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Translation and Foreign Language Learning

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ArticleTranslation Theories and Skills http://dx.doi.org/10.26855/tfll.2026.02.007

Evaluating ChatGPT-assisted Translation of Traditional Chinese Medicine Terminology: Performance, Limitations, and Implications for Terminological Standardization

Hongli Feng

School of Foreign Languages, Ningxia Medical University, Yinchuan 750004, Ningxia, China.

*Corresponding author: Hongli Feng

Published: February 28, 2026

Abstract

The difficulty of translating TCM terminology cannot be reduced to differences between Chinese and English vocabulary. Many terms arise from a medical tradition whose theoretical assumptions and cultural associations do not have straightforward English counterparts. Although LLMs are now common in translation-related work, how reliably they handle this conceptually dense medical vocabulary is still open to question. This study focuses on ChatGPT's handling of core diagnostic terms in TCM and asks whether its output has any practical value for terminological standardization. The corpus contains 295 terms taken from three authoritative terminology resources: the WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region (WHO/WPRO, 2007), the International Standard Chinese-English Basic Nomenclature of Chinese Medicine (ISN), published under the auspices of the World Federation of Chinese Medicine Societies (WFCMS), and the International Standardization of English Translation of Basic Terminology in Chinese Medicine (ISBT). Cross-source comparison yielded 147 terms with identical English renderings across the reference resources and 148 terms represented by 322 distinct English variants recorded across the three reference resources. Fifteen bilingual experts then evaluated the ChatGPT-generated translations. Quantitative results were considered together with expert judgments on communicative adequacy, linguis-tic accuracy, cultural representation, and alignment with terminology standards. Terms with established English equivalents were generally handled more successfully than those closely tied to TCM theory or cultural interpretation. The outputs were often readable and semantically usable, yet some weakened distinctions that remain important within the source knowledge system. In practice, the model is better suited to proposing candidates and facilitating comparison than to determining a final standard form. That decision continues to require spe-cialist review. LLM assistance is therefore treated here as one component of terminological work, not as a substitute for expert judgment.

Keyword

Traditional Chinese Medicine; Terminology Translation; Large Language Models; ChatGPT; Terminological Standardization

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Copyright

© 2026 by the author(s).
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives (CC BY-NC-ND) license, which permits non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited and is not modified or adapted.
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How to cite this paper

Evaluating ChatGPT-assisted Translation of Traditional Chinese Medicine Terminology: Performance, Limitations, and Implications for Terminological Standardization

How to cite this paper: Hongli Feng. (2026). Evaluating ChatGPT-assisted Translation of Traditional Chinese Medicine Terminology: Performance, Limitations, and Implications for Terminological Standardization. Translation and Foreign Language Learning2(2), 209-218.

DOI: http://dx.doi.org/10.26855/tfll.2026.02.007