Teaching Provenance to AI: An Annotation Scheme for Museum Data

Publikation: Beiträge in SammelwerkenAufsätze in SammelwerkenForschung

Authors

Our paper addresses how artificial intelligence technologies can transform museum records of provenance into structured and machine-readable data, which is the first critical step in undertaking a large-scale cross-institutional analysis of object history. Drawing on research on natural language processing (NLP), we have identified sentence boundary disambiguation and span categorization as highly effective techniques for extracting and structuring information from provenance texts. Our paper focuses on a provenance-specific annotation scheme that enables us to retain historical nuances when constructing provenance linked open data (PLOD)
OriginalspracheEnglisch
TitelAI in Museums : Reflections, Perspectives and Applications
HerausgeberSonja Thiel, Johannes Bernhardt
Anzahl der Seiten10
ErscheinungsortBielefeld
Verlagtranscript Verlag
Erscheinungsdatum27.12.2023
Seiten163-172
ISBN (Print)978-3-8376-6710-3
ISBN (elektronisch)978-3-8394-6710-7
DOIs
PublikationsstatusErschienen - 27.12.2023

Bibliographische Notiz

Publisher Copyright:
© Sonja Thiel, Johannes C. Bernhardt (eds.). All rights reserved.

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