+stealer	-1.7	0.78102	[-2, -2, -1, -2, -3, -1, -2, -2, -2, 0]
+stealers	-2.2	0.74833	[-2, -2, -2, -4, -2, -2, -3, -1, -2, -2]
+stealing	-2.7	0.9	[-3, -2, -2, -4, -4, -3, -1, -3, -2, -3]
+stealings	-1.9	0.9434	[-2, -2, -1, -1, -1, -3, -4, -2, -1, -2]
+steals	-2.3	0.64031	[-4, -2, -2, -3, -2, -2, -2, -2, -2, -2]
+stealth	-0.3	1.34536	[-2, 1, 1, -1, 0, -3, 0, 1, -1, 1]
+stealthier	-0.3	1.00499	[0, 0, -3, 0, 0, 1, 0, -1, 0, 0]
+stealthiest	0.4	2.10713	[-1, 2, 1, 1, 3, 4, -1, 0, -2, -3]
+stealthily	0.1	1.37477	[2, 0, 0, -1, 1, 0, -3, 2, 0, 0]
+stealthiness	0.2	0.74833	[1, 0, 0, -1, 1, 0, -1, 0, 1, 1]
+stealths	-0.3	0.78102	[-2, 0, 0, -1, 0, 1, -1, 0, 0, 0]
+stealthy	-0.1	0.7	[0, 0, 0, -1, 1, -1, -1, 0, 1, 0]
+stench	-2.3	0.64031	[-3, -2, -2, -3, -3, -1, -3, -2, -2, -2]
+stenches	-1.5	1.11803	[-2, -2, -1, -3, 0, 0, -3, -2, 0, -2]
+stenchful	-2.4	0.91652	[-3, -1, -3, -1, -2, -2, -3, -4, -2, -3]
+stenchy	-2.3	1.00499	[-4, -1, -2, -3, -1, -1, -2, -3, -3, -3]
+stereotype	-1.3	0.78102	[-1, -1, -2, 0, -2, 0, -2, -1, -2, -2]
+stereotyped	-1.2	0.4	[-1, -1, -2, -1, -2, -1, -1, -1, -1, -1]
+stifled	-1.4	0.66332	[-1, -1, -1, -1, -3, -1, -2, -2, -1, -1]
+stimulate	0.9	0.83066	[1, 0, 1, 1, 1, 2, -1, 2, 1, 1]
+stimulated	0.9	0.7	[1, 0, 0, 0, 1, 1, 2, 1, 2, 1]
+stimulates	1.0	0.89443	[1, 0, 0, 0, 1, 1, 2, 1, 3, 1]
+stimulating	1.9	0.7	[2, 3, 2, 1, 3, 2, 1, 2, 1, 2]
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+stink	-1.7	0.64031	[-2, -2, -1, -3, -2, -1, -1, -2, -1, -2]
+stinkard	-2.3	0.9	[-2, -3, -3, -2, -3, -2, -3, -3, 0, -2]
+stinkards	-1.0	1.26491	[-2, -1, 2, -2, -1, -1, 0, -3, -1, -1]
+stinkbug	-0.2	0.4	[-1, 0, 0, 0, 0, 0, 0, 0, -1, 0]
+stinkbugs	-1.0	1.26491	[0, 0, 0, -4, -1, -2, -1, 0, -2, 0]
+stinker	-1.5	0.80623	[-3, -1, -3, -1, -1, -2, -1, -1, -1, -1]
+stinkers	-1.2	1.07703	[-3, 1, -1, -2, -2, -1, -1, -2, 0, -1]
+stinkhorn	-0.2	1.16619	[-2, -2, 0, 0, -1, 0, 1, 2, 0, 0]
+stinkhorns	-0.8	0.9798	[0, -3, 0, -2, 0, 0, -1, -1, -1, 0]
+stinkier	-1.5	1.0247	[-2, -1, -2, -2, -1, 1, -2, -1, -3, -2]
+stinkiest	-2.1	1.57797	[-1, -2, -3, -4, -2, -1, 1, -4, -1, -4]
+stinking	-2.4	0.91652	[-2, -4, -2, -3, -3, -1, -2, -1, -3, -3]
+stinkingly	-1.3	1.55242	[-2, -3, -3, -2, -2, 1, -2, 2, -1, -1]
+stinko	-1.5	0.80623	[-1, -2, -2, -2, 0, -1, -2, -1, -1, -3]
+stinkpot	-2.5	0.92195	[-4, -1, -3, -4, -2, -2, -3, -2, -2, -2]
+stinkpots	-0.7	1.26886	[-1, -3, -2, -1, 0, 2, 0, -1, 0, -1]
+stinks	-1.0	1.34164	[-2, -2, -1, -2, 2, -1, -2, 1, -1, -2]
+stinkweed	-0.4	1.0198	[-2, 0, -1, 0, 2, 0, -1, -1, 0, -1]
+stinkwood	-0.1	1.13578	[0, -2, 0, 0, 0, -2, 1, 0, 2, 0]
+stinky	-1.5	0.5	[-2, -1, -1, -2, -1, -1, -2, -2, -1, -2]
+stolen	-2.2	0.9798	[-3, -2, -2, -1, -3, -2, -3, 0, -3, -3]
+stop	-1.2	0.87178	[-1, 0, -2, -2, 0, -1, -2, -2, 0, -2]
+stopped	-0.9	0.53852	[-1, -1, -1, -1, -2, -1, -1, -1, 0, 0]
+stopping	-0.6	0.66332	[-1, 0, 0, -1, 0, 0, 0, -1, -2, -1]
+stops	-0.6	0.8	[-1, -1, 0, 0, -2, 0, -2, 0, 0, 0]
+stout	0.7	1.34536	[2, 0, 3, 1, 2, 1, 0, 0, -2, 0]
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+strain	-0.2	0.9798	[0, 0, -2, 0, -1, 2, 0, -1, 0, 0]
+strained	-1.7	0.78102	[0, -2, -1, -1, -2, -2, -2, -3, -2, -2]
+strainer	-0.8	1.249	[2, -2, -1, 0, -1, 0, -2, 0, -2, -2]
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+straining	-1.3	0.78102	[0, -3, -2, -1, -1, -1, -1, -1, -2, -1]
+strains	-1.2	0.4	[-1, -1, -1, -2, -1, -2, -1, -1, -1, -1]
+strange	-0.8	0.74833	[0, -1, -1, 0, -2, 0, -1, -2, 0, -1]
+strangely	-1.2	0.87178	[0, -1, -2, -2, 0, -3, -1, -1, -1, -1]
+strangled	-2.5	1.0247	[-1, -1, -3, -3, -3, -3, -1, -4, -3, -3]
+strength	2.2	0.6	[1, 2, 2, 3, 2, 3, 3, 2, 2, 2]
+strengthen	1.3	0.64031	[1, 1, 2, 1, 2, 1, 2, 0, 2, 1]
+strengthened	1.8	0.4	[2, 2, 2, 2, 1, 2, 2, 1, 2, 2]
