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Description
The purpose of this paper is to present the results of a study investigating the effectiveness of AI in the compilation of the Dictionary of Georgian Neologisms, an ongoing project at the Centre for Lexicography and Language Technologies at Ilia State University. The data for the study were selected from a dataset of 1,700 neologisms identified in previous research that developed a semi-automatic method for detecting neologisms in Modern Georgian (Laluashvili & Margalitadze, 2025). Three major categories of Georgian neologisms were selected: (1) borrowings, including direct loans, morphologically adapted loanwords, and loan translations; (2) word formation, with a special focus on internally created Georgian formations; and (3) semantic evolution. The experiments conducted in this study employed ChatGPT 5.2, Gemini 3.0 Thinking, and Grok 4.1 Thinking in combination to mitigate model-specific bias in handling Georgian linguistic material. These models were applied to the primary task of evaluating the effectiveness of LLMs in identifying the meanings of neologisms and generating lexicographic definitions. The findings demonstrate that LLMs can serve as powerful lexicographic tools capable of effectively processing Georgian linguistic data. However, their performance and accuracy are highly dependent on the prompts designed and employed by lexicographers.