Higher-order logical inference with compositional semantics

Koji Mineshima, Pascual Martínez-Gómez, Yusuke Miyao, Daisuke Bekki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

40 Citations (Scopus)


We present a higher-order inference system based on a formal compositional semantics and the wide-coverage CCG parser. We develop an improved method to bridge between the parser and semantic composition. The system is evaluated on the FraCaS test suite. In contrast to the widely held view that higher-order logic is unsuitable for efficient logical inferences, the results show that a system based on a reasonably-sized semantic lexicon and a manageable number of non-first-order axioms enables efficient logical inferences, including those concerned with generalized quantifiers and intensional operators, and outperforms the state-of-the-art firstorder inference system.

Original languageEnglish
Title of host publicationConference Proceedings - EMNLP 2015
Subtitle of host publicationConference on Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Number of pages7
ISBN (Electronic)9781941643327
Publication statusPublished - 2015
Externally publishedYes
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal
Duration: 2015 Sept 172015 Sept 21

Publication series

NameConference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing


ConferenceConference on Empirical Methods in Natural Language Processing, EMNLP 2015

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems


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