Semantic Web Evaluation Challenge

Semantic Web Evaluation Challenges pp 40-50

Using FRED for Named Entity Resolution, Linking and Typing for Knowledge Base Population

Conference paper

DOI: 10.1007/978-3-319-25518-7_4

Part of the Communications in Computer and Information Science book series (CCIS, volume 548)
Cite this paper as:
Consoli S., Recupero D.R. (2015) Using FRED for Named Entity Resolution, Linking and Typing for Knowledge Base Population. In: Gandon F., Cabrio E., Stankovic M., Zimmermann A. (eds) Semantic Web Evaluation Challenges. Communications in Computer and Information Science, vol 548. Springer, Cham

Abstract

FRED is a machine reader for extracting RDF graphs that are linked to LOD and compliant to Semantic Web and Linked Data patterns. We describe the capabilities of FRED as a semantic middleware for semantic web applications. In particular, we will show (i) how FRED recognizes and resolves named entities, (ii) how it links them to existing knowledge base, and (iii) how it gives them a type. Given a sentence in any language, it provides different semantic functionalities (frame detection, topic extraction, named entity recognition, resolution and coreference, terminology extraction, sense tagging and disambiguation, taxonomy induction, semantic role labeling, type induction) by means of a versatile user-interface, which can be recalled as REST Web service. The system can be freely used at http://wit.istc.cnr.it/stlab-tools/fred.

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.STLab-ISTC Consiglio Nazionale Delle RicercheCataniaItaly

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