Yufang Liu


2018

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AntNLP at CoNLL 2018 Shared Task: A Graph-Based Parser for Universal Dependency Parsing
Tao Ji | Yufang Liu | Yijun Wang | Yuanbin Wu | Man Lan
Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

We describe the graph-based dependency parser in our system (AntNLP) submitted to the CoNLL 2018 UD Shared Task. We use bidirectional lstm to get the word representation, then a bi-affine pointer networks to compute scores of candidate dependency edges and the MST algorithm to get the final dependency tree. From the official testing results, our system gets 70.90 LAS F1 score (rank 9/26), 55.92 MLAS (10/26) and 60.91 BLEX (8/26).