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+strengthening	2.2	0.74833	[3, 3, 1, 1, 2, 2, 2, 2, 3, 3]
+strengthens	2.0	0.63246	[3, 2, 1, 2, 2, 3, 2, 1, 2, 2]
+strengths	1.7	0.64031	[2, 1, 3, 1, 2, 1, 2, 1, 2, 2]
+stress	-1.8	0.6	[-1, -2, -2, -1, -2, -1, -2, -3, -2, -2]
+stressed	-1.4	0.4899	[-1, -1, -1, -2, -2, -1, -2, -2, -1, -1]
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+stressful	-2.3	0.45826	[-2, -2, -2, -2, -3, -3, -2, -3, -2, -2]
+stressfully	-2.6	0.66332	[-2, -3, -1, -3, -3, -3, -3, -2, -3, -3]
+stressing	-1.5	0.67082	[-1, -2, -1, -1, -3, -1, -2, -2, -1, -1]
+stressless	1.6	0.4899	[1, 2, 1, 2, 1, 2, 1, 2, 2, 2]
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+stressor	-1.8	0.74833	[-2, -1, -1, -2, -3, -2, -1, -2, -3, -1]
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+stricken	-2.3	0.9	[0, -2, -2, -2, -2, -3, -3, -3, -3, -3]
+strike	-0.5	1.11803	[0, 0, 0, -2, -2, 1, 1, -2, -1, 0]
+strikers	-0.6	1.0198	[0, 0, -2, -3, 0, 0, -1, 0, 0, 0]
+strikes	-1.5	0.92195	[0, -2, -2, -2, -3, -1, -2, -1, 0, -2]
+strong	2.3	0.78102	[3, 2, 3, 3, 1, 1, 3, 2, 2, 3]
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+stronger	1.6	0.66332	[2, 1, 1, 1, 2, 3, 2, 1, 2, 1]
+strongest	1.9	0.9434	[2, 3, 2, 1, 2, 2, 0, 3, 1, 3]
+stronghold	0.5	0.80623	[0, 2, 0, 0, 2, 0, 0, 0, 0, 1]
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+strongyloidosis	-0.8	1.66132	[-2, -3, 0, 0, -2, -2, 2, -2, 2, -1]
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+struck	-1.0	0.89443	[-1, -2, -1, 0, -2, -2, -1, -1, 1, -1]
+struggle	-1.3	0.45826	[-2, -1, -2, -1, -2, -1, -1, -1, -1, -1]
+struggled	-1.4	0.66332	[-2, -2, -1, -1, -1, -1, -2, -2, 0, -2]
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+strugglers	-1.4	0.4899	[-1, -2, -1, -1, -2, -1, -2, -2, -1, -1]
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+struggling	-1.8	0.6	[-2, -2, -2, -2, -1, -1, -2, -2, -3, -1]
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+stubbornness	-1.1	0.53852	[-1, -1, 0, -2, -1, -1, -1, -2, -1, -1]
+stubbornnesses	-1.5	0.80623	[-1, -2, -3, -1, -1, -3, -1, -1, -1, -1]
+stuck	-1.0	0.44721	[-1, -1, -1, -1, 0, -1, -1, -1, -1, -2]
+stunk	-1.6	1.68523	[-2, -2, -3, 2, -2, -3, -3, 1, -1, -3]
+stunned	-0.4	1.28062	[-1, -3, -1, 0, -1, -1, 0, 2, 1, 0]
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+stupidest	-2.4	0.66332	[-2, -3, -2, -3, -1, -3, -3, -2, -2, -3]
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+stupidly	-2.0	0.7746	[-1, -2, -3, -3, -1, -3, -2, -1, -2, -2]
+stupidness	-1.7	0.64031	[-3, -1, -2, -1, -2, -1, -2, -2, -1, -2]
+stupidnesses	-2.6	0.8	[-2, -2, -2, -4, -4, -3, -3, -2, -2, -2]
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+stuttered	-0.9	1.04403	[-1, -1, 2, -1, -1, -1, -2, -2, -1, -1]
+stutterer	-1.0	1.18322	[-1, -1, 2, -1, -1, -1, -3, -2, -1, -1]
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+stuttering	-1.3	0.9	[-1, -1, -1, 0, -3, -1, -1, -1, -3, -1]
+stutters	-1.0	0.63246	[-1, -1, -1, -2, 0, -2, 0, -1, -1, -1]
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+submissively	-1.0	1.18322	[-1, -1, -1, -1, 2, -1, -1, -2, -3, -1]
+submissiveness	-0.7	0.78102	[-2, 0, -1, 0, -1, 0, -2, 0, -1, 0]
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+subversive	-0.9	1.81384	[-3, 0, -4, -1, -2, -1, 2, -1, 2, -1]
+succeed	2.2	0.74833	[2, 3, 2, 2, 2, 1, 2, 4, 2, 2]
+succeeded	1.8	0.87178	[2, 2, 1, 2, 2, 0, 2, 3, 3, 1]
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+succeeding	2.2	1.16619	[2, 3, 0, 3, 4, 3, 1, 1, 2, 3]
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+success	2.7	0.64031	[4, 3, 2, 2, 3, 2, 3, 3, 2, 3]
+successes	2.6	0.66332	[2, 4, 3, 3, 2, 3, 2, 2, 3, 2]
+successful	2.8	0.6	[3, 3, 2, 3, 4, 3, 3, 3, 2, 2]
