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> Natural Language Processing (NLP), along with Large Language Models (LLMs), holds significant potential in the domain of literature, leveraging its computational capabilities to analyze and comprehend human language. These techniques prove to be particularly useful in a specific part of Greek literature called Anacreaontea — a collection of poems emulating the style of the 6th-century BCE Greek poet Anacreon. This paper presents an LLM approach to the automatic classification of Anacreaontea poems in their respective topoi. Our methodology explores two well-established autoregressive language models (LLama 2 and Mistral) and investigates the usage of contextual prompting in this scenario. We also provide an annotated corpus with 21 fragments of the Anacreontea with topos for Greek and Portuguese text. |
