The Translation of Body Part Idioms Using Chatgpt: a Comparative Analysis with Official Dictionaries
TL;DR
The research confirms that ChatGPT successfully identifies functional equivalents in the Serbian language, often prioritising the naturalness of expressions over literal translation, often prioritising the naturalness of expressions over literal translation.
Abstract
: In the era of digital transformation and the rapid advancement of generative artificial intelligence, the translation of idiomatic expressions has become a crucial benchmark for evaluating the cognitive and linguistic capabilities of Large Language Models (LLMs). This paper presents a detailed analysis of research conducted on a corpus of ten English body part idioms taken from the Pioneer B2 textbook used at Singidunum University. The aim of the research was to compare translations generated by the ChatGPT model with solutions from official idiomatic dictionaries, utilising Pavol Kvetko's classification and Mona Baker’s equivalence strategies as the theoretical framework. The analysis encompasses idioms of varying degrees of transparency, ranging from completely opaque to semi-idioms. The study results indicate a 90% accuracy rate in conveying meaning, alongside an unexpectedly high 60% correspondence of keywords in both languages. The research confirms that ChatGPT successfully identifies functional equivalents in the Serbian language, often prioritising the naturalness of expressions over literal translation. This work contributes to the discussion on the role of AI tools as assistants in translation and education, emphasising that while AI shows exceptional dexterity in mapping conceptual fields, human oversight remains essential for the final validation of stylistic nuances. The findings have significant applications for international scientific research, particularly in the domain of applying information technology in foreign language teaching.