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Utilizing Translation Memory-based Prompting to Enhance GPT-4’s Translation Performance: A Case Study

by JINGJING FENG (Author)
20 Pages
Open Access
Journal: Journal of Translation Studies Volume 5 Issue 1 Publication Year 2025 pp. 57 - 76

Summary

This study investigates the integration of Translation Memory (TM) with GPT-4 to enhance its translation capabilities. It employs a TM-based prompting strategy that draws on the 2023 Chinese Government Work Report to inform the translation of the 2024 version of the Report. Methodologically, the research compared TM-based prompts with non-TM-based prompts and official translations, evaluating translation quality through Bilingual Evaluation Understudy (BLEU) scores and human assessments. Contrary to expectations, the results indicate that TM-based prompting did not significantly improve the accuracy or contextual relevance of translations, compared with the baseline methods. This suggests that, while TM can provide context, it may not always translate with higher quality, without further prompting or optimizations.

Details

Pages
20
DOI
10.3726/JTS012025.3
Publication date
2025 (August)
Keywords
utilizing translation memory-based prompting enhance gpt-4’s performance case study
Product Safety
Peter Lang Group AG

Biographical notes

JINGJING FENG (Author)

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Title: Utilizing Translation Memory-based Prompting to Enhance GPT-4’s Translation Performance: A Case Study