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title
BeerQA: A Dataset for Open-Domain Varying-hop Question Answering
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BeerQA Homepage BeerQA Menu BeerQA A Dataset for Open-Domain Varying-hop Question Answering What is BeerQA? BeerQA is an open-domain question answering dataset that features questions requiring information from one or more Wikipedia documents to answer, which presents a more realistic challenge for open-domain question answering. BeerQA is constructed based on the Stanford Question Answering Dataset (SQuAD) and the HotpotQA dataset , by a team of NLP researchers at JD AI Research , Samsung Research , and Stanford University . For more details about BeerQA, please refer to our EMNLP 2021 paper: (Qi, Lee, Sido, & Manning 2021) Getting started BeerQA is distributed under a CC BY-SA 4.0 License . The training and development sets can be downloaded below. Training set (153MB) Dev set (16MB) Test set questions (2.1MB) A more comprehensive summary about data download, preprocessing, baseline model training, and evaluation is included in our GitHub ...
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