Using Wikipedia and Semantic Resources to Find Answer Types and Appropriate Answer Candidate Sets in Question Answering

Po-Chun Chen, Meng-Jie Zhuang, Chuan-Jie Lin


Abstract
This paper proposes a new idea that uses Wikipedia categories as answer types and defines candidate sets inside Wikipedia. The focus of a given question is searched in the hierarchy of Wikipedia main pages. Our searching strategy combines head-noun matching and synonym matching provided in semantic resources. The set of answer candidates is determined by the entry hierarchy in Wikipedia and the hyponymy hierarchy in WordNet. The experimental results show that the approach can find candidate sets in a smaller size but achieve better performance especially for ARTIFACT and ORGANIZATION types, where the performance is better than state-of-the-art Chinese factoid QA systems.
Anthology ID:
W16-4401
Volume:
Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016)
Month:
December
Year:
2016
Address:
Osaka, Japan
Editors:
Key-Sun Choi, Christina Unger, Piek Vossen, Jin-Dong Kim, Noriko Kando, Axel-Cyrille Ngonga Ngomo
Venue:
WS
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
1–10
Language:
URL:
https://aclanthology.org/W16-4401
DOI:
Bibkey:
Cite (ACL):
Po-Chun Chen, Meng-Jie Zhuang, and Chuan-Jie Lin. 2016. Using Wikipedia and Semantic Resources to Find Answer Types and Appropriate Answer Candidate Sets in Question Answering. In Proceedings of the Open Knowledge Base and Question Answering Workshop (OKBQA 2016), pages 1–10, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Using Wikipedia and Semantic Resources to Find Answer Types and Appropriate Answer Candidate Sets in Question Answering (Chen et al., 2016)
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PDF:
https://aclanthology.org/W16-4401.pdf