gsarti/nested-crosswords

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:

1. 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.

2. 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.

3. 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.

4. 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.en config)

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