English

Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings

Computation and Language 2021-07-07 v1 Machine Learning

Abstract

This paper describes the system used in submission from SHANGHAITECH team to the IWPT 2021 Shared Task. Our system is a graph-based parser with the technique of Automated Concatenation of Embeddings (ACE). Because recent work found that better word representations can be obtained by concatenating different types of embeddings, we use ACE to automatically find the better concatenation of embeddings for the task of enhanced universal dependencies. According to official results averaged on 17 languages, our system ranks 2nd over 9 teams.

Keywords

Cite

@article{arxiv.2107.02416,
  title  = {Enhanced Universal Dependency Parsing with Automated Concatenation of Embeddings},
  author = {Xinyu Wang and Zixia Jia and Yong Jiang and Kewei Tu},
  journal= {arXiv preprint arXiv:2107.02416},
  year   = {2021}
}

Comments

Second Place in IWPT 2021 shared task, 7 pages