AXIOpedia: Enriching DBpedia with OWL Axioms from Wikipedia

The Semantic Web relies on the creation of rich knowledge bases which link data on the Web. Having access to such a knowledge base enables significant progress in difficult and challenging tasks such as semantic annotation and retrieval. DBpedia, the RDF representation of Wikipedia, is considered today as the central interlinking hub for the emerging Web of data. However, DBpedia still displays some substantial limitations such as the