From 15f5c8158b1be071f507b8c3846f9695181a234c Mon Sep 17 00:00:00 2001
From: Cavit Erginsoy <cavit@erginsoy.com>
Date: Mon, 3 Feb 2025 07:25:11 +0000
Subject: [PATCH] Add word ladder dataset to GALLERY.md

- Documented word ladder dataset configuration and generation details
- Included three example tasks demonstrating word transformation scenarios
- Updated table of contents with new dataset entry
---
 GALLERY.md | 33 +++++++++++++++++++++++++++++++++
 1 file changed, 33 insertions(+)

diff --git a/GALLERY.md b/GALLERY.md
index f0a2caba..f76b0304 100644
--- a/GALLERY.md
+++ b/GALLERY.md
@@ -31,6 +31,7 @@ This gallery shows examples from all available datasets using their default conf
 - [spell_backward](#spell-backward)
 - [sudoku](#sudoku)
 - [syllogism](#syllogism)
+- [word_ladder](#word-ladder)
 - [word_sequence_reversal](#word-sequence-reversal)
 - [word_sorting](#word-sorting)
 
@@ -1242,6 +1243,38 @@ Metadata: {'premise1': 'No whales are birds', 'premise2': 'Some birds are teache
 
 ```
 
+### word_ladder {word-ladder}
+Generates word ladder transformation tasks
+
+Default configuration:
+```python
+min_word_length = 4
+max_word_length = 4
+min_chain_length = -1
+max_chain_length = -1
+seed = None
+size = 500
+```
+
+Example tasks:
+```
+Example 1:
+Question: Transform the word ladder 'COLD' to 'WARM' by changing one letter at a time.
+Answer: COLD,CORD,CARD,WARD,WARM
+Metadata: {'start_word': 'COLD', 'end_word': 'WARM', 'word_length': 4, 'chain_length': 5}
+
+Example 2:
+Question: Transform the word ladder 'DARK' to 'LIGHT' by changing one letter at a time.
+Answer: DARK,DARE,DATE,LATE,LITE,LIGHT
+Metadata: {'start_word': 'DARK', 'end_word': 'LIGHT', 'word_length': 4, 'chain_length': 6}
+
+Example 3:
+Question: Transform the word ladder 'HEAD' to 'TAIL' by changing one letter at a time.
+Answer: HEAD,HEAL,TEAL,TAIL
+Metadata: {'start_word': 'HEAD', 'end_word': 'TAIL', 'word_length': 4, 'chain_length': 4}
+
+```
+
 ### word_sequence_reversal {word-sequence-reversal}
 Generates word sequence reversal tasks from text spans