ATR4CH is a replicable five-step methodology for LLM-based knowledge extraction from cultural heritage documents that combines annotation models and ontological frameworks, achieving F1 scores of 0.96-0.99 for metadata, 0.7-0.8 for entities, and 0.62 G-EVAL for discourse on Wikipedia articles about
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Knowledge Graphs Generation from Cultural Heritage Texts: Combining LLMs and Ontological Engineering for Scholarly Debates
ATR4CH is a replicable five-step methodology for LLM-based knowledge extraction from cultural heritage documents that combines annotation models and ontological frameworks, achieving F1 scores of 0.96-0.99 for metadata, 0.7-0.8 for entities, and 0.62 G-EVAL for discourse on Wikipedia articles about