Second-Order Neural Dependency Parsing with Message Passing and End-to-End Training

10 Oct 2020 Xinyu Wang Kewei Tu

In this paper, we propose second-order graph-based neural dependency parsing using message passing and end-to-end neural networks. We empirically show that our approaches match the accuracy of very recent state-of-the-art second-order graph-based neural dependency parsers and have significantly faster speed in both training and testing... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK BENCHMARK
Dependency Parsing Chinese Pennbank MFVI UAS 92.78 # 1
LAS 91.69 # 1
Dependency Parsing Penn Treebank MFVI UAS 96.91 # 2
LAS 95.34 # 2

Methods used in the Paper