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JaQuAD: Japanese Question Answering Dataset for Machine Reading Comprehension
[article]
2022
arXiv
pre-print
Question Answering (QA) is a task in which a machine understands a given document and a question to find an answer. Despite impressive progress in the NLP area, QA is still a challenging problem, especially for non-English languages due to the lack of annotated datasets. In this paper, we present the Japanese Question Answering Dataset, JaQuAD, which is annotated by humans. JaQuAD consists of 39,696 extractive question-answer pairs on Japanese Wikipedia articles. We finetuned a baseline model
arXiv:2202.01764v1
fatcat:m445sc2hdjd5tmb3nrov6eilma