Exploring Entity Recognition and Disambiguation for Cultural Heritage Collections Seth van Hooland ⋄ ∗ , Max De Wilde ⋄ , Ruben Verborgh † , Thomas Steiner ‡ and Rik Van de Walle † ⋄ Université libre de Bruxelles (ULB) Information and Communication Science Department Avenue F. D. Roosevelt, 50 – CP 123 B-1050 Brussels, Belgium {svhoolan,madewild}@ulb.ac.be † iMinds – Multimedia Lab – Ghent University Gaston Crommenlaan 8 bus 201 B-9050 Ledeberg-Ghent, Belgium {ruben.verborgh,rik.vandewalle}@ugent.be ‡ Universitat Politècnica de Catalunya – Department LSI Carrer Jordi Girona, 29 E-08034 Barcelona, Spain tsteiner@lsi.upc.edu Abstract Unstructured metadata fields such as ‘description’ offer tremendous value for users to understand cultural heritage objects. However, this type of narrative information is of little direct use within a machine-readable context due to its unstructured nature. This paper explores the possibilities and limitations of Named-Entity Recognition (NER) and Term Extraction (TE) to mine such unstructured metadata for meaningful concepts. These concepts can be used to leverage otherwise limited searching and browsing operations, but they can also play an important role to foster Digital Humanities research. In order to catalyze experimentation with NER and TE, the paper proposes an evaluation of the performance of three third-party entity extraction services through a comprehensive case study, based on the descriptive fields of the Smithsonian Cooper-Hewitt National Design Museum in New York. In order to cover both NER and TE, we first offer a quantitative analysis of named-entities retrieved by the services in terms of precision and recall compared to a manually annotated gold-standard corpus, then complement this approach with a more qualitative assessment of relevant terms extracted. Based on the outcomes of this double analysis, the conclusions present the added value of entity extraction services, but also indicate the dangers of uncritically using NER and/or TE, and by extension Linked Data principles, within the Digital Humanities. All metadata and tools used within the paper are freely available, making it possible for researchers and practitioners to repeat the methodology. By doing so, the paper offers a significant contribution towards understanding the value of entity recognition and disambiguation for the Digital Humanities. This is the author version of an article submitted for publication. Please cite as: van Hooland, S., De Wilde, M., Verborgh, R., Steiner T., and Van de Walle, R., Exploring Entity Recognition and Disambiguation for Cultural Heritage Collections? In: Literary and Linguistics Computing, 2014. ∗ Corresponding author 1