Using FRED for named entity resolution, linking and typing for knowledge base population

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.