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        "description": "CommonsenseQA is a new multiple-choice question answering dataset that requires different types of commonsense knowledge\nto predict the correct answers . It contains 12,102 questions with one correct answer and four distractor answers.\nThe dataset is provided in two major training/validation/testing set splits: \"Random split\" which is the main evaluation\nsplit, and \"Question token split\", see paper for details.\n",
        "citation": "@inproceedings{talmor-etal-2019-commonsenseqa,\n    title = \"{C}ommonsense{QA}: A Question Answering Challenge Targeting Commonsense Knowledge\",\n    author = \"Talmor, Alon  and\n      Herzig, Jonathan  and\n      Lourie, Nicholas  and\n      Berant, Jonathan\",\n    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)\",\n    month = jun,\n    year = \"2019\",\n    address = \"Minneapolis, Minnesota\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/N19-1421\",\n    doi = \"10.18653/v1/N19-1421\",\n    pages = \"4149--4158\",\n    archivePrefix = \"arXiv\",\n    eprint        = \"1811.00937\",\n    primaryClass  = \"cs\",\n}\n",
        "homepage": "https://www.tau-nlp.org/commonsenseqa",
        "license": "",
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