A Tableau Prover for Natural Logic and Language

Lasha Abzianidze

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

17 Citations (Scopus)
204 Downloads (Pure)

Abstract

Modeling the entailment relation over sentences is one of the generic problems of natural language understanding. In order to account for this problem, we design a theorem prover for Natural Logic, a logic whose terms resemble natural language expressions. The prover is based on an analytic tableau method and employs syntactically and semantically motivated schematic rules. Pairing the prover with a preprocessor, which generates formulas of Natural Logic from linguistic expressions, results in a proof system for natural language. It is shown that the system obtains a comparable accuracy (81%) on the unseen SICK data while achieving the state-of-the-art precision (98%).
Original languageEnglish
Title of host publicationProceedings of the 2015 Conference on Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Number of pages11
Publication statusPublished - 2015

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