+successfully	2.2	0.6	[2, 2, 1, 2, 2, 2, 3, 3, 2, 3]
+successfulness	2.7	0.78102	[3, 3, 4, 3, 3, 2, 3, 2, 1, 3]
+succession	0.8	0.87178	[2, 0, 1, 2, 0, 2, 1, 0, 0, 0]
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+successionally	1.1	1.13578	[2, 2, 0, 0, 0, 0, 2, 3, 0, 2]
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+successor	0.9	0.83066	[0, 2, 0, 0, 1, 2, 2, 1, 1, 0]
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+sucked	-2.0	0.89443	[-2, -2, -1, -1, -1, -3, -4, -2, -2, -2]
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+suckering	-2.1	0.7	[-2, -3, -2, -1, -2, -3, -3, -2, -1, -2]
+suckers	-2.3	1.00499	[-2, -1, -2, -4, -1, -2, -3, -2, -4, -2]
+sucks	-1.5	1.28452	[-1, -2, -2, -1, -3, -4, -1, 1, -1, -1]
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+suffer	-2.5	0.67082	[-3, -3, -2, -2, -3, -3, -3, -2, -1, -3]
+suffered	-2.2	0.74833	[-3, -2, -1, -3, -2, -3, -1, -3, -2, -2]
+sufferer	-2.0	0.63246	[-3, -2, -2, -2, -2, -3, -1, -2, -2, -1]
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+suffering	-2.1	0.83066	[-2, -1, -3, -2, -1, -2, -3, -3, -1, -3]
+suffers	-2.1	0.7	[-3, -2, -1, -2, -2, -2, -3, -1, -3, -2]
+suicidal	-3.5	0.67082	[-4, -4, -4, -4, -3, -4, -3, -3, -2, -4]
+suicide	-3.5	0.67082	[-4, -3, -4, -4, -4, -2, -3, -4, -4, -3]
+suing	-1.1	1.13578	[1, -1, -1, 0, -1, -3, -1, -1, -3, -1]
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+sulky	-0.8	1.77764	[-3, 3, -2, -3, 0, -2, 0, -1, 1, -1]
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+super	2.9	0.7	[4, 2, 4, 3, 3, 3, 2, 3, 2, 3]
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+superior	2.5	1.11803	[2, 3, 1, 3, 3, 0, 3, 3, 4, 3]
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+supporting	1.9	0.9434	[3, 2, 1, 1, 3, 3, 1, 1, 3, 1]
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+supremacist	0.5	2.15639	[3, 2, -3, 1, 2, 2, 2, -2, 1, -3]
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+supreme	2.6	1.11355	[2, 3, 2, 1, 4, 2, 1, 3, 4, 4]
+supremely	2.7	1.00499	[2, 4, 1, 4, 2, 4, 2, 3, 2, 3]
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+supremest	2.2	1.98997	[4, 3, 1, 0, 4, 4, -2, 3, 1, 4]
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+supremos	1.3	0.78102	[0, 2, 2, 1, 0, 2, 2, 1, 2, 1]
+sure	1.3	0.64031	[1, 1, 3, 1, 1, 2, 1, 1, 1, 1]
+surefire	1.0	0.7746	[1, 1, 0, 2, 2, 1, 0, 1, 2, 0]
+surefooted	1.9	0.83066	[0, 3, 2, 2, 2, 2, 1, 2, 3, 2]
+surefootedly	1.6	0.91652	[1, 1, 2, 0, 2, 1, 3, 3, 1, 2]
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+surely	1.9	0.7	[2, 2, 2, 1, 1, 1, 3, 2, 3, 2]
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+surety	1.0	0.44721	[1, 1, 1, 1, 1, 0, 1, 1, 2, 1]
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+surprised	0.9	0.9434	[2, 0, 0, 0, 0, 2, 2, 1, 2, 0]
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+survived	2.3	0.78102	[3, 4, 2, 2, 2, 1, 2, 3, 2, 2]
+surviving	1.2	0.87178	[1, 3, 1, 0, 2, 0, 1, 1, 1, 2]
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+suspected	-0.9	1.13578	[-1, 0, -1, -2, -1, -1, -2, 2, -2, -1]
+suspecting	-0.7	1.34536	[-1, 2, -1, -1, -1, 1, -2, -1, -3, 0]
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+suspend	-1.3	0.64031	[0, -2, -1, -2, -1, -1, -2, -1, -2, -1]
+suspended	-2.1	0.83066	[-2, -1, -2, -3, -3, -1, -3, -1, -2, -3]
+suspicion	-1.6	0.91652	[-2, -2, -1, -2, 1, -2, -2, -2, -2, -2]
+suspicions	-1.5	0.67082	[-1, -2, -1, -2, -1, -1, -3, -1, -2, -1]
+suspicious	-1.5	0.67082	[-1, -2, -1, -1, -2, -1, -2, -1, -3, -1]
+suspiciously	-1.7	0.45826	[-2, -2, -1, -2, -1, -2, -2, -1, -2, -2]
+suspiciousness	-1.2	1.46969	[-2, -3, -2, -1, -1, 1, 2, -2, -2, -2]
+sux	-1.5	0.92195	[-1, -1, -2, -1, -2, -1, -3, 0, -3, -1]
