PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples

Daisuke Kawahara, Sadao Kurohashi

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

5 Citations (Scopus)

Abstract

We present a PP-attachment disambiguation method based on a gigantic volume of unambiguous examples extracted from raw corpus. The unambiguous examples are utilized to acquire precise lexical preferences for PP-attachment disambiguation. Attachment decisions are made by a machine learning method that optimizes the use of the lexical preferences. Our experiments indicate that the precise lexical preferences work effectively.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages188-198
Number of pages11
DOIs
Publication statusPublished - 2005
Event2nd International Joint Conference on Natural Language Processing, IJCNLP 2005 - Jeju Island, Korea, Republic of
Duration: Oct 11 2005Oct 13 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3651 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other2nd International Joint Conference on Natural Language Processing, IJCNLP 2005
Country/TerritoryKorea, Republic of
CityJeju Island
Period10/11/0510/13/05

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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