Visual denotations for recognizing textual entailment

Dan Han, Pascual Martínez-Gómez, Koji Mineshima

研究成果: Conference contribution

6 被引用数 (Scopus)

抄録

In the logic approach to Recognizing Textual Entailment, identifying phrase-to-phrase semantic relations is still an unsolved problem. Resources such as the Paraphrase Database offer limited coverage despite their large size whereas unsupervised distributional models of meaning often fail to recognize phrasal entailments. We propose to map phrases to their visual denotations and compare their meaning in terms of their images. We show that our approach is effective in the task of Recognizing Textual Entailment when combined with specific linguistic and logic features.

本文言語English
ホスト出版物のタイトルEMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings
出版社Association for Computational Linguistics (ACL)
ページ2853-2859
ページ数7
ISBN(電子版)9781945626838
DOI
出版ステータスPublished - 2017
外部発表はい
イベント2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017 - Copenhagen, Denmark
継続期間: 2017 9月 92017 9月 11

出版物シリーズ

名前EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings

Conference

Conference2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017
国/地域Denmark
CityCopenhagen
Period17/9/917/9/11

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 情報システム
  • 計算理論と計算数学

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