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• W3017330897 abstract "Considering the widespread use of mobile and voice search, answer passage retrieval for non-factoid questions plays a critical role in modern information retrieval systems. Despite the importance of the task, the community still feels the significant lack of large-scale non-factoid question answering collections with real questions and comprehensive relevance judgments. In this paper, we develop and release a collection of 2,626 open-domain non-factoid questions from a diverse set of categories. The dataset, called ANTIQUE, contains 34k manual relevance annotations. The questions were asked by real users in a community question answering service, i.e., Yahoo! Answers. Relevance judgments for all the answers to each question were collected through crowdsourcing. To facilitate further research, we also include a brief analysis of the data as well as baseline results on both classical and neural IR models." @default.
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• W3017330897 date "2020-01-01" @default.
• W3017330897 modified "2023-10-16" @default.
• W3017330897 title "ANTIQUE: A Non-factoid Question Answering Benchmark" @default.
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• W3017330897 doi "https://doi.org/10.1007/978-3-030-45442-5_21" @default.
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