Constructing Datasets for Multi-hop Reading Comprehension Across Documents (arXiv)

arxiv.org

Question answering (QA) has seen many improvements in recent years, particularly fuelled by new datasets such as SQuAD. Existing datasets, however, focus on single-hop reading comprehension, i.e. extracting an answer to a question from a given paragraph. Welbl et al. introduce two new datasets for multi-hop reading comprehension, which is much closer the real-world task of open-domain question answering. The datasets require models to first identify relevant documents among a number of candidate documents and then determine the correct answer.

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