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Korquad1.0: Korean QA Dataset For Machine Reading Comprehension

Seungyoung Lim, Myungji Kim, Jooyoul Lee . Arxiv 2019 – 50 citations

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Compositional Generalization Content Enrichment Datasets Has Code Image Text Integration Interactive Environments Interdisciplinary Approaches Multimodal Semantic Representation Neural Machine Translation Productivity Enhancement Question Answering

Machine Reading Comprehension (MRC) is a task that requires machine to understand natural language and answer questions by reading a document. It is the core of automatic response technology such as chatbots and automatized customer supporting systems. We present Korean Question Answering Dataset(KorQuAD), a large-scale Korean dataset for extractive machine reading comprehension task. It consists of 70,000+ human generated question-answer pairs on Korean Wikipedia articles. We release KorQuAD1.0 and launch a challenge at https://KorQuAD.github.io to encourage the development of multilingual natural language processing research.

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