Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases

Yunshi Lan, Jing Jiang


Abstract
Previous work on answering complex questions from knowledge bases usually separately addresses two types of complexity: questions with constraints and questions with multiple hops of relations. In this paper, we handle both types of complexity at the same time. Motivated by the observation that early incorporation of constraints into query graphs can more effectively prune the search space, we propose a modified staged query graph generation method with more flexible ways to generate query graphs. Our experiments clearly show that our method achieves the state of the art on three benchmark KBQA datasets.
Anthology ID:
2020.acl-main.91
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Editors:
Dan Jurafsky, Joyce Chai, Natalie Schluter, Joel Tetreault
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
969–974
Language:
URL:
https://aclanthology.org/2020.acl-main.91
DOI:
10.18653/v1/2020.acl-main.91
Bibkey:
Cite (ACL):
Yunshi Lan and Jing Jiang. 2020. Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 969–974, Online. Association for Computational Linguistics.
Cite (Informal):
Query Graph Generation for Answering Multi-hop Complex Questions from Knowledge Bases (Lan & Jiang, ACL 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/landing_page/2020.acl-main.91.pdf
Video:
 http://slideslive.com/38929263