Using Named Entity Recognition to Enhance Access to a Museum Catalog

Digital technologies have been successfully applied in cultural heritage projects that support the digitization of cultural objects, metadata creation, metadata maintenance, and the creation of digital infrastructure for cultural heritage research, to name a few. When we discuss archival digital textual content, some of the most immediate tasks relate to automatic metadata generation, searchability, and preservation, all of which can be helped by services for automatic semantic annotation.

In this blogpost we discuss the applicability of such services for automatic extraction of person names and locations from Oral History Transcripts provided by the United States Holocaust Memorial Museum (USHMM). The algorithms for automatic information extraction can work with comparatively high accuracy when applied in a close domain, they are especially helpful and could greatly speed up the human work when large volumes of data are to be processed.

Learning outcomes

After viewing this training resource, users will be able to:

• Understand how DH tools can help to automatically extract specific information from big data sets
• Explore named-entity recognition in oral history catalogs