SCTB: A Chinese Treebank in Scientific Domain
Chenhui Chu, Toshiaki Nakazawa, Daisuke Kawahara, Sadao Kurohashi
Abstract
Treebanks are curial for natural language processing (NLP). In this paper, we present our work for annotating a Chinese treebank in scientific domain (SCTB), to address the problem of the lack of Chinese treebanks in this domain. Chinese analysis and machine translation experiments conducted using this treebank indicate that the annotated treebank can significantly improve the performance on both tasks. This treebank is released to promote Chinese NLP research in scientific domain.- Anthology ID:
- W16-5407
- Volume:
- Proceedings of the 12th Workshop on Asian Language Resources (ALR12)
- Month:
- December
- Year:
- 2016
- Address:
- Osaka, Japan
- Editors:
- Koiti Hasida, Kam-Fai Wong, Nicoletta Calzorari, Key-Sun Choi
- Venue:
- ALR
- SIG:
- Publisher:
- The COLING 2016 Organizing Committee
- Note:
- Pages:
- 59–67
- Language:
- URL:
- https://aclanthology.org/W16-5407
- DOI:
- Cite (ACL):
- Chenhui Chu, Toshiaki Nakazawa, Daisuke Kawahara, and Sadao Kurohashi. 2016. SCTB: A Chinese Treebank in Scientific Domain. In Proceedings of the 12th Workshop on Asian Language Resources (ALR12), pages 59–67, Osaka, Japan. The COLING 2016 Organizing Committee.
- Cite (Informal):
- SCTB: A Chinese Treebank in Scientific Domain (Chu et al., ALR 2016)
- PDF:
- https://preview.aclanthology.org/naacl24-info/W16-5407.pdf
- Data
- Universal Dependencies