Handling multiword expressions in causality estimation

Shota Sasaki, Sho Takase, Naoya Inoue, Naoaki Okazaki, Kentaro Inui

Research output: Contribution to conferencePaperpeer-review

15 Citations (Scopus)


Previous studies on causality estimation mainly aquire causal event pairs from a large corpus based on lexico-syntactic patterns and coreference relations, and estimate causality by a statistical method. However, most of the previous studies assume event pairs can be represented by a pair of single words, therefore they cannot estimate multiword causality correctly (e.g.“tired”-“give up”) . In this paper, we create a list of multiword expressions and extend an existing method. Our evaluation demonstrates that the proper treatment of multiword expression events is effective and the proposed method outperforms the state-of-the-art causality estimation model.

Original languageEnglish
Publication statusPublished - 2017
Event12th International Conference on Computational Semantics, IWCS 2017 - Montpellier, France
Duration: 2017 Sept 192017 Sept 22


Conference12th International Conference on Computational Semantics, IWCS 2017

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems


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