Combining Event Semantics and Degree Semantics for Natural Language Inference

Izumi Haruta, Koji Mineshima, Daisuke Bekki

研究成果: Conference contribution

8 被引用数 (Scopus)

抄録

In formal semantics, there are two well-developed semantic frameworks: event semantics, which treats verbs and adverbial modifiers using the notion of event, and degree semantics, which analyzes adjectives and comparatives using the notion of degree. However, it is not obvious whether these frameworks can be combined to handle cases in which the phenomena in question are interacting with each other. Here, we study this issue by focusing on natural language inference (NLI). We implement a logic-based NLI system that combines event semantics and degree semantics and their interaction with lexical knowledge. We evaluate the system on various NLI datasets containing linguistically challenging problems. The results show that the system achieves high accuracies on these datasets in comparison with previous logic-based systems and deep-learning-based systems. This suggests that the two semantic frameworks can be combined consistently to handle various combinations of linguistic phenomena without compromising the advantage of either framework.

本文言語English
ホスト出版物のタイトルCOLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference
編集者Donia Scott, Nuria Bel, Chengqing Zong
出版社Association for Computational Linguistics (ACL)
ページ1758-1764
ページ数7
ISBN(電子版)9781952148279
出版ステータスPublished - 2020
イベント28th International Conference on Computational Linguistics, COLING 2020 - Virtual, Online, Spain
継続期間: 2020 12月 82020 12月 13

出版物シリーズ

名前COLING 2020 - 28th International Conference on Computational Linguistics, Proceedings of the Conference

Conference

Conference28th International Conference on Computational Linguistics, COLING 2020
国/地域Spain
CityVirtual, Online
Period20/12/820/12/13

ASJC Scopus subject areas

  • コンピュータ サイエンスの応用
  • 計算理論と計算数学
  • 理論的コンピュータサイエンス

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