Using a Natural Language Understanding System to Generate Semantic Web Content
MetadataShow full item record
Type of Work28 pages
journal articles preprints
Citation of Original PublicationAkshay Java, Sergei Nirenburg, Marjorie McShane, Tim Finin, Jesse English, and Anupam Joshi, Using a Natural Language Understanding System to Generate Semantic Web Content, 50 Int’l Journal on Semantic Web & Information Systems, 3(4), 50-74, October-December 2007, http://www.cogsci.rpi.edu/~mcsham2/MargePapers/Java_Using_2007.pdf
RightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
© IGI Global
natural language processing
text meaning representations (TMRs)
UMBC Ebiquity Research Group
We describe our research on automatically generating rich semantic annotations of text and making it available on the Semantic Web. In particular, we discuss the challenges involved in adapting the OntoSem natural language processing system for this purpose. OntoSem, an implementation of the theory of ontological semantics under continuous development for over fifteen years, uses a specially constructed NLP-oriented ontology and an ontologicalsemantic lexicon to translate English text into a custom ontology-motivated knowledge representation language, the language of text meaning representations (TMRs). OntoSem concentrates on a variety of ambiguity resolution tasks as well as processing unexpected input and reference. To adapt OntoSem's representation to the Semantic Web, we developed a translation system, OntoSem2OWL, between the TMR language into the Semantic Web language OWL. We next used OntoSem and OntoSem2OWL to support SemNews, an experimental web service that monitors RSS news sources, processes the summaries of the news stories and publishes a structured representation of the meaning of the text in the news story.