The HIT-SCIR System for End-to-End Parsing of Universal Dependencies
Wanxiang Che, Jiang Guo, Yuxuan Wang, Bo Zheng, Huaipeng Zhao, Yang Liu, Dechuan Teng, Ting Liu
Abstract
This paper describes our system (HIT-SCIR) for the CoNLL 2017 shared task: Multilingual Parsing from Raw Text to Universal Dependencies. Our system includes three pipelined components: tokenization, Part-of-Speech (POS) tagging and dependency parsing. We use character-based bidirectional long short-term memory (LSTM) networks for both tokenization and POS tagging. Afterwards, we employ a list-based transition-based algorithm for general non-projective parsing and present an improved Stack-LSTM-based architecture for representing each transition state and making predictions. Furthermore, to parse low/zero-resource languages and cross-domain data, we use a model transfer approach to make effective use of existing resources. We demonstrate substantial gains against the UDPipe baseline, with an average improvement of 3.76% in LAS of all languages. And finally, we rank the 4th place on the official test sets.- Anthology ID:
- K17-3005
- Volume:
- Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Jan Hajič, Dan Zeman
- Venue:
- CoNLL
- SIG:
- SIGNLL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 52–62
- Language:
- URL:
- https://aclanthology.org/K17-3005
- DOI:
- 10.18653/v1/K17-3005
- Cite (ACL):
- Wanxiang Che, Jiang Guo, Yuxuan Wang, Bo Zheng, Huaipeng Zhao, Yang Liu, Dechuan Teng, and Ting Liu. 2017. The HIT-SCIR System for End-to-End Parsing of Universal Dependencies. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 52–62, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- The HIT-SCIR System for End-to-End Parsing of Universal Dependencies (Che et al., CoNLL 2017)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/K17-3005.pdf
- Data
- Universal Dependencies