# Linguistically Informed ChatGPT Prompts to Enhance Japanese-Chinese Machine Translation: A Case Study on Attributive Clauses

arXiv: https://arxiv.org/abs/2303.15587 · HTML: https://mlsanity.com/paper/2303.15587/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 25 references that are in the map.
- First posted on arXiv 27 Mar 2023.

## Builds on (most cited first, 6 of 6)

- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014)
- [Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation](https://mlsanity.com/paper/1609.08144/) (2016)
- [Six Challenges for Neural Machine Translation](https://mlsanity.com/paper/1706.03872/) (2017)
- [A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarios](https://mlsanity.com/paper/2010.12309/) (2020)

## Built on by (most cited first, 8 of 8)

- [Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMs](https://mlsanity.com/paper/2402.03927/) (2024)
- [TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties](https://mlsanity.com/paper/2308.03051/) (2023)
- [Prompting ChatGPT for Translation: A Comparative Analysis of Translation Brief and Persona Prompts](https://mlsanity.com/paper/2403.00127/) (2024)
- [Optimizing Machine Translation through Prompt Engineering: An Investigation into ChatGPT's Customizability](https://mlsanity.com/paper/2308.01391/) (2023)
- [Gender Bias in Machine Translation and The Era of Large Language Models](https://mlsanity.com/paper/2401.10016/) (2024)
- [To what extent is ChatGPT useful for language teacher lesson plan creation?](https://mlsanity.com/paper/2407.09974/) (2024)
- [Assessing the Code Clone Detection Capability of Large Language Models](https://mlsanity.com/paper/2407.02402/) (2024)
- [The Role of Prompt Language and Translation-Theory-Driven Prompts in Large Language Models: A Case Study on Spanish-Chinese Journalistic Translation](https://mlsanity.com/paper/2607.03160/) (2026)

## Abstract (arXiv)

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%.