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Extracting Mathematical Concepts from Text

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arxiv 2208.13830 v1 pith:33VP4RSE submitted 2022-08-29 cs.CL

Jacob Collard , Valeria de Paiva , Brendan Fong , Eswaran Subrahmanian This is my paper · ORCID
classification cs.CL
keywords mathematicalcategorycorpusdifferentextractingsentencessmalltext
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We investigate different systems for extracting mathematical entities from English texts in the mathematical field of category theory as a first step for constructing a mathematical knowledge graph. We consider four different term extractors and compare their results. This small experiment showcases some of the issues with the construction and evaluation of terms extracted from noisy domain text. We also make available two open corpora in research mathematics, in particular in category theory: a small corpus of 755 abstracts from the journal TAC (3188 sentences), and a larger corpus from the nLab community wiki (15,000 sentences).

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  1. Math Natural Language Inference: this should be easy!

    cs.CL 2025-07 conditional novelty 6.0 of 10

    A new Math NLI corpus from category theory abstracts plus a ten-model evaluation shows LLM unanimous votes approach human labels (88%) but individual LLMs still make basic math reasoning errors.

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