Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language
Abstract
Current NLP datasets targeting ambiguity can be solved by a native speaker with relative ease. We present Cryptonite, a large-scale dataset based on cryptic crosswords, which is both linguistically complex and naturally sourced. Each example in Cryptonite is a cryptic clue, a short phrase or sentence with a misleading surface reading, whose solving requires disambiguating semantic, syntactic, and phonetic wordplays, as well as world knowledge. Cryptic clues pose a challenge even for experienced solvers, though top-tier experts can solve them with almost 100% accuracy. Cryptonite is a challenging task for current models; fine-tuning T5-Large on 470k cryptic clues achieves only 7.6% accuracy, on par with the accuracy of a rule-based clue solver (8.6%).
Keywords
Cite
@article{arxiv.2103.01242,
title = {Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language},
author = {Avia Efrat and Uri Shaham and Dan Kilman and Omer Levy},
journal= {arXiv preprint arXiv:2103.01242},
year = {2021}
}
Comments
EMNLP 2021