Semantically-enhanced information extraction

Hisham Assal, John Seng, Franz Kurfess, Emily Schwarz, Kym Pohl
2011 2011 Aerospace Conference  
Information Extraction using Natural Language Processing (NLP) produces entities along with some of the relationships that may exist among them. To be semantically useful, however, such discrete extractions must be put into context through some form of intelligent analysis. This paper 1,2 offers a two-part architecture that employs the statistical methods of traditional NLP to extract discrete information elements in a relatively domain-agnostic manner, which are then injected into an
more » ... enabled environment where they can be semantically analyzed. Within this semantic environment, extractions are woven into the contextual fabric of a userprovided, domain-centric ontology where users together with user-provided logic can analyze these extractions within a more contextually complete picture. Our demonstration system infers the possibility of a terrorist plot by extracting key events and relationships from a collection of news articles and intelligence reports.
doi:10.1109/aero.2011.5747547 fatcat:bgmnkonxgnaj3awh4avm5md5du