Conference article

A Wide-Coverage Symbolic Natural Language Inference System

Jean-Philippe Bernardy
Department of Philosophy, Linguistics and Theory of Science, University of Gothenburg, Sweden

Stergios Chatzikyriakidis
Department of Philosophy, Linguistics and Theory of Science, University of Gothenburg, Sweden

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Published in: Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa), September 30 - October 2, Turku, Finland

Linköping Electronic Conference Proceedings 167:31, p. 298--303

NEALT Proceedings Series 42:31, p. 298--303

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Published: 2019-10-02

ISBN: 978-91-7929-995-8

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

We present a system for Natural Language Inference which uses a dynamic semantics converter from abstract syntax trees to Coq types. It combines the fine-grainedness of a dynamic semantics system with the powerfulness of a state-of-the-art proof assistant, like Coq. We evaluate the system on all sections of the FraCaS test suite, excluding section 6. This is the first system that does a complete run on the anaphora and ellipsis sections of the FraCaS. It has a better overall accuracy than any previous system.

Keywords

Natural Language Inference Type Theoretical Semantics Monads Dynamic Semantics

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