From 07839de87b7607e458f86b36034d66413506d34c Mon Sep 17 00:00:00 2001
From: Joe Davison <josephddavison@gmail.com>
Date: Sat, 19 Sep 2020 23:04:43 -0400
Subject: [PATCH] Add Polyglot-NER Dataset (#641)
* add polyglot-ner
* style
* update field names
* update dataset infos
* style
* style again...
* fix dummy data
---
datasets/polyglot_ner/dataset_infos.json | 1 +
.../dummy/ar/1.0.0/dummy_data.zip | Bin 0 -> 1809 bytes
.../dummy/bg/1.0.0/dummy_data.zip | Bin 0 -> 1857 bytes
.../dummy/ca/1.0.0/dummy_data.zip | Bin 0 -> 1605 bytes
.../dummy/combined/1.0.0/dummy_data.zip | Bin 0 -> 56567 bytes
.../dummy/cs/1.0.0/dummy_data.zip | Bin 0 -> 1742 bytes
.../dummy/da/1.0.0/dummy_data.zip | Bin 0 -> 1674 bytes
.../dummy/de/1.0.0/dummy_data.zip | Bin 0 -> 1712 bytes
.../dummy/el/1.0.0/dummy_data.zip | Bin 0 -> 1931 bytes
.../dummy/en/1.0.0/dummy_data.zip | Bin 0 -> 1657 bytes
.../dummy/es/1.0.0/dummy_data.zip | Bin 0 -> 1582 bytes
.../dummy/et/1.0.0/dummy_data.zip | Bin 0 -> 1776 bytes
.../dummy/fa/1.0.0/dummy_data.zip | Bin 0 -> 1653 bytes
.../dummy/fi/1.0.0/dummy_data.zip | Bin 0 -> 1858 bytes
.../dummy/fr/1.0.0/dummy_data.zip | Bin 0 -> 1667 bytes
.../dummy/he/1.0.0/dummy_data.zip | Bin 0 -> 1724 bytes
.../dummy/hi/1.0.0/dummy_data.zip | Bin 0 -> 1809 bytes
.../dummy/hr/1.0.0/dummy_data.zip | Bin 0 -> 1680 bytes
.../dummy/hu/1.0.0/dummy_data.zip | Bin 0 -> 1814 bytes
.../dummy/id/1.0.0/dummy_data.zip | Bin 0 -> 1695 bytes
.../dummy/it/1.0.0/dummy_data.zip | Bin 0 -> 1620 bytes
.../dummy/ja/1.0.0/dummy_data.zip | Bin 0 -> 1806 bytes
.../dummy/ko/1.0.0/dummy_data.zip | Bin 0 -> 1896 bytes
.../dummy/lt/1.0.0/dummy_data.zip | Bin 0 -> 1714 bytes
.../dummy/lv/1.0.0/dummy_data.zip | Bin 0 -> 1756 bytes
.../dummy/ms/1.0.0/dummy_data.zip | Bin 0 -> 1679 bytes
.../dummy/nl/1.0.0/dummy_data.zip | Bin 0 -> 1671 bytes
.../dummy/no/1.0.0/dummy_data.zip | Bin 0 -> 1715 bytes
.../dummy/pl/1.0.0/dummy_data.zip | Bin 0 -> 1806 bytes
.../dummy/pt/1.0.0/dummy_data.zip | Bin 0 -> 1638 bytes
.../dummy/ro/1.0.0/dummy_data.zip | Bin 0 -> 1700 bytes
.../dummy/ru/1.0.0/dummy_data.zip | Bin 0 -> 1994 bytes
.../dummy/sk/1.0.0/dummy_data.zip | Bin 0 -> 1743 bytes
.../dummy/sl/1.0.0/dummy_data.zip | Bin 0 -> 1697 bytes
.../dummy/sr/1.0.0/dummy_data.zip | Bin 0 -> 1710 bytes
.../dummy/sv/1.0.0/dummy_data.zip | Bin 0 -> 1694 bytes
.../dummy/th/1.0.0/dummy_data.zip | Bin 0 -> 2821 bytes
.../dummy/tl/1.0.0/dummy_data.zip | Bin 0 -> 1566 bytes
.../dummy/tr/1.0.0/dummy_data.zip | Bin 0 -> 1855 bytes
.../dummy/uk/1.0.0/dummy_data.zip | Bin 0 -> 1857 bytes
.../dummy/vi/1.0.0/dummy_data.zip | Bin 0 -> 1640 bytes
.../dummy/zh/1.0.0/dummy_data.zip | Bin 0 -> 1316 bytes
datasets/polyglot_ner/polyglot_ner.py | 188 ++++++++++++++++++
43 files changed, 189 insertions(+)
create mode 100644 datasets/polyglot_ner/dataset_infos.json
create mode 100644 datasets/polyglot_ner/dummy/ar/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/bg/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/ca/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/combined/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/cs/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/da/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/de/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/el/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/en/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/es/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/et/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/fa/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/fi/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/fr/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/he/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/hi/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/hr/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/hu/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/id/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/it/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/ja/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/ko/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/lt/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/lv/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/ms/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/nl/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/no/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/pl/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/pt/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/ro/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/ru/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/sk/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/sl/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/sr/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/sv/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/th/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/tl/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/tr/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/uk/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/vi/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/dummy/zh/1.0.0/dummy_data.zip