+swear	-0.2	1.53623	[-2, 2, -1, 1, 1, 0, -1, -2, 2, -2]
+swearing	-1.0	1.09545	[0, -2, -1, -1, -2, 0, 1, -3, -1, -1]
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+sweet	2.0	0.63246	[1, 2, 2, 2, 3, 3, 2, 1, 2, 2]
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+sweetie	2.2	0.6	[2, 3, 3, 2, 1, 3, 2, 2, 2, 2]
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+tensely	-1.2	0.6	[-1, -2, -2, -2, -1, 0, -1, -1, -1, -1]
+tenseness	-1.5	0.67082	[-1, -1, -1, -1, -1, -2, -2, -1, -2, -3]
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+tensioned	-0.4	1.11355	[-2, 0, -1, 2, -1, 0, -1, -1, -1, 1]
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+tensioners	-0.9	1.04403	[-1, 0, -2, -2, -1, 1, -2, 0, 0, -2]
+tensioning	-1.4	1.0198	[-1, -1, -1, -1, 0, -2, -3, -3, 0, -2]
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+terrify	-2.3	0.78102	[-3, -3, -2, -2, -1, -4, -2, -2, -2, -2]
+terrifying	-2.7	0.78102	[-4, -3, -3, -2, -2, -2, -4, -2, -3, -2]
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+unlovelier	-1.9	0.7	[-2, -2, -1, -3, -1, -2, -1, -3, -2, -2]
+unloveliest	-1.9	0.83066	[-2, -4, -2, -2, -1, -1, -1, -2, -2, -2]
+unloveliness	-2.0	0.89443	[-2, -3, -1, -1, -3, -1, -3, -2, -3, -1]
+unlovely	-2.1	0.53852	[-2, -3, -2, -3, -1, -2, -2, -2, -2, -2]
+unloving	-2.3	0.45826	[-2, -3, -2, -3, -2, -2, -2, -3, -2, -2]
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+unprofessional	-2.3	0.78102	[-2, -1, -3, -3, -2, -1, -3, -2, -3, -3]
+unprotected	-1.5	0.67082	[-2, -2, -1, -1, -3, -1, -1, -2, -1, -1]
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+unsatisfied	-1.7	0.64031	[-2, -1, -2, -1, -1, -2, -3, -1, -2, -2]
+unsavory	-1.9	0.53852	[-2, -1, -2, -2, -2, -3, -1, -2, -2, -2]
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+unsophisticated	-1.2	0.87178	[-1, -1, -1, -2, -2, -2, -1, -2, 1, -1]
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+unsuccessfully	-1.7	0.78102	[-2, -2, -1, -1, -1, -2, -3, -3, -1, -1]
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+unsurely	-1.3	0.78102	[-1, 0, -1, -1, -1, -3, -1, -2, -2, -1]
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+upset	-1.6	0.4899	[-1, -1, -2, -2, -1, -1, -2, -2, -2, -2]
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+upsetter	-1.9	0.7	[-2, -2, -1, -1, -3, -2, -3, -1, -2, -2]
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+upsetting	-2.1	0.53852	[-2, -3, -2, -3, -2, -1, -2, -2, -2, -2]
+uptight	-1.6	0.4899	[-2, -1, -2, -1, -1, -2, -2, -1, -2, -2]
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+urgent	0.8	1.16619	[3, -1, 0, 1, 1, 0, 0, 0, 2, 2]
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+uselessly	-1.5	0.67082	[-2, -3, -1, -1, -1, -1, -2, -2, -1, -1]
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+validate	1.5	0.92195	[1, 2, 1, 1, 1, 3, 1, 3, 0, 2]
+validated	0.9	0.83066	[2, 1, 0, 1, 1, 0, 2, 0, 0, 2]
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+validating	1.4	0.8	[2, 2, 1, 3, 0, 2, 1, 1, 1, 1]
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+victimised	-1.5	1.56525	[-2, -2, -2, 1, -3, 2, -2, -3, -2, -2]
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+victimising	-2.5	0.67082	[-3, -1, -3, -2, -2, -3, -3, -2, -3, -3]
+victimization	-2.3	0.78102	[-1, -3, -3, -2, -3, -1, -3, -2, -3, -2]
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+victimize	-2.5	0.67082	[-3, -2, -4, -2, -2, -2, -2, -3, -3, -2]
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+victimizer	-1.8	1.72047	[-3, -2, -3, -3, -2, 2, 1, -2, -3, -3]
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+victimizing	-2.6	0.4899	[-2, -3, -3, -3, -2, -3, -2, -3, -2, -3]
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+villainously	-2.9	0.53852	[-3, -3, -3, -3, -3, -4, -2, -3, -2, -3]
