tau/commonsense_qa

Dataset Overview

Basic Information

• Name: CommonsenseQA
• Language: English (en)
• License: MIT
• Multilinguality: Monolingual
• Size: 1K<n<10K
• Source Data: Original data
• Task Category: Question Answering
• Task ID: open-domain-qa
• Paper Code ID: commonsenseqa
• Display Name: CommonsenseQA

Dataset Structure

• Features:
  • id: String type, unique ID.
  • question: String type, question description.
  • question_concept: String type, concept related to the question.
  • choices: Dictionary type, containing option labels and texts.
    • label: String type, option label.
    • text: String type, option text.
  • answerKey: String type, correct answer.
• Data Splits:
  • train: 9,741 samples, 2,207,794 bytes.
  • validation: 1,221 samples, 273,848 bytes.
  • test: 1,140 samples, 257,842 bytes.
  • Total Download Size: 1,558,570 bytes.
  • Total Dataset Size: 2,739,484 bytes.

Dataset Creation

• Annotation Creators: Crowd‑sourced
• Language Creators: Crowd‑sourced

Usage Considerations

• License: MIT, see details at this link.

• Citation Information:

  @inproceedings{talmor-etal-2019-commonsenseqa, title = "{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge", author = "Talmor, Alon and Herzig, Jonathan and Lourie, Nicholas and Berant, Jonathan", booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)", month = jun, year = "2019", address = "Minneapolis, Minnesota", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/N19-1421", doi = "10.18653/v1/N19-1421", pages = "4149--4158", archivePrefix = "arXiv", eprint = "1811.00937", primaryClass = "cs", }

Contributors

• @thomwolf
• @lewtun
• @albertvillanova
• @patrickvonplaten