Japanese semantic role labeling with hierarchical tag context trees

Yasuhiro Ishihara, Koichi Takeuchi

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

Abstract

In this paper we describe that the hierarchical tag context tree (HTCT) approach improves the accuracy of semantic role labeling on Japanese text. In Japanese language there are functional multiword expressions such as no-tame-ni and yotte that have potential to designate semantic relations between a predicate and its arguments. Since these expressions come to the end part of each argument, the performance of the CRF-based semantic role labeler can be improved by taking into account the last morphemes of each argument as features. We apply our proposed system to the annotated corpus of semantic role labels on a balanced Japanese corpus. The experimental results show that the CRFbased labeler with features extracted by HTCT approach outperforms the normal CRF-based labeler.

Original languageEnglish
Title of host publicationComputational Linguistics - 14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015, Revised Selected Papers
EditorsKoiti Hasida, Ayu Purwarianti
PublisherSpringer Verlag
Pages21-32
Number of pages12
ISBN (Print)9789811005145
DOIs
Publication statusPublished - 2016
Event14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015 - Bali, Indonesia
Duration: May 19 2015May 21 2015

Publication series

NameCommunications in Computer and Information Science
Volume593
ISSN (Print)1865-0929

Other

Other14th International Conference of the Pacific Association for Computaitonal Linguistics, PACLING 2015
Country/TerritoryIndonesia
CityBali
Period5/19/155/21/15

Keywords

  • CRFs
  • Hierarchical tag context trees
  • Semantic role labeling

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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