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+vindicating	-1.1	1.97231	[-3, -2, 2, -3, -2, 1, 1, 1, -3, -3]
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+vulnerability	-0.9	1.75784	[1, -1, -1, -2, 1, -3, -1, 2, -4, -1]
+vulnerable	-0.9	1.37477	[-2, -2, 2, -1, -3, -1, 1, -1, -1, -1]
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+vulnerably	-1.2	1.46969	[-2, -2, 2, -1, -2, -3, 1, -1, -2, -2]
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+vultures	-1.3	1.55242	[-2, -3, -2, 2, -2, -2, -3, -1, -1, 1]
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+warmly	1.7	0.64031	[2, 1, 2, 1, 2, 1, 2, 1, 2, 3]
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+warmongering	-2.5	0.67082	[-2, -3, -3, -1, -2, -3, -3, -2, -3, -3]
+warmongers	-2.8	0.87178	[-2, -3, -4, -4, -3, -1, -2, -3, -3, -3]
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+warmouths	-0.8	1.32665	[-1, -1, -2, -1, -2, -2, 0, 2, 1, -2]
+warms	1.1	0.7	[2, 2, 1, 2, 1, 0, 1, 1, 0, 1]
+warmth	2.0	0.44721	[2, 2, 2, 2, 1, 2, 2, 3, 2, 2]
+warmup	0.4	0.66332	[0, 2, 0, 1, 1, 0, 0, 0, 0, 0]
+warmups	0.8	0.9798	[0, 2, 0, 0, 0, 2, 2, 0, 2, 0]
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+warned	-1.1	0.53852	[-1, -1, -2, 0, -1, -1, -1, -2, -1, -1]
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+warnings	-1.2	0.9798	[-2, -1, 0, -1, -2, 0, 0, -1, -3, -2]
+warns	-0.4	1.0198	[1, -1, -1, 1, -1, -1, -2, 1, 0, -1]
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+warring	-1.9	1.04403	[-3, -3, 0, -1, -2, -2, -3, -1, -1, -3]
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+warship	-0.7	0.9	[0, 0, 0, 0, 0, -2, -1, 0, -2, -2]
+warships	-0.5	0.80623	[0, -1, 0, 0, -2, 0, 0, -2, 0, 0]
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+weakened	-1.3	0.9	[-2, -1, -1, -1, -1, -2, -2, -2, 1, -2]
+weakener	-1.6	1.11355	[-2, -1, -1, -1, -2, -2, -3, -3, 1, -2]
+weakeners	-1.3	0.45826	[-1, -2, -1, -2, -1, -1, -2, -1, -1, -1]
+weakening	-1.3	0.45826	[-2, -1, -1, -1, -1, -1, -1, -2, -2, -1]
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+weaker	-1.9	0.83066	[-2, -2, -2, -2, -2, -1, -4, -1, -1, -2]
+weakest	-2.3	0.64031	[-2, -4, -2, -3, -2, -2, -2, -2, -2, -2]
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+weakfishes	-0.6	0.8	[0, -1, 0, -2, 0, 0, -1, 0, -2, 0]
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+weakish	-1.2	0.4	[-1, -2, -1, -1, -1, -1, -2, -1, -1, -1]
+weaklier	-1.5	0.67082	[-1, -2, -1, -3, -2, -1, -1, -2, -1, -1]
+weakliest	-2.1	0.83066	[-2, -2, -2, -2, -3, -1, -2, -1, -4, -2]
+weakling	-1.3	1.00499	[-1, -2, -1, -3, -2, -2, -1, -1, 1, -1]
+weaklings	-1.4	0.66332	[-2, -1, -1, -1, -1, -2, -2, 0, -2, -2]
+weakly	-1.8	0.87178	[-2, -2, -2, -2, -4, -1, -1, -1, -1, -2]
+weakness	-1.8	0.6	[-2, -2, -2, -1, -1, -2, -1, -3, -2, -2]
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+weakside	-1.1	1.37477	[-3, -2, -3, -1, -2, -1, 1, 1, -1, 0]
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+wealthier	2.2	0.6	[3, 2, 1, 3, 2, 2, 2, 3, 2, 2]
+wealthiest	2.2	0.9798	[2, 4, 4, 1, 2, 1, 2, 2, 2, 2]
+wealthily	2.0	0.89443	[2, 3, 1, 4, 2, 1, 1, 2, 2, 2]
+wealthiness	2.4	1.11355	[2, 4, 2, 4, 1, 2, 4, 1, 2, 2]
+wealthy	1.5	1.0247	[1, 2, 1, 4, 1, 0, 2, 1, 2, 1]
+weapon	-1.2	0.87178	[0, -2, -2, -1, 0, -2, -1, -2, 0, -2]
+weaponed	-1.4	0.91652	[-2, -2, -3, -1, -1, 0, 0, -2, -1, -2]
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+weaponry	-0.9	0.7	[-2, -2, 0, -1, 0, -1, -1, -1, 0, -1]
+weapons	-1.9	0.9434	[-2, -1, -2, -2, -1, -3, -3, -3, -2, 0]
+weary	-1.1	1.13578	[-2, -1, -2, -3, 0, -1, -1, -2, 0, 1]
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+weepier	-1.8	0.87178	[-3, -3, -2, -1, -2, -2, -2, 0, -1, -2]
