An improved neural network model for joint POS tagging and dependency parsing

We propose a novel neural network model for joint part-of-speech (POS) tagging and dependency parsing. Our model extends the well-known BIST graph-based dependency parser (Kiperwasser and Goldberg, 2016) by incorporating a BiLSTM-based tagging component to produce automatically predicted POS tags for the parser... (read more)

PDF Abstract CONLL 2018 PDF CONLL 2018 Abstract

Datasets


Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Dependency Parsing Penn Treebank jPTDP POS 97.97 # 1
UAS 94.51 # 12
LAS 92.87 # 13

Methods used in the Paper


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