Keyword-based Natural Language Premise Selection for an Automatic Mathematical Statement Proving

Doratossadat Dastgheib, Ehsaneddin Asgari*

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)124-126
Number of pages3
JournalProceedings - International Conference on Computational Linguistics, COLING
Volume29
Issue number16
Publication statusPublished - 2022
Externally publishedYes
Event16th Workshop on Graph-Based Methods for Natural Language Processing, TextGraphs 2022, in conjunction with the 29th International Conference on Computational Linguistics, COLING 2022 - Gyeongju, Korea, Republic of
Duration: 12 Oct 202217 Oct 2022

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