Abstract
We have implemented a novel approach for robust ontology design from natural language texts by combining Discourse Representation Theory (DRT), linguistic frame semantics, and ontology design patterns. We show that DRT-based frame detection is feasible by conducting a comparative evaluation of our approach and existing tools. Furthermore, we define a mapping between DRT and RDF/OWL for the production of quality linked data and ontologies, and present FRED, an online tool for converting text into internally well-connected and linked-data-ready ontologies in web-service-acceptable time.
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Presutti, V., Draicchio, F., Gangemi, A. (2012). Knowledge Extraction Based on Discourse Representation Theory and Linguistic Frames. In: ten Teije, A., et al. Knowledge Engineering and Knowledge Management. EKAW 2012. Lecture Notes in Computer Science(), vol 7603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33876-2_12
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DOI: https://doi.org/10.1007/978-3-642-33876-2_12
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