A Transition-Based System for Joint Part-of-Speech Tagging and Labeled Non-Projective Dependency Parsing.

Bernd Bohnet, Joakim Nivre

Research output: Chapter in Book/Report/Conference proceedingConference contribution

130 Citations (Scopus)
16 Downloads (Pure)

Abstract

Most current dependency parsers presuppose
that input words have been morphologically
disambiguated using a part-of-speech tagger
before parsing begins. We present a transitionbased system for joint part-of-speech tagging
and labeled dependency parsing with nonprojective trees. Experimental evaluation on
Chinese, Czech, English and German shows
consistent improvements in both tagging and
parsing accuracy when compared to a pipeline
system, which lead to improved state-of-theart results for all languages.
Original languageEnglish
Title of host publicationAssociation for Computational Linguistics
Subtitle of host publicationJoint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Pages1455-1465
Number of pages10
Publication statusPublished - 2012

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