@inproceedings{ferreira-freitas-2020-natural,
title = "Natural Language Premise Selection: Finding Supporting Statements for Mathematical Text",
author = "Ferreira, Deborah and
Freitas, Andr{\'e}",
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.266",
pages = "2175--2182",
abstract = "Mathematical text is written using a combination of words and mathematical expressions. This combination, along with a specific way of structuring sentences makes it challenging for state-of-art NLP tools to understand and reason on top of mathematical discourse. In this work, we propose a new NLP task, the natural premise selection, which is used to retrieve supporting definitions and supporting propositions that are useful for generating an informal mathematical proof for a particular statement. We also make available a dataset, NL-PS, which can be used to evaluate different approaches for the natural premise selection task. Using different baselines, we demonstrate the underlying interpretation challenges associated with the task.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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<abstract>Mathematical text is written using a combination of words and mathematical expressions. This combination, along with a specific way of structuring sentences makes it challenging for state-of-art NLP tools to understand and reason on top of mathematical discourse. In this work, we propose a new NLP task, the natural premise selection, which is used to retrieve supporting definitions and supporting propositions that are useful for generating an informal mathematical proof for a particular statement. We also make available a dataset, NL-PS, which can be used to evaluate different approaches for the natural premise selection task. Using different baselines, we demonstrate the underlying interpretation challenges associated with the task.</abstract>
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%0 Conference Proceedings
%T Natural Language Premise Selection: Finding Supporting Statements for Mathematical Text
%A Ferreira, Deborah
%A Freitas, André
%S Proceedings of the 12th Language Resources and Evaluation Conference
%D 2020
%8 may
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F ferreira-freitas-2020-natural
%X Mathematical text is written using a combination of words and mathematical expressions. This combination, along with a specific way of structuring sentences makes it challenging for state-of-art NLP tools to understand and reason on top of mathematical discourse. In this work, we propose a new NLP task, the natural premise selection, which is used to retrieve supporting definitions and supporting propositions that are useful for generating an informal mathematical proof for a particular statement. We also make available a dataset, NL-PS, which can be used to evaluate different approaches for the natural premise selection task. Using different baselines, we demonstrate the underlying interpretation challenges associated with the task.
%U https://aclanthology.org/2020.lrec-1.266
%P 2175-2182
Markdown (Informal)
[Natural Language Premise Selection: Finding Supporting Statements for Mathematical Text](https://aclanthology.org/2020.lrec-1.266) (Ferreira & Freitas, LREC 2020)
ACL