Abstract
Hypernym-hyponym (“is-a”) relations are key components in taxonomies, object hierarchies and knowledge graphs. While there is abundant research on is-a relation extraction in English, it still remains a challenge to identify such relations from Chinese knowledge sources accurately due to the flexibility of language expression. In this paper, we introduce a weakly supervised framework to extract Chinese is-a relations from user generated categories. It employs piecewise linear projection models trained on a Chinese taxonomy and an iterative learning algorithm to update models incrementally. A pattern-based relation selection method is proposed to prevent “semantic drift” in the learning process using bi-criteria optimization. Experimental results illustrate that the proposed approach outperforms state-of-the-art methods.- Anthology ID:
- C16-1128
- 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:
- 1350–1361
- Language:
- URL:
- https://aclanthology.org/C16-1128
- DOI:
- Cite (ACL):
- Chengyu Wang and Xiaofeng He. 2016. Chinese Hypernym-Hyponym Extraction from User Generated Categories. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 1350–1361, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- Chinese Hypernym-Hyponym Extraction from User Generated Categories (Wang & He, COLING 2016)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/C16-1128.pdf