The study explores the potential of LLMs in interpreting and translating Bessarabian idioms. The central problem addressed is the semantic non-compositionality of idiomatic expressions, which poses a significant challenge for Natural Language Processing since their figurative meaning cannot be derived from literal components. As part of the CI ARiA project, 1000 proverbs were digitized, using a corpus of 400 of them to evaluate the performance of 10 AI models (such as ChatGPT, Gemini, Grok). The methodology is multi-algorithmic, combining textual distance metrics (Levenshtein, Jaccard) with semantic similarity analysis via Sentence Transformers. The results indicate that while models demonstrate a solid capacity to grasp metaphorical meanings, significant differences exist regarding consistency and explanatory style.
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Inga Titchiev
Olesea Caftanatov
Crinu Dimitriu
SHILAP Revista de lepidopterología
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Titchiev et al. (Thu,) studied this question.
www.synapsesocial.com/papers/6994055d4e9c9e835dfd62aa — DOI: https://doi.org/10.36120/2587-3644.v20i2.116-127