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+weepiest	-2.4	0.91652	[-4, -2, -2, -2, -2, -1, -2, -2, -4, -3]
+weeping	-1.9	0.9434	[-2, -2, -1, -1, -1, -1, -4, -2, -2, -3]
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+weeps	-1.4	1.35647	[-2, -3, -1, -2, -1, -3, 1, -2, 1, -2]
+weepy	-1.3	1.55242	[-2, -3, -1, -2, 2, -3, -1, -2, 1, -2]
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+weirder	-0.5	0.80623	[1, -1, -1, -1, -1, 1, -1, -1, 0, -1]
+weirdest	-0.9	1.22066	[-2, 0, -2, -1, -1, -1, -3, 1, 1, -1]
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+weirdly	-1.2	0.74833	[0, -1, -1, -2, -3, -1, -1, -1, -1, -1]
+weirdness	-0.9	1.64012	[-3, -2, -1, -1, 2, -1, 1, -3, 1, -2]
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+weirdo	-1.8	0.6	[-2, -2, -2, -2, -2, -2, -1, -1, -3, -1]
+weirdoes	-1.3	0.64031	[-2, -1, -2, -1, -1, -2, -1, 0, -1, -2]
+weirdos	-1.1	0.9434	[-1, -1, -1, -2, 1, -3, -1, -1, -1, -1]
+weirds	-0.6	0.4899	[-1, -1, -1, 0, -1, 0, 0, -1, 0, -1]
+weirdy	-0.9	0.83066	[-1, -1, 0, 0, -1, 0, -2, -2, 0, -2]
+welcome	2.0	0.63246	[1, 3, 2, 1, 2, 2, 2, 2, 3, 2]
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+welcomeness	2.0	0.89443	[2, 3, 1, 2, 3, 0, 2, 3, 2, 2]
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+welcomes	1.7	0.78102	[1, 1, 2, 2, 3, 3, 1, 2, 1, 1]
+welcoming	1.9	0.7	[2, 2, 1, 1, 2, 2, 2, 3, 3, 1]
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+welled	0.4	0.8	[0, 0, 2, 0, 0, 0, 0, 0, 2, 0]
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+wellspring	1.5	0.92195	[3, 1, 1, 1, 0, 2, 2, 3, 1, 1]
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+wept	-2.0	1.09545	[-3, -2, -3, -3, -1, -3, 0, -1, -1, -3]
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+whine	-1.5	1.11803	[-1, -4, -1, -1, -1, -3, 0, -2, -1, -1]
+whined	-0.9	1.04403	[-2, -1, -2, -1, -1, -1, -2, 1, 1, -1]
+whiner	-1.2	0.4	[-1, -2, -1, -1, -1, -2, -1, -1, -1, -1]
+whiners	-0.6	1.95959	[-2, 0, -2, -2, 4, 1, 1, -2, -2, -2]
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+whiney	-1.3	0.45826	[-1, -2, -1, -1, -1, -2, -2, -1, -1, -1]
+whining	-0.9	1.51327	[-3, 0, -1, -1, -3, -1, 1, 2, -2, -1]
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+whored	-2.8	0.87178	[-2, -3, -4, -2, -2, -3, -4, -4, -2, -2]
+whoredom	-2.1	2.02237	[-4, -2, -4, -3, -3, -3, -4, -1, 2, 1]
+whoredoms	-2.4	1.11355	[-1, -3, 0, -3, -2, -3, -3, -4, -2, -3]
+whorehouse	-1.1	2.11896	[-2, -2, -2, 3, 3, -3, -3, -2, -1, -2]
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+whoremaster	-1.9	1.22066	[-1, -3, -3, -2, -1, -3, 0, 0, -3, -3]
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+wickeder	-2.2	1.32665	[-2, -3, -1, -4, 1, -3, -3, -3, -2, -2]
+wickedest	-2.9	1.04403	[-3, -1, -3, -3, -3, -3, -1, -4, -4, -4]
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+wimpish	-1.6	0.4899	[-2, -1, -2, -1, -2, -2, -1, -2, -2, -1]
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+wimple	-0.2	0.74833	[0, -1, 0, 0, 0, 0, -2, 0, 0, 1]
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+wimpy	-0.9	1.04403	[-2, -1, -1, -1, -1, -2, -1, 1, -2, 1]
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+winning	2.4	0.4899	[2, 3, 3, 2, 2, 2, 3, 3, 2, 2]
+winningly	2.3	1.48661	[1, 3, 4, 3, 3, 1, 2, 3, -1, 4]
+winnings	2.5	0.92195	[3, 4, 3, 2, 2, 3, 1, 1, 3, 3]
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+winnowing	-0.1	0.53852	[0, 0, -1, 0, 0, 0, 0, 1, -1, 0]
+winnows	-0.2	0.4	[0, 0, -1, -1, 0, 0, 0, 0, 0, 0]
+wins	2.7	0.78102	[2, 2, 3, 3, 4, 4, 3, 2, 2, 2]
+wisdom	2.4	0.66332	[2, 3, 4, 2, 3, 2, 2, 2, 2, 2]
+wise	2.1	0.83066	[2, 3, 1, 4, 2, 2, 1, 2, 2, 2]
+wiseacre	-1.2	1.16619	[-2, -1, -2, -2, -2, -1, -2, 1, 1, -2]
