2019/05/22 by Hashemi, Helia, Aliannejadi, Mohammad, Zamani, Hamed +1 · 6 citations
#Computation and Language (cs.CL) #FOS: Computer and information sciences #Information Retrieval (cs.IR)
paper · doi:10.48550/arxiv.1905.08957
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 34,011 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 recently developed neural IR models.