  This paper explores the influence of integrating the purpose of the
translation and the target audience into prompts on the quality of translations
produced by ChatGPT. Drawing on previous translation studies, industry
practices, and ISO standards, the research underscores the significance of the
pre-production phase in the translation process. The study reveals that the
inclusion of suitable prompts in large-scale language models like ChatGPT can
yield flexible translations, a feat yet to be realized by conventional Machine
Translation (MT). The research scrutinizes the changes in translation quality
when prompts are used to generate translations that meet specific conditions.
The evaluation is conducted from a practicing translator's viewpoint, both
subjectively and qualitatively, supplemented by the use of OpenAI's word
embedding API for cosine similarity calculations. The findings suggest that the
integration of the purpose and target audience into prompts can indeed modify
the generated translations, generally enhancing the translation quality by
industry standards. The study also demonstrates the practical application of
the "good translation" concept, particularly in the context of marketing
documents and culturally dependent idioms.
