@inproceedings{abzianidze-2017-langpro,
title = "{L}ang{P}ro: Natural Language Theorem Prover",
author = "Abzianidze, Lasha",
editor = "Specia, Lucia and
Post, Matt and
Paul, Michael",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
month = sep,
year = "2017",
address = "Copenhagen, Denmark",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D17-2020",
doi = "10.18653/v1/D17-2020",
pages = "115--120",
abstract = "LangPro is an automated theorem prover for natural language. Given a set of premises and a hypothesis, it is able to prove semantic relations between them. The prover is based on a version of analytic tableau method specially designed for natural logic. The proof procedure operates on logical forms that preserve linguistic expressions to a large extent. {\%}This property makes the logical forms easily obtainable from syntactic trees. {\%}, in particular, Combinatory Categorial Grammar derivation trees. The nature of proofs is deductive and transparent. On the FraCaS and SICK textual entailment datasets, the prover achieves high results comparable to state-of-the-art.",
}
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<abstract>LangPro is an automated theorem prover for natural language. Given a set of premises and a hypothesis, it is able to prove semantic relations between them. The prover is based on a version of analytic tableau method specially designed for natural logic. The proof procedure operates on logical forms that preserve linguistic expressions to a large extent. %This property makes the logical forms easily obtainable from syntactic trees. %, in particular, Combinatory Categorial Grammar derivation trees. The nature of proofs is deductive and transparent. On the FraCaS and SICK textual entailment datasets, the prover achieves high results comparable to state-of-the-art.</abstract>
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%0 Conference Proceedings
%T LangPro: Natural Language Theorem Prover
%A Abzianidze, Lasha
%Y Specia, Lucia
%Y Post, Matt
%Y Paul, Michael
%S Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F abzianidze-2017-langpro
%X LangPro is an automated theorem prover for natural language. Given a set of premises and a hypothesis, it is able to prove semantic relations between them. The prover is based on a version of analytic tableau method specially designed for natural logic. The proof procedure operates on logical forms that preserve linguistic expressions to a large extent. %This property makes the logical forms easily obtainable from syntactic trees. %, in particular, Combinatory Categorial Grammar derivation trees. The nature of proofs is deductive and transparent. On the FraCaS and SICK textual entailment datasets, the prover achieves high results comparable to state-of-the-art.
%R 10.18653/v1/D17-2020
%U https://aclanthology.org/D17-2020
%U https://doi.org/10.18653/v1/D17-2020
%P 115-120
Markdown (Informal)
[LangPro: Natural Language Theorem Prover](https://aclanthology.org/D17-2020) (Abzianidze, EMNLP 2017)
ACL
- Lasha Abzianidze. 2017. LangPro: Natural Language Theorem Prover. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pages 115–120, Copenhagen, Denmark. Association for Computational Linguistics.