2012 NERDAFrameworkforUnifyingNamedE

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Subject Headings: NERD Ontology.

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Abstract

Named Entity Extraction is a mature task in the NLP field that has yielded numerous services gaining popularity in the Semantic Web community for extracting knowledge from web documents. These services are generally organized as pipelines, using dedicated APIs and different taxonomy for extracting, classifying and disambiguating named entities. Integrating one of these services in a particular application requires to implement an appropriate driver. Furthermore, the results of these services are not comparable due to different formats. This prevents the comparison of the performance of these services as well as their possible combination. We address this problem by proposing NERD, a framework which unifies 10 popular named entity extractors available on the web, and the NERD ontology which provides a rich set of axioms aligning the taxonomies of these tools.

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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2012 NERDAFrameworkforUnifyingNamedEGiuseppe Rizzo
Raphaël Troncy
NERD: A Framework for Unifying Named Entity Recognition and Disambiguation Extraction Tools