Zusammenfassung
Knowledge Extraction (KE) techniques are used to convert unstructured information present in texts to
Knowledge Graphs (KGs) which can be queried and explored. Despite their potential for cultural heritage
domains, such as Art History, these techniques often encounter limitations if applied to domain-specific
data. In this paper we present the main challenges that KE has to face on art-historical texts, by using as
case study Giorgio Vasari’s The Lives of The Artists. This paper discusses the following NLP tasks for
art-historical texts, namely entity recognition and linking, coreference resolution, time extraction, motif
extraction and artwork extraction. Several strategies to annotate art-historical data for these tasks and
evaluate NLP models are also proposed.
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