create mode 100644 datasets/polyglot_ner/polyglot_ner.py
diff --git a/datasets/polyglot_ner/dataset_infos.json b/datasets/polyglot_ner/dataset_infos.json
new file mode 100644
index 00000000000..19c4c7d7d70
--- /dev/null
+++ b/datasets/polyglot_ner/dataset_infos.json
@@ -0,0 +1 @@
+{"ca": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. The dataset contains the basic Wikipedia based\ntraining data for 40 languages we have (with coreference resolution) for the task of\nnamed entity recognition. The details of the procedure of generating them is outlined in\nSection 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data\ncorresponding to a different language. For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ca", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 143746026, "num_examples": 372665, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 143746026, "size_in_bytes": 1250764632}, "de": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. 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For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "de", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 156744752, "num_examples": 547578, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 156744752, "size_in_bytes": 1263763358}, "es": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. 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For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "es", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 145387551, "num_examples": 386699, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 145387551, "size_in_bytes": 1252406157}, "fi": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. 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For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "fi", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 95175890, "num_examples": 387465, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 95175890, "size_in_bytes": 1202194496}, "hi": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. 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For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "hi", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 177698330, "num_examples": 401648, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 177698330, "size_in_bytes": 1284716936}, "id": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. 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For example, \"es\" includes only spanish examples.\n", "citation": "@article{polyglotner,\n author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},\n title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},\n journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},\n month = {April},\n year = {2015},\n publisher = {SIAM},\n}\n", "homepage": "https://sites.google.com/site/rmyeid/projects/polylgot-ner", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "lang": {"dtype": "string", "id": null, "_type": "Value"}, "words": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "builder_name": "polyglot_ner", "config_name": "ko", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 174523416, "num_examples": 560105, "dataset_name": "polyglot_ner"}}, "download_checksums": {"http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz": {"num_bytes": 1107018606, "checksum": "1a64a1f61470050870b4429ea7a3e8376f60dc0fa1a587deeb7d2625baa08f69"}}, "download_size": 1107018606, "post_processing_size": null, "dataset_size": 174523416, "size_in_bytes": 1281542022}, "ms": {"description": "Polyglot-NER\nA training dataset automatically generated from Wikipedia and Freebase the task\nof named entity recognition. 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diff --git a/datasets/polyglot_ner/polyglot_ner.py b/datasets/polyglot_ner/polyglot_ner.py
new file mode 100644
index 00000000000..2ebd02b0e47
--- /dev/null
+++ b/datasets/polyglot_ner/polyglot_ner.py
@@ -0,0 +1,188 @@
+# coding=utf-8
+# Copyright 2020 HuggingFace Datasets Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Lint as: python3
+"""The Polyglot-NER Dataset."""
