AI-assisted Translation of Qatari Idiomatic Expressions: The Case of Al Jar

Abstract

Translating idiomatic expressions offers a way to engage with and explore other cultures. This study investigates the potential of the large language model ChatGPT-5.2 to translate Qatari idiomatic expressions into English, focusing on the first two episodes of the Qatari Arabic television series Al-Jar (2019). The study identifies the strategies and procedures utilized by ChatGPT-5.2 in rendering Qatari idiomatic expressions. The study employs a methodological approach that involves collecting, analyzing, and interpreting data in light of relevant academic literature. Vinay and Darbelnet’s (1958/ 1995) translation strategies serve as the theoretical framework for the analysis. The findings reveal that ChatGPT-5.2 relies more heavily on oblique translation procedures, such as transposition, modulation, and equivalence, than on direct translation procedures. Oblique translation strategy accounts for 68.97% of the instances, while the direct translation strategy, represented here by literal translation, accounts for 31.03%. This study contributes to translation studies by identifying the role of artificial intelligence in translating idiomatic expressions from an underrepresented dialect, such as Qatari Arabic. Keywords: Artificial Intelligence, Idiomatic Expressions, Qatari Culture, Qatari Arabic, English.

Date of Award	2026
Original language	American English
Awarding Institution	HBKU College of Humanities and Social Science