In the field of Japanese-Chinese translation linguistics, the issue of correctly translating attributive clauses has persistently proven to be challenging. Present-day machine translation tools often fail to accurately translate attributive clauses from Japanese to Chinese. In light of this, this paper investigates the linguistic problem underlying such difficulties, namely how does the semantic role of the modified noun affect the selection of translation patterns for attributive clauses, from a linguistic perspective. To ad-dress these difficulties, a pre-edit scheme is proposed, which aims to enhance the accuracy of translation. Furthermore, we propose a novel two-step prompt strategy, which combines this pre-edit scheme with ChatGPT, currently the most widely used large language model. This prompt strategy is capable of optimizing translation input in zero-shot scenarios and has been demonstrated to improve the average translation accuracy score by over 35%.

翻译：在日汉翻译语言学领域，定语从句的正确翻译问题一直具有挑战性。当前的机器翻译工具往往无法准确地将日语定语从句翻译为中文。基于此，本文从语言学视角探讨了导致此类困难的语言学问题，即修饰名词的语义角色如何影响定语从句翻译模式的选择。为解决这些困难，本文提出了一种旨在提升翻译准确性的预编辑方案。此外，我们提出了一种新颖的两步提示策略，将该预编辑方案与当前广泛使用的大语言模型ChatGPT相结合。该提示策略能够在零样本场景下优化翻译输入，并被证明可将平均翻译准确率提升超过35%。