+
+from __future__ import absolute_import, division, print_function
+
+import os
+
+import datasets
+
+
+_CITATION = """\
+@article{polyglotner,
+ author = {Al-Rfou, Rami and Kulkarni, Vivek and Perozzi, Bryan and Skiena, Steven},
+ title = {{Polyglot-NER}: Massive Multilingual Named Entity Recognition},
+ journal = {{Proceedings of the 2015 {SIAM} International Conference on Data Mining, Vancouver, British Columbia, Canada, April 30- May 2, 2015}},
+ month = {April},
+ year = {2015},
+ publisher = {SIAM},
+}
+"""
+
+_LANGUAGES = [
+ "ca",
+ "de",
+ "es",
+ "fi",
+ "hi",
+ "id",
+ "ko",
+ "ms",
+ "pl",
+ "ru",
+ "sr",
+ "tl",
+ "vi",
+ "ar",
+ "cs",
+ "el",
+ "et",
+ "fr",
+ "hr",
+ "it",
+ "lt",
+ "nl",
+ "pt",
+ "sk",
+ "sv",
+ "tr",
+ "zh",
+ "bg",
+ "da",
+ "en",
+ "fa",
+ "he",
+ "hu",
+ "ja",
+ "lv",
+ "no",
+ "ro",
+ "sl",
+ "th",
+ "uk",
+]
+
+_LANG_FILEPATHS = {
+ lang: os.path.join(
+ "acl_datasets",
+ lang,
+ "data" if lang != "zh" else "", # they're all lang/data/lang_wiki.conll except "zh"
+ f"{lang}_wiki.conll",
+ )
+ for lang in _LANGUAGES
+}
+
+_DESCRIPTION = """\
+Polyglot-NER
+A training dataset automatically generated from Wikipedia and Freebase the task
+of named entity recognition. The dataset contains the basic Wikipedia based
+training data for 40 languages we have (with coreference resolution) for the task of
+named entity recognition. The details of the procedure of generating them is outlined in
+Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
+corresponding to a different language. For example, "es" includes only spanish examples.
+"""
+
+_DATA_URL = "http://cs.stonybrook.edu/~polyglot/ner2/emnlp_datasets.tgz"
+_HOMEPAGE_URL = "https://sites.google.com/site/rmyeid/projects/polylgot-ner"
+_VERSION = "1.0.0"
+
+
+class PolyglotNERConfig(datasets.BuilderConfig):
+ def __init__(self, *args, languages=None, **kwargs):
+ super().__init__(*args, version=datasets.Version(_VERSION, ""), **kwargs)
+ self.languages = languages
+
+ @property
+ def filepaths(self):
+ return [_LANG_FILEPATHS[lang] for lang in self.languages]
+
+
+class PolyglotNER(datasets.GeneratorBasedBuilder):
+ """The Polyglot-NER Dataset"""
+
+ BUILDER_CONFIGS = [
+ PolyglotNERConfig(name=lang, languages=[lang], description=f"Polyglot-NER examples in {lang}.")
+ for lang in _LANGUAGES
+ ] + [
+ PolyglotNERConfig(
+ name="combined", languages=_LANGUAGES, description=f"Complete Polyglot-NER dataset with all languages."
+ )
+ ]
+
+ def _info(self):
+ return datasets.DatasetInfo(
+ description=_DESCRIPTION,
+ features=datasets.Features(
+ {
+ "id": datasets.Value("string"),
+ "lang": datasets.Value("string"),
+ "words": datasets.Sequence(datasets.Value("string")),
+ "ner": datasets.Sequence(datasets.Value("string")),
+ }
+ ),
+ supervised_keys=None,
+ homepage=_HOMEPAGE_URL,
+ citation=_CITATION,
+ )
+
+ def _split_generators(self, dl_manager):
+ """Returns SplitGenerators."""
+ path = dl_manager.download_and_extract(_DATA_URL)
+
+ return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"datapath": path})]
+
+ def _generate_examples(self, datapath):
+ sentence_counter = 0
+ for filepath, lang in zip(self.config.filepaths, self.config.languages):
+ filepath = os.path.join(datapath, filepath)
+ with open(filepath, encoding="utf-8") as f:
+ current_words = []
+ current_ner = []
+ for row in f:
+ row = row.rstrip()
+ if row:
+ token, label = row.split("\t")
+ current_words.append(token)
+ current_ner.append(label)
+ else:
+ # New sentence
+ if not current_words:
+ # Consecutive empty lines will cause empty sentences
+ continue
+ assert len(current_words) == len(current_ner), "💔 between len of words & ner"
+ sentence = (
+ sentence_counter,
+ {
+ "id": str(sentence_counter),
+ "lang": lang,
+ "words": current_words,
+ "ner": current_ner,
+ },
+ )
+ sentence_counter += 1
+ current_words = []
+ current_ner = []
+ yield sentence
+ # Don't forget last sentence in dataset 🧐
+ if current_words:
+ yield sentence_counter, {
+ "id": str(sentence_counter),
+ "lang": lang,
+ "words": current_words,
+ "ner": current_ner,
+ }