arXiv (Cornell University) · 2017 · 38 citations · 10 references
Language StudiesComputer ScienceLinguisticsComputational LinguisticsNatural Language ProcessingSyntaxDependency ParsingLanguage ModelsParsingSyntactic AnalysisSyntactic ParsingSyntax ParsingAutomatic Dependency ParsingCharacter-based EmbeddingsNeural Dependency ParsingNeural ParsingParsing Accuracy MetricsParsing With Dependency GrammarsRecurrent Neural Network TaggingTransition-based Dependency Parsing
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.
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