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        <title>Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving</title>
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    <abstract>Extraction of supportive premises for a mathematical problem can contribute to profound success in improving automatic reasoning systems. One bottleneck in automated theorem proving is the lack of a proper semantic information retrieval system for mathematical texts. In this paper, we show the effect of keyword extraction in the natural language premise selection (NLPS) shared task proposed in TextGraph-16 that seeks to select the most relevant sentences supporting a given mathematical statement.</abstract>
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%0 Conference Proceedings
%T Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving
%A Dastgheib, Doratossadat
%A Asgari, Ehsaneddin
%S Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F dastgheib-asgari-2022-keyword
%X Extraction of supportive premises for a mathematical problem can contribute to profound success in improving automatic reasoning systems. One bottleneck in automated theorem proving is the lack of a proper semantic information retrieval system for mathematical texts. In this paper, we show the effect of keyword extraction in the natural language premise selection (NLPS) shared task proposed in TextGraph-16 that seeks to select the most relevant sentences supporting a given mathematical statement.
%U https://aclanthology.org/2022.textgraphs-1.14
%P 124-126

Markdown (Informal)

[Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving](https://aclanthology.org/2022.textgraphs-1.14) (Dastgheib & Asgari, TextGraphs 2022)

• Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving (Dastgheib & Asgari, TextGraphs 2022)

ACL

• Doratossadat Dastgheib and Ehsaneddin Asgari. 2022. Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving. In Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing, pages 124–126, Gyeongju, Republic of Korea. Association for Computational Linguistics.