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How to Design Translation Prompts for ChatGPT: An Empirical Study

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arxiv 2304.02182 v2 pith:T3GRQBIK submitted 2023-04-05 cs.CL

Yuan Gao , Ruili Wang , Feng Hou This is my paper
classification cs.CL
keywords chatgpttranslationpromptstranslationslanguageabilitiescommercialempirical
verification ladder T0 review T1 audit T2 compute T3 formal
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The recently released ChatGPT has demonstrated surprising abilities in natural language understanding and natural language generation. Machine translation relies heavily on the abilities of language understanding and generation. Thus, in this paper, we explore how to assist machine translation with ChatGPT. We adopt several translation prompts on a wide range of translations. Our experimental results show that ChatGPT with designed translation prompts can achieve comparable or better performance over commercial translation systems for high-resource language translations. We further evaluate the translation quality using multiple references, and ChatGPT achieves superior performance compared to commercial systems. We also conduct experiments on domain-specific translations, the final results show that ChatGPT is able to comprehend the provided domain keyword and adjust accordingly to output proper translations. At last, we perform few-shot prompts that show consistent improvement across different base prompts. Our work provides empirical evidence that ChatGPT still has great potential in translations.

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Cited by 2 Pith papers

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