Datasets:
cryptonite

	---
	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-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: [Github](https://github.com/aviaefrat/cryptonite)
	- Repository: [Github](https://github.com/aviaefrat/cryptonite)
	- Paper: [Arxiv](https://arxiv.org/pdf/2103.01242.pdf)
	- Leaderboard:
	- Point of Contact: [Twitter](https://twitter.com/AviaEfrat)

	### 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.

	```python
	{
	'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 crossword
	- `answer`: a string representing the answer to the clue
	- `enumeration`: a string representing the
	- `publisher`: a string representing the publisher of the crossword
	- `date`: a int64 representing the UNIX timestamp of the date of publication of the crossword
	- `quick`: 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](https://github.com/theo-m) for adding this dataset.