Abstract
Words to express relations in natural language (NL) statements may be different from those to represent properties in knowledge bases (KB). The vocabulary gap becomes barriers for knowledge base construction and retrieval. With the demo system called NL2KB in this paper, users can browse which properties in KB side may be mapped to for a given relational pattern in NL side. Besides, they can retrieve the sets of relational patterns in NL side for a given property in KB side. We describe how the mapping is established in detail. Although the mined patterns are used for Chinese knowledge base applications, the methodology can be extended to other languages.- Anthology ID:
- C16-2059
- Volume:
- Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editor:
- Hideo Watanabe
- Venue:
- COLING
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 282–286
- Language:
- URL:
- https://aclanthology.org/C16-2059
- DOI:
- Cite (ACL):
- Sheng-Lun Wei, Yen-Pin Chiu, Hen-Hsen Huang, and Hsin-Hsi Chen. 2016. NL2KB: Resolving Vocabulary Gap between Natural Language and Knowledge Base in Knowledge Base Construction and Retrieval. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations, pages 282–286, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- NL2KB: Resolving Vocabulary Gap between Natural Language and Knowledge Base in Knowledge Base Construction and Retrieval (Wei et al., COLING 2016)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/C16-2059.pdf