Datasets:
language:
- en
license: apache-2.0
task_categories:
- text-generation
tags:
- crossword
- rebus
- nested-clues
- word-puzzles
pretty_name: Nested Crossword Clues
size_categories:
- 10K<n<100K
source_datasets:
- albertxu/CrosswordQA
- wikimedia/wikipedia
Nested Crossword Clues
A dataset of English sentences with recursively nested crossword clue definitions. Each example starts from a natural sentence sampled from English Wikipedia, where content words are replaced by crossword-style definitions from CrosswordQA. The definitions themselves are then recursively nested — words within clues are replaced by further clues — up to 10 levels deep.
Example
Original sentence (level 0):
He developed the theory of relativity.
Level 1 (words replaced with crossword clues):
He [Brought to maturity] the [Hypothesis] of [Family connection].
Level 2 (words within clues replaced further):
He [Brought to [Full growth]] the [[Educated guess]] of [Family [Link]].
Each example records the sentence at every nesting level, from the plain original to the maximally nested version.
Dataset Fields
| Field | Type | Description |
|---|---|---|
example_id |
int |
Unique example identifier |
source_article_title |
string |
Title of the Wikipedia article the sentence was sampled from |
original_sentence |
string |
The original unmodified sentence (level 0) |
levels |
list[string] |
The sentence at each nesting depth. levels[0] is the original, levels[k] has k layers of [bracketed clue] nesting |
max_nesting_depth |
int |
The deepest nesting level achieved for this example |
num_replacements_per_level |
list[int] |
Number of word-to-clue replacements made at each depth level |
Construction
The dataset is built in four phases:
Clue Index: A lookup table is built from the CrosswordQA train split (~6.4M clue-answer pairs), mapping lowercase answers (up to 2 words) to their corresponding clue strings.
Sentence Sampling: Sentences are sampled from English Wikipedia (November 2023 snapshot) via streaming and reservoir sampling. Sentences are filtered to 5–25 words, must end with sentence-ending punctuation, and must be free of wiki markup artifacts.
Recursive Nesting: For each sentence, content words are replaced with randomly chosen crossword clues from the index. The replacement is then applied recursively to words within the clues themselves, building a tree of nested definitions up to a maximum depth of 10. A max-gap constraint ensures definitions are densely distributed — if too many consecutive words go unreplaced, replacement is forced or the example is dropped.
Anti-cycle Protection: A set of already-replaced words is tracked across all nesting levels. Clues containing previously replaced words are rejected to prevent circular definitions.
Filters and Design Choices
- Stopwords skipped: Common English function words (articles, prepositions, pronouns, auxiliaries) are left unreplaced to maintain readability.
- Bigram matching: Two-word answers from CrosswordQA are matched greedily before single words.
- Max-gap constraint: At the sentence level (depth 1), if 3+ consecutive content words go unreplaced, the next replacement is forced. If no valid clue exists, the entire example is dropped and a new sentence is sampled.
- Min answer length: Answers shorter than 3 characters are excluded from the index.
- Max clue length: Clues longer than 80 characters are excluded.
- No brackets in clues: Clues containing
[,],(,),{,}are excluded to avoid ambiguity with the nesting notation.
Source Datasets
- CrosswordQA — 6.4M crossword clue-answer pairs (train split)
- English Wikipedia — November 2023 snapshot (
20231101.enconfig)
Generation Script
The dataset was generated using scripts/build_nested_clues.py from the rebus-reasoning repository.
python scripts/build_nested_clues.py \
--num-examples 100000 \
--max-depth 10 \
--seed 42 \
--max-answer-words 2 \
--max-gap 3 \
--replacement-prob 0.8 \
--articles-to-scan 50000 \
--save-index output/clue_index.json \
--output output/nested_clues.json
License
Apache 2.0