Frustratingly Hard Evidence Retrieval for QA Over Books
Xiangyang Mou, Mo Yu, Bingsheng Yao, Chenghao Yang, Xiaoxiao Guo, Saloni Potdar, Hui Su
Abstract
A lot of progress has been made to improve question answering (QA) in recent years, but the special problem of QA over narrative book stories has not been explored in-depth. We formulate BookQA as an open-domain QA task given its similar dependency on evidence retrieval. We further investigate how state-of-the-art open-domain QA approaches can help BookQA. Besides achieving state-of-the-art on the NarrativeQA benchmark, our study also reveals the difficulty of evidence retrieval in books with a wealth of experiments and analysis - which necessitates future effort on novel solutions for evidence retrieval in BookQA.- Anthology ID:
- 2020.nuse-1.13
- Volume:
- Proceedings of the First Joint Workshop on Narrative Understanding, Storylines, and Events
- Month:
- July
- Year:
- 2020
- Address:
- Online
- Venues:
- ACL | NUSE | WS
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 108–113
- URL:
- https://www.aclweb.org/anthology/2020.nuse-1.13
- DOI:
- PDF:
- https://www.aclweb.org/anthology/2020.nuse-1.13.pdf
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