A Tableau Prover for Natural Logic and Language

Lasha Abzianidze

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

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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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Abzianidze, L. (2015). A Tableau Prover for Natural Logic and Language. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing Association for Computational Linguistics (ACL).
Abzianidze, Lasha. / A Tableau Prover for Natural Logic and Language. Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), 2015.
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Abzianidze, L 2015, A Tableau Prover for Natural Logic and Language. in Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL).

A Tableau Prover for Natural Logic and Language. / Abzianidze, Lasha.

Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL), 2015.

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

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AB - 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%).

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Abzianidze L. A Tableau Prover for Natural Logic and Language. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics (ACL). 2015