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Variable typing: Assigning meaning to variables in mathematical text

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Stathopoulos, YA 
Rei, M 

Abstract

Information about the meaning of mathematical variables in text is useful in NLP/IR tasks such as symbol disambiguation, topic modeling and mathematical information retrieval (MIR). We introduce variable typing, the task of assigning one mathematical type (multi-word technical terms referring to mathematical concepts) to each variable in a sentence of mathematical text. As part of this work, we also introduce a new annotated data set composed of 33,524 data points extracted from scientific documents published on arXiv. Our intrinsic evaluation demonstrates that our data set is sufficient to successfully train and evaluate current classifiers from three different model architectures. The best performing model is evaluated on an extrinsic task: MIR, by producing a typed formula index. Our results show that the best performing MIR models make use of our typed index, compared to a formula index only containing raw symbols, thereby demonstrating the usefulness of variable typing.

Description

Keywords

Journal Title

NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference

Conference Name

The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Journal ISSN

Volume Title

1

Publisher

Association for Computational Linguistics