id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_peutawgvezbthoqdwyuujshbfm	S. van Hooland	Exploring entity recognition and disambiguation for cultural heritage collections	2013	18	.pdf	application/pdf	10646	764	53	limitations of Named-Entity Recognition (NER) and Term Extraction (TE) to mine such unstructured performance of three third-party entity extraction services through a comprehensive case study, based the unstructured narrative offered in descriptive fields for meaningful concepts through the use of namedentity recognition (NER) and term extraction (TE). in what follows we use the well-known acronym NER to cover both named-entity recognition and term the Semantic Web community, consists in disambiguating named entities with data from the Linking Term Extraction, and Zemanta, provide services for named-entity extraction and disambiguation within the precision, recall, and F1 score of the different NER services against the manually annotated data. identified by the services, i.e. terms rather than named-entities, such as epigraphy or gold for example, Linked Data and the Potential of entity extraction for the Digital Humanities Linked Data and the Potential of entity extraction for the Digital Humanities	./cache/work_peutawgvezbthoqdwyuujshbfm.pdf	./txt/work_peutawgvezbthoqdwyuujshbfm.txt