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SyntaxNet Models for the CoNLL 2017 Shared Task

Authors :
Alberti, Chris
Andor, Daniel
Bogatyy, Ivan
Collins, Michael
Gillick, Dan
Kong, Lingpeng
Koo, Terry
Ma, Ji
Omernick, Mark
Petrov, Slav
Thanapirom, Chayut
Tung, Zora
Weiss, David
Publication Year :
2017

Abstract

We describe a baseline dependency parsing system for the CoNLL2017 Shared Task. This system, which we call "ParseySaurus," uses the DRAGNN framework [Kong et al, 2017] to combine transition-based recurrent parsing and tagging with character-based word representations. On the v1.3 Universal Dependencies Treebanks, the new system outpeforms the publicly available, state-of-the-art "Parsey's Cousins" models by 3.47% absolute Labeled Accuracy Score (LAS) across 52 treebanks.<br />Comment: Tech report

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.1703.04929
Document Type :
Working Paper