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+wiseass	-1.8	0.6	[-2, -2, -1, -1, -2, -2, -3, -2, -1, -2]
+wiseasses	-1.5	1.36015	[-1, -2, 2, -2, -1, -3, -2, -3, -1, -2]
+wisecrack	-0.1	1.22066	[-1, -1, -1, -2, 2, 1, -1, 1, 1, 0]
+wisecracked	-0.5	0.92195	[1, 1, -1, -1, 0, -1, -2, 0, -1, -1]
+wisecracker	-0.1	0.7	[-1, 1, -1, -1, 0, 0, 0, 0, 1, 0]
+wisecrackers	0.1	1.04403	[-1, 0, 1, 1, 0, 2, 1, -1, -1, -1]
+wisecracking	-0.6	0.4899	[0, 0, -1, 0, -1, 0, -1, -1, -1, -1]
+wisecracks	-0.3	1.55242	[1, 2, -1, 2, -3, 0, 0, -2, -1, -1]
+wised	1.5	0.67082	[2, 2, 2, 1, 1, 2, 0, 1, 2, 2]
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+wiselier	0.9	1.3	[1, 2, 2, -2, 0, 1, 3, 1, 0, 1]
+wiseliest	1.6	1.49666	[1, 4, 2, 2, 1, 2, 2, 3, -2, 1]
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+wiseness	1.9	0.7	[2, 3, 2, 2, 3, 1, 1, 1, 2, 2]
+wisenheimer	-1.0	1.18322	[-1, 1, -1, -1, -1, 0, -1, -3, 0, -3]
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+wiser	1.2	0.87178	[1, 3, 0, 1, 1, 2, 0, 2, 1, 1]
+wises	1.3	1.48661	[3, 3, 2, -2, 2, 0, 0, 2, 2, 1]
+wisest	2.1	1.51327	[1, 3, 3, 3, 3, 2, 2, 3, -2, 3]
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+wish	1.7	1.1	[2, 1, 1, 0, 2, 1, 3, 2, 4, 1]
+wishes	0.6	0.8	[0, 0, 1, 0, 1, 0, 2, 0, 2, 0]
+wishing	0.9	0.7	[2, 1, 1, 0, 0, 0, 1, 1, 2, 1]
+witch	-1.5	0.80623	[-1, -2, -2, -1, -3, 0, -2, -2, -1, -1]
+withdrawal	0.1	1.57797	[1, -1, 0, -2, -2, 2, -1, 1, 0, 3]
+woe	-1.8	0.6	[-3, -2, -2, -2, -1, -1, -2, -1, -2, -2]
+woebegone	-2.6	0.66332	[-3, -2, -3, -2, -2, -4, -3, -2, -2, -3]
+woebegoneness	-1.1	1.37477	[-3, 0, -1, 1, -1, -4, 0, -1, -1, -1]
+woeful	-1.9	0.83066	[-1, -2, -2, -1, -3, -3, -1, -2, -1, -3]
+woefully	-1.7	1.48661	[-1, -3, -2, 1, -3, -3, -2, -2, 1, -3]
+woefulness	-2.1	0.7	[-3, -2, -2, -1, -2, -3, -3, -1, -2, -2]
+woes	-1.9	0.83066	[-2, -2, -2, -1, -2, -3, -3, 0, -2, -2]
+woesome	-1.2	1.6	[-2, -3, -2, -1, 0, 3, -2, -2, -1, -2]
+won	2.7	0.9	[3, 4, 2, 2, 2, 4, 4, 2, 2, 2]
+wonderful	2.7	0.78102	[2, 3, 3, 2, 4, 2, 2, 3, 4, 2]
+wonderfully	2.9	0.83066	[1, 3, 3, 4, 3, 2, 3, 3, 4, 3]
+wonderfulness	2.9	0.53852	[3, 2, 3, 3, 3, 3, 3, 2, 4, 3]
+woo	2.1	1.37477	[4, 2, 1, 3, 2, 2, -1, 2, 2, 4]
+woohoo	2.3	1.1	[3, 3, 1, 4, 4, 2, 1, 1, 2, 2]
+woot	1.8	1.07703	[2, 0, 2, 2, 2, 2, 0, 4, 2, 2]
+worn	-1.2	0.4	[-1, -1, -1, -1, -1, -1, -2, -1, -2, -1]
+worried	-1.2	0.74833	[-1, -1, -1, -1, -1, -2, -3, 0, -1, -1]
+worriedly	-2.0	0.44721	[-2, -2, -3, -2, -2, -2, -2, -1, -2, -2]
+worrier	-1.8	0.6	[-2, -2, -1, -2, -1, -3, -2, -2, -1, -2]
+worriers	-1.7	0.45826	[-2, -1, -2, -2, -2, -2, -1, -2, -1, -2]
+worries	-1.8	0.6	[-2, -2, -1, -2, -1, -2, -2, -3, -1, -2]
+worriment	-1.5	0.67082	[-1, -2, -1, -1, -1, -2, -1, -3, -1, -2]
+worriments	-1.9	0.7	[-2, -1, -2, -3, -1, -2, -3, -1, -2, -2]
+worrisome	-1.7	0.64031	[-1, -1, -1, -2, -1, -2, -3, -2, -2, -2]
+worrisomely	-2.0	0.63246	[-1, -2, -1, -2, -2, -3, -2, -2, -3, -2]
+worrisomeness	-1.9	0.53852	[-2, -2, -3, -1, -2, -2, -2, -1, -2, -2]
+worrit	-2.1	0.53852	[-2, -2, -1, -2, -2, -3, -3, -2, -2, -2]
+worrits	-1.2	0.9798	[-1, -2, -2, -1, 0, 0, -1, -3, 0, -2]
+worry	-1.9	0.7	[-2, -3, -1, -3, -1, -2, -1, -2, -2, -2]
+worrying	-1.4	0.66332	[-2, -1, -2, -2, -1, 0, -1, -1, -2, -2]
+worrywart	-1.8	0.9798	[-2, -2, -2, -1, -1, -1, -1, -3, -1, -4]
+worrywarts	-1.5	0.5	[-2, -1, -2, -2, -2, -1, -1, -1, -2, -1]
+worse	-2.1	0.83066	[-2, -2, -1, -3, -4, -2, -1, -2, -2, -2]
+worsen	-2.3	0.78102	[-4, -3, -1, -2, -2, -2, -2, -3, -2, -2]
+worsened	-1.9	1.22066	[-2, -2, -2, -1, -2, -2, -4, 1, -3, -2]
+worsening	-2.0	0.44721	[-2, -3, -2, -2, -2, -2, -1, -2, -2, -2]
+worsens	-2.1	0.53852	[-2, -2, -2, -2, -1, -2, -2, -3, -3, -2]
+worser	-2.0	0.89443	[-2, -2, -4, -1, -2, -2, -2, -3, -1, -1]
