Acquisition of phrase correspondences using natural deduction proofs

Hitomi Yanaka, Koji Mineshima, Pascual Martínez-Ǵomez, Daisuke Bekki

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

How to identify, extract, and use phrasal knowledge is a crucial problem for the task of Recognizing Textual Entailment (RTE). To solve this problem, we propose a method for detecting paraphrases via natural deduction proofs of semantic relations between sentence pairs. Our solution relies on a graph reformulation of partial variable unifications and an algorithm that induces subgraph alignments between meaning representations. Experiments show that our method can automatically detect various paraphrases that are absent from existing paraphrase databases. In addition, the detection of paraphrases using proof information improves the accuracy of RTE tasks.

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756-766
ページ数11
ISBN(電子版)9781948087278
出版ステータスPublished - 2018
外部発表はい
イベント2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 - New Orleans, United States
継続期間: 2018 6月 12018 6月 6

出版物シリーズ

名前NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference
1

Conference

Conference2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018
国/地域United States
CityNew Orleans
Period18/6/118/6/6

ASJC Scopus subject areas

  • 言語学および言語
  • 言語および言語学
  • コンピュータ サイエンスの応用

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