Multilingual syntactic-semantic dependency parsing with three-stage approximate max-margin linear models

Yotaro Watanabe, Masayuki Asahara, Yuji Matsumoto

Research output: Contribution to conferencePaperpeer-review

1 Citation (Scopus)

Abstract

This paper describes a system for syntacticsemantic dependency parsing for multiple languages. The system consists of three parts: a state-of-the-art higher-order projective dependency parser for syntactic dependency parsing, a predicate classifier, and an argument classifier for semantic dependency parsing. For semantic dependency parsing, we explore use of global features. All components are trained with an approximate max-margin learning algorithm. In the closed challenge of the CoNLL-2009 Shared Task (Hajič et al., 2009), our system achieved the 3rd best performances for English and Czech, and the 4th best performance for Japanese.

Original languageEnglish
Pages114-119
Number of pages6
DOIs
Publication statusPublished - 2009
Event13th Conference on Computational Natural Language Learning, CoNLL 2009 - Boulder, CO, United States
Duration: 2009 Jun 42009 Jun 4

Other

Other13th Conference on Computational Natural Language Learning, CoNLL 2009
CountryUnited States
CityBoulder, CO
Period09/6/409/6/4

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Linguistics and Language

Fingerprint Dive into the research topics of 'Multilingual syntactic-semantic dependency parsing with three-stage approximate max-margin linear models'. Together they form a unique fingerprint.

Cite this