Dataset Card for "art"

Dataset Summary

ART consists of over 20k commonsense narrative contexts and 200k explanations.

The Abductive Natural Language Inference Dataset from AI2.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

Data Instances

anli

• Size of downloaded dataset files: 5.12 MB
• Size of the generated dataset: 34.36 MB
• Total amount of disk used: 39.48 MB

An example of 'train' looks as follows.

{
    "hypothesis_1": "Chad's car had all sorts of other problems besides alignment.",
    "hypothesis_2": "Chad's car had all sorts of benefits other than being sexy.",
    "label": 1,
    "observation_1": "Chad went to get the wheel alignment measured on his car.",
    "observation_2": "The mechanic provided a working alignment with new body work."
}

Data Fields

The data fields are the same among all splits.

anli

• observation_1 : a string feature.
• observation_2 : a string feature.
• hypothesis_1 : a string feature.
• hypothesis_2 : a string feature.
• label : a classification label, with possible values including 0 (0), 1 (1), 2 (2).

Data Splits

name	train	validation
anli	169654	1532

Dataset Creation

Curation Rationale

More Information Needed

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

More Information Needed

Licensing Information

More Information Needed

Citation Information

@inproceedings{Bhagavatula2020Abductive,
  title={Abductive Commonsense Reasoning},
  author={Chandra Bhagavatula and Ronan Le Bras and Chaitanya Malaviya and Keisuke Sakaguchi and Ari Holtzman and Hannah Rashkin and Doug Downey and Wen-tau Yih and Yejin Choi},
  booktitle={International Conference on Learning Representations},
  year={2020},
  url={https://openreview.net/forum?id=Byg1v1HKDB}
}

Contributions

Thanks to @patrickvonplaten , @thomwolf , @mariamabarham , @lewtun , @lhoestq for adding this dataset.