Constraint-Based Question Answering with Knowledge Graph

Junwei Bao, Nan Duan, Zhao Yan, Ming Zhou, Tiejun Zhao


Abstract
WebQuestions and SimpleQuestions are two benchmark data-sets commonly used in recent knowledge-based question answering (KBQA) work. Most questions in them are ‘simple’ questions which can be answered based on a single relation in the knowledge base. Such data-sets lack the capability of evaluating KBQA systems on complicated questions. Motivated by this issue, we release a new data-set, namely ComplexQuestions, aiming to measure the quality of KBQA systems on ‘multi-constraint’ questions which require multiple knowledge base relations to get the answer. Beside, we propose a novel systematic KBQA approach to solve multi-constraint questions. Compared to state-of-the-art methods, our approach not only obtains comparable results on the two existing benchmark data-sets, but also achieves significant improvements on the ComplexQuestions.
Anthology ID:
C16-1236
Volume:
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
Month:
December
Year:
2016
Address:
Osaka, Japan
Venue:
COLING
SIG:
Publisher:
The COLING 2016 Organizing Committee
Note:
Pages:
2503–2514
Language:
URL:
https://aclanthology.org/C16-1236
DOI:
Bibkey:
Cite (ACL):
Junwei Bao, Nan Duan, Zhao Yan, Ming Zhou, and Tiejun Zhao. 2016. Constraint-Based Question Answering with Knowledge Graph. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 2503–2514, Osaka, Japan. The COLING 2016 Organizing Committee.
Cite (Informal):
Constraint-Based Question Answering with Knowledge Graph (Bao et al., COLING 2016)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp-22-attachments/C16-1236.pdf
Code
 JunweiBao/MulCQA
Data
SimpleQuestions