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Description
The present research explores the use of large language models (LLMs) in digital lexicography, specifically for translating Italian multiword expressions (MWEs) into English and French.
The study aims to assess the capability of contemporary LLMs in providing accurate and reliable translation equivalents, examples and definitions of Italian MWEs into English and French, while also evaluating the need for expert validation in refining AI-generated lexicographic resources. We seek to develop a digital resource tailored for language learners, offering frequently attested translations.
Methodologically, 120 expressions were evaluated by human experts and compared across two LLMs (Gemini 2.0 Flash and Mistral-Large-2411) using different metrics aimed at assessing including correctness, accuracy and contextual suitability, along with the capacity to produce meaning explanations and usage examples. Results show that English translations received higher expert ratings than French ones, with high correlation between human and AI evaluations in the case of English, and significantly lower agreement in the case of French translations. The findings indicate that LLMs provide generally reliable translations, though expert oversight remains crucial.
