Improving Chinese semantic role labeling using high-quality surface and deep case frames

Gongye Jin, Daisuke Kawahara, Sadao Kurohashi

研究成果: Conference contribution

抄録

This paper presents a method for improving semantic role labeling (SRL) using a large amount of automatically acquired knowledge. We acquire two varieties of knowledge, which we call surface case frames and deep case frames. Although the surface case frames are compiled from syntactic parses and can be used as rich syntactic knowledge, they have limited capability for resolving semantic ambiguity. To compensate the deficiency of the surface case frames, we compile deep case frames from automatic semantic roles. We also consider quality management for both types of knowledge in order to get rid of the noise brought from the automatic analyses. The experimental results show that Chinese SRL can be improved using automatically acquired knowledge and the quality management shows a positive effect on this task.

本文言語English
ホスト出版物のタイトルLong Papers
出版社Association for Computational Linguistics (ACL)
ページ568-577
ページ数10
ISBN(電子版)9781510838604
DOI
出版ステータスPublished - 2017
外部発表はい
イベント15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Valencia, Spain
継続期間: 2017 4 32017 4 7

出版物シリーズ

名前15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference
1

Conference

Conference15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017
CountrySpain
CityValencia
Period17/4/317/4/7

ASJC Scopus subject areas

  • Linguistics and Language
  • Language and Linguistics

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