+worship	1.2	1.07703	[1, 0, 0, 1, 3, 0, 2, 3, 1, 1]
+worshiped	2.4	1.0198	[1, 2, 4, 3, 4, 1, 2, 3, 2, 2]
+worshiper	1.0	1.0	[0, 0, 2, 3, 0, 2, 1, 1, 1, 0]
+worshipers	0.9	0.83066	[0, 0, 0, 2, 1, 1, 1, 2, 2, 0]
+worshipful	0.7	1.00499	[1, -1, 3, 1, 1, 1, 0, 0, 0, 1]
+worshipfully	1.1	1.3	[0, 0, 0, 1, 3, 0, 3, 3, 1, 0]
+worshipfulness	1.6	0.8	[3, 1, 2, 2, 1, 1, 3, 1, 1, 1]
+worshiping	1.0	1.18322	[0, 3, 0, 3, 0, 1, 1, 2, 0, 0]
+worshipless	-0.6	1.0198	[0, -1, -3, -1, -1, -1, 0, 0, 0, 1]
+worshipped	2.7	0.78102	[3, 2, 3, 3, 1, 4, 2, 3, 3, 3]
+worshipper	0.6	0.66332	[1, 1, 0, 0, 1, 0, 0, 2, 1, 0]
+worshippers	0.8	0.87178	[0, 1, 0, 0, 3, 1, 1, 1, 0, 1]
+worshipping	1.6	1.28062	[1, 3, 3, 3, 0, 3, 1, 0, 2, 0]
+worships	1.4	1.11355	[2, 0, 1, 3, 2, 1, 0, 3, 2, 0]
+worst	-3.1	1.04403	[-4, -4, -3, -1, -3, -4, -2, -2, -4, -4]
+worth	0.9	0.9434	[0, 0, 1, 1, 2, 1, 1, 3, 0, 0]
+worthless	-1.9	1.13578	[-3, -1, -3, -4, -1, -3, -1, -1, -1, -1]
+worthwhile	1.4	0.4899	[1, 1, 1, 2, 1, 1, 2, 1, 2, 2]
+worthy	1.9	0.53852	[2, 2, 2, 1, 1, 2, 2, 2, 3, 2]
+wow	2.8	0.9798	[2, 3, 2, 4, 4, 3, 3, 2, 1, 4]
+wowed	2.6	0.8	[3, 3, 4, 3, 2, 1, 3, 3, 2, 2]
+wowing	2.5	0.67082	[2, 2, 3, 3, 2, 3, 4, 2, 2, 2]
+wows	2.0	1.61245	[2, 3, 3, 3, 2, 1, -2, 1, 4, 3]
+wowser	-1.1	2.02237	[-3, 3, 0, 2, -2, -1, -3, -2, -2, -3]
+wowsers	1.0	2.14476	[0, -2, 4, 2, 3, 0, 1, 2, -3, 3]
+wrathful	-2.7	0.64031	[-3, -2, -2, -3, -3, -2, -4, -2, -3, -3]
+wreck	-1.9	0.7	[-1, -2, -3, -3, -2, -2, -2, -1, -1, -2]
+wrong	-2.1	1.04403	[-2, -2, -2, -2, -4, -4, -1, -1, -1, -2]
+wronged	-1.9	0.53852	[-2, -2, -2, -2, -2, -1, -3, -2, -2, -1]
+x-d	2.6	0.91652	[2, 3, 3, 4, 1, 2, 3, 4, 2, 2]
+x-p	1.7	0.45826	[2, 2, 1, 2, 2, 1, 1, 2, 2, 2]
+xd	2.8	0.87178	[3, 3, 4, 2, 3, 3, 1, 2, 4, 3]
+xp	1.6	0.4899	[2, 2, 2, 1, 1, 1, 2, 2, 1, 2]
+yay	2.4	1.0198	[1, 3, 3, 2, 2, 1, 4, 4, 2, 2]
+yeah	1.2	0.6	[1, 1, 1, 2, 1, 1, 0, 2, 1, 2]
+yearning	0.5	1.0247	[0, 1, 0, 1, 0, 3, 0, 1, -1, 0]
+yeees	1.7	1.00499	[1, 3, 1, 2, 1, 1, 4, 2, 1, 1]
+yep	1.2	0.4	[1, 1, 1, 1, 1, 1, 2, 2, 1, 1]
+yes	1.7	0.78102	[1, 2, 2, 1, 1, 1, 3, 3, 1, 2]
+youthful	1.3	0.45826	[1, 2, 1, 2, 1, 1, 1, 1, 2, 1]
+yucky	-1.8	0.6	[-2, -1, -1, -2, -2, -1, -2, -2, -3, -2]
+yummy	2.4	1.0198	[1, 2, 4, 3, 2, 2, 3, 1, 4, 2]
+zealot	-1.9	1.04403	[-2, -3, -1, -2, -1, -3, -4, -1, -1, -1]
+zealots	-0.8	1.83303	[-1, -2, -1, -2, -2, 1, -2, 4, -1, -2]
+zealous	0.5	1.43178	[2, -1, 2, 1, 0, 0, 3, 0, -2, 0]
+{:	1.8	0.9798	[1, 3, 2, 2, 1, 1, 4, 2, 1, 1]
+|-0	-1.2	0.74833	[0, -2, -1, -1, -1, -1, -1, -1, -1, -3]
+|-:	-0.8	0.74833	[-1, -2, 0, -1, 0, -2, -1, -1, 0, 0]
+|-:>	-1.6	0.4899	[-1, -2, -2, -2, -2, -1, -1, -2, -2, -1]
+|-o	-1.2	0.9798	[-1, 0, -1, -1, -1, -1, -1, -4, -1, -1]
+|:	-0.5	1.68819	[2, -3, -1, 0, -1, -1, -1, -2, -1, 3]
+|;-)	2.2	1.32665	[4, 1, 1, 1, 3, 2, 4, 1, 4, 1]
+|=	-0.4	1.56205	[2, -2, -1, 0, -1, -1, -1, -2, -1, 3]
+|^:	-1.1	0.7	[-2, 0, -1, -1, 0, -1, -1, -2, -2, -1]
+|o:	-0.9	0.53852	[-1, 0, -1, -2, -1, 0, -1, -1, -1, -1]
+||-:	-2.3	0.45826	[-2, -2, -2, -3, -3, -3, -2, -2, -2, -2]
+}:	-2.1	0.83066	[-1, -1, -3, -2, -3, -2, -2, -1, -3, -3]
+}:(	-2.0	0.63246	[-3, -1, -2, -1, -3, -2, -2, -2, -2, -2]
+}:)	0.4	1.42829	[1, 1, -2, 1, 2, -2, 1, -1, 2, 1]
+}:-(	-2.1	0.7	[-2, -1, -2, -2, -2, -4, -2, -2, -2, -2]
+}:-)	0.3	1.61555	[1, 1, -2, 1, -1, -3, 2, 2, 1, 1]
+bulls	1.9	1.86
+bull	1.8	1.682
+bullish	2.3	1.5798
+whales	-1.1	1.9138
+support	1	1.9322
+resistance	0.3	2.1756
+bear	-1.3	1.8797
+bearish	-1.4	1.2042
+short	-0.8	1.5213
+long	1.3	1.6375
+bounce	1.1	1.6854
+rekt	-2.2	2.4404
+arbitrage	0.4	1.9633
+manipulation	-2.7	1.2721
+bot	-0.9	2.1833
+strategy	1.5	1.9679
+SEC	0	1.4142
+regulations	-1.2	1.6865
+FUD	-1.9	1.912
+ICO	-0.4	2.1705
+CNBC	-2.1	2.0276
+hodl	0	2.357
\ No newline at end of file