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|Booktitle=Conference on Digital Curation Technologies (Qurator) | |Booktitle=Conference on Digital Curation Technologies (Qurator) | ||
|Publisher=http://ceur-ws.org/ | |Publisher=http://ceur-ws.org/ | ||
| + | |Editor=http://ceur-ws.org/ | ||
| + | |Series=Conference on Digital Curation Technologies (Qurator) | ||
| + | |Number=3 | ||
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{{Publikation Details | {{Publikation Details | ||
|Abstract=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. | |Abstract=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. | ||
| + | |Download=paper7.pdf | ||
| + | |Link=http://ceur-ws.org/Vol-3234/paper7.pdf | ||
|Forschungsgruppe=Information Service Engineering | |Forschungsgruppe=Information Service Engineering | ||
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Aktuelle Version vom 31. Oktober 2022, 09:46 Uhr
Knowledge Extraction for Art History: the Case of Vasari’s The Lives of The Artists (1568)
Knowledge Extraction for Art History: the Case of Vasari’s The Lives of The Artists (1568)
Published: 2022
Herausgeber: http://ceur-ws.org/
Buchtitel: Conference on Digital Curation Technologies (Qurator)
Nummer: 3
Reihe: Conference on Digital Curation Technologies (Qurator)
Verlag: http://ceur-ws.org/
Referierte Veröffentlichung
BibTeX
Kurzfassung
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.
Download: Media:paper7.pdf
Weitere Informationen unter: Link
Information Service Engineering