AKSW is back in the news after announcing “the first version of the Federated knOwledge eXtraction (FOX) framework. FOX integrates and merges the results of frameworks for Named Entity Recognition, Keyword/Keyphrase Extraction and Relation Extraction by using machine learning techniques. By these means, FOX can generate RDF out of natural language with improved accuracy. FOX has been shown to be up to 15% more accurate than other frameworks, including commercial software.” Read more

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Entity Extraction is the process of automatically extracting document metadata from unstructured text documents.  Extracting key entities such as person names, locations, dates, specialized terms and product terminology from free-form text can empower organizations to not only improve keyword search but also open the door to semantic search, faceted search and document repurposing.  This article defines the field of entity extraction, shows some of the technical challenges involved, and shows how RDF can be used to store document annotations. It then shows how new tools such as Apache UIMA are poised to make entity extraction much more cost effective to an organization.

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