Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: null
pretty_name: Cryptonite
dataset_info:
- config_name: default
features:
- name: agent_info
sequence:
- name: Bottomline
dtype: string
- name: Role
dtype: string
- name: Target
dtype: float32
- name: agent_turn
sequence: int32
- name: dialogue_acts
sequence:
- name: intent
dtype: string
- name: price
dtype: float32
- name: utterance
sequence: string
- name: items
sequence:
- name: Category
dtype: string
- name: Images
dtype: string
- name: Price
dtype: float32
- name: Description
dtype: string
- name: Title
dtype: string
splits:
- name: train
num_bytes: 8538836
num_examples: 5247
- name: test
num_bytes: 1353933
num_examples: 838
- name: validation
num_bytes: 966032
num_examples: 597
download_size: 25373618
dataset_size: 10858801
- config_name: cryptonite
features:
- name: clue
dtype: string
- name: answer
dtype: string
- name: enumeration
dtype: string
- name: publisher
dtype: string
- name: date
dtype: int64
- name: quick
dtype: bool
- name: id
dtype: string
splits:
- name: train
num_bytes: 52228597
num_examples: 470804
- name: validation
num_bytes: 2901768
num_examples: 26156
- name: test
num_bytes: 2908275
num_examples: 26157
download_size: 21615952
dataset_size: 58038640
config_names:
- cryptonite
- default
Dataset Card for Cryptonite
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
Dataset Summary
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%).
Languages
English
Dataset Structure
Data Instances
This is one example from the train set.
{
'clue': 'make progress socially in stated region (5)',
'answer': 'climb',
'date': 971654400000,
'enumeration': '(5)',
'id': 'Times-31523-6across',
'publisher': 'Times',
'quick': False
}
Data Fields
clue
: a string representing the clue provided for the crosswordanswer
: a string representing the answer to the clueenumeration
: a string representing thepublisher
: a string representing the publisher of the crossworddate
: a int64 representing the UNIX timestamp of the date of publication of the crosswordquick
: a bool representing whether the crossword is quick (a crossword aimed at beginners, easier to solve)id
: a string to uniquely identify a given example in the dataset
Data Splits
Train (470,804 examples), validation (26,156 examples), test (26,157 examples).
Dataset Creation
Curation Rationale
Crosswords from the Times and the Telegraph.
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
Avia Efrat, Uri Shaham, Dan Kilman, Omer Levy
Licensing Information
cc-by-nc-4.0
Citation Information
@misc{efrat2021cryptonite,
title={Cryptonite: A Cryptic Crossword Benchmark for Extreme Ambiguity in Language},
author={Avia Efrat and Uri Shaham and Dan Kilman and Omer Levy},
year={2021},
eprint={2103.01242},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Contributions
Thanks to @theo-m for adding this dataset.