Unlexicalized dependency parser for variable word order languages based on local contextual pattern

Hoojung Chung, Hae-Chang Rim

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

We investigate the effect of unlexicalization in a dependency parser for variable word order languages and propose an unlexicalized parser which can utilize some contextual information in order to achieve performance comparable to that of lexicalized parsers. Unlexicalization of an early dependency parser makes performance decrease by 3.6%. However, when we modify the unlexicalized parser into the one which can consider additional contextual information, the parser performs better than some lexicalized dependency parsers, while it requires simpler smoothing processes, less time and space for parsing.

Original languageEnglish
Pages (from-to)112-123
Number of pages12
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2945
Publication statusPublished - 2004 Dec 1

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Language
Parsing
Smoothing
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ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Computer Science(all)
  • Theoretical Computer Science

Cite this

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