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Datasets:
allenai
/
ai2_arc

Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
open-domain-qa
multiple-choice-qa
Languages:
English
Size:
1K - 10K
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Dataset card Viewer Files Community
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albertvillanova HF staff commited on
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0555bd8
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1 Parent(s): a47c900

Delete legacy dataset_infos.json

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  1. dataset_infos.json +0 -134
dataset_infos.json DELETED
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- {
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- "ARC-Challenge": {
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- "description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n",
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- "citation": "@article{allenai:arc,\n author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and\n Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},\n title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},\n journal = {arXiv:1803.05457v1},\n year = {2018},\n}\n",
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- "description": "A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in\n advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains\n only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also\n including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.\n",
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