A Dataset of Ancient Chinese Math Word Problems and an Application for Research in Historic Mathematics

Keßler F (2025)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2025

Pages Range: 59-70

Conference Proceedings Title: Proceedings of the Second Workshop on Ancient Language Processing

Event location: Albuquerque

URI: https://aclanthology.org/2025.alp-1.8/

Open Access Link: https://aclanthology.org/2025.alp-1.8/

Abstract

Solving math word problems, i.e. mathemati-cal problems stated in natural language, has re-ceived much attention in the Artificial Intelli-gence (AI) community over the last years. Unsurprisingly, research has focused on problems stated in contemporary languages. In contrast to this, in this article, we introduce a dataset of math word problems that is extracted from ancient Chinese mathematical texts. The dataset is made available. We report a baseline per-formance for GPT-4o solving the problems in the dataset using a Program-of-Thought paradigm that translates the mathematical pro-cedures in the original texts into Python code, giving acceptable performance but showing that the model often struggles with understanding the pre-modern language. Finally, we describe how the generated code can be used for research into the history of mathematics, by offering a way to search the texts by abstract op-erations instead of specific lexemes.

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How to cite

APA:

Keßler, F. (2025). A Dataset of Ancient Chinese Math Word Problems and an Application for Research in Historic Mathematics. In Adam Anderson, Shai Gordin, Bin Li, Yudong Liu, Marco C. Passarotti, Rachele Sprugnoli (Eds.), Proceedings of the Second Workshop on Ancient Language Processing (pp. 59-70). Albuquerque.

MLA:

Keßler, Florian. "A Dataset of Ancient Chinese Math Word Problems and an Application for Research in Historic Mathematics." Proceedings of the Second Workshop on Ancient Language Processing, Albuquerque Ed. Adam Anderson, Shai Gordin, Bin Li, Yudong Liu, Marco C. Passarotti, Rachele Sprugnoli, 2025. 59-70.

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