Haonan Li

Haonan Li

Postdoc at MBZUAI

Neural character-level dependency parsing for Chinese

Haonan Li, Zhisong Zhang, Yuqi Ju, Hai Zhao Neural character-level dependency parsing for Chinese. In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI), 2018

@inproceedings{DBLP:conf/aaai/LiZJZ18,
  author    = {Haonan Li and
               Zhisong Zhang and
               Yuqi Ju and
               Hai Zhao},
  title     = {Neural Character-level Dependency Parsing for Chinese},
  booktitle = {Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence,
               New Orleans, Louisiana, USA},
  pages     = {5205--5212},
  publisher = {AAAI Press},
  year      = {2018},
  url       = {https://www.aaai.org/ocs/index.php/AAAI/AAAI18/paper/view/17076},
}

Abstract

This paper presents a truly full character-level neural dependency parser together with a newly released character-level dependency treebank for Chinese, which has suffered a lot from the dilemma of defining word or not to model character interactions. Integrating full character-level dependencies with character embedding and human annotated characterlevel part-of-speech and dependency labels for the first time, we show an extra performance enhancement from the evaluation on Chinese Penn Treebank and SJTU (Shanghai Jiao Tong University) Chinese Character Dependency Treebank and the potential of better understanding deeper structure of Chinese sentences.