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
- Editors:
- Yuji Matsumoto, Rashmi Prasad
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 2503–2514
- Language:
- URL:
- https://aclanthology.org/C16-1236
- DOI:
- 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)
- PDF:
- https://preview.aclanthology.org/bionlp-24-ingestion/C16-1236.pdf
- Code
- JunweiBao/MulCQA
- Data
- SimpleQuestions