Machine Translation Constraints in Lexical Conversion in Classical Chinese and Implications for China’s English Teaching
DOI:
https://doi.org/10.54097/2past304Keywords:
Classical Chinese Lexical Conversion, Cognitive-linguistic Mechanisms, Machine Translation Constraints, English Teaching Transformation, Human-Machine CollaborationAbstract
The study focuses on the lexical conversion in Classical Chinese and explors its semantic generalization, syntactic dependency, and cognitive mechanisms (metonymic and metaphoric mapping, and prominence principle). Sixteen samples from classical texts were selected, and their translations by three machine translation (MT) engines, DeepSeek, Doubao and Youdao, were tested against authoritative versions. Results show that MT exhibits gradient differences in accuracy when identifying lexical conversions, and fails in semantic reconstruction and cultural preservation. These limitations stem from MT’s reliance on distributional statistics rather than human-like cognitive frames. The findings highlight the irreplaceability of core human capacities (contextual sensitivity, cultural metaphorical competence) and advocate transforming China’s English teaching into a paradigm that combines language, digital, and humanity elements. This paradigm aims to foster the collaboration between human and machine, to cultivate students’ higher-order thinking and humanistic values, and to provide theoretical and practical references for English teaching transformation in China in the digital age.
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[1] Deng, R. H. A Comparative Analysis of English Word-formation by Conversion and English-Chinese Lexical Conversion in Translation [J]. English Square (Academic Research), 2014, (4), 33–34. https://doi. org/10. 16723/j. cnki. yygc. 2014.04.024
[2] [2]Zou, L. Z. and Bai, C. On the Essential Differences Between Flexible Word-Class Use in Classical and Modern Chinese [J]. Studies in Language and Linguistics, 2009, 29(02):37-42.
[3] Wang, K. Z. Flexible Use of Word Classes in Classical Chinese) [M]. Changsha, China: Hunan People's Publishing House, 1989.
[4] Zeng, Y. M. The Impact of Cognitive Schemas on the Reception and Interpretation of Foreign Literary Works: A Cross-Cultural Exploration [J]. Lecture Notes on Language and Literature,2025, 8(1).
[5] He, M. Y. and Kun, Y. Constructionalization of English Caused-motion Constructions and Its Consequences [J]. Foreign Languages and Their Teaching, 2013, (3), 20-24.
[6] Wang, Y. The principle of prominence and research & Teaching Morphology: A New View Based on Embodied-bognitive Linguistic [J]. Language Education, 2022, 10(2), 54–63.
[7] Alves, F. and Jakobsen, A. L. The Routledge Handbook of Translation and Cognition (Routledge Handbooks in Translation and Interpreting Studies) [M]. 2023.
[8] Zhan, C. T., Ding, L., Shen, L., Zhan, Y. B., Yang, X. H. and Liu, W. F. Building Accurate Translation-tailored Large Language Models with Language-aware Instruction Tuning [J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26 (08), 1341-1356.
[9] Lakoff, G., & Johnson, M. Metaphors We Live by [M]. University of Chicago Press, 1980.
[10] Richards, J. C., & Rodgers, T. S. Approaches and methods in language teaching (2nd ed.) [M]. Cambridge University Press, 2001.
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