Year: 2026
Type: article
Abstract: We aim to examine the extent to which Large Language Models (LLMs), specifically ChatGPT-5 can translate English syntax terminology into Arabic. We collected 44 terms from generative syntax previous works, including books and journal articles, as well as from our experience in the field. These terms were translated by humans, and then by ChatGPT-5. We then analyzed and compared both translations. We used the analytical and comparative approach amalgamated with micro approach in our analysis. Findings unveil that ChatGPT still cannot translate the core syntax properties embedded in the terms under study involving several syntactic (and semantic) challenges: only 25% of ChatGPT translations were accurate, while 38.6% were inaccurate, and 36.4.% were partially correct, which we consider appropriate. Based on these findings, a set of actionable strategies were proposed, the most notable of which is finetuning LLMs on syntactic terminology in both languages to better LLMs’ working mechanism for accurate or at least appropriate translation.
Source: Discover Artificial Intelligence
Authors: Mohammed Q. Shormani, Yehia A. AlSohbani
Institutions: Ibb University, Arab Open University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,590
OpenAlex ID: W7139911631