Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering

Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Hong Wang, Shiyu Chang, Murray Campbell, William Yang Wang

Abstract
A key challenge of multi-hop question answering (QA) in the open-domain setting is to accurately retrieve the supporting passages from a large corpus. Existing work on open-domain QA typically relies on off-the-shelf information retrieval (IR) techniques to retrieve answer passages, i.e., the passages containing the groundtruth answers. However, IR-based approaches are insufficient for multi-hop questions, as the topic of the second or further hops is not explicitly covered by the question. To resolve this issue, we introduce a new subproblem of open-domain multi-hop QA, which aims to recognize the bridge (i.e., the anchor that links to the answer passage) from the context of a set of start passages with a reading comprehension model. This model, the bridge reasoner, is trained with a weakly supervised signal and produces the candidate answer passages for the passage reader to extract the answer. On the full-wiki HotpotQA benchmark, we significantly improve the baseline method by 14 point F1. Without using any memory inefficient contextual embeddings, our result is also competitive with the state-of-the-art that applies BERT in multiple modules.
Anthology ID:
D19-5806
Volume:
Proceedings of the 2nd Workshop on Machine Reading for Question Answering
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen
Venue:
WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
48–52
Language:
URL:
https://aclanthology.org/D19-5806
DOI:
10.18653/v1/D19-5806
Bibkey:
Cite (ACL):
Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Hong Wang, Shiyu Chang, Murray Campbell, and William Yang Wang. 2019. Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering. In Proceedings of the 2nd Workshop on Machine Reading for Question Answering, pages 48–52, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering (Xiong et al., 2019)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-3/D19-5806.pdf
Data
HotpotQA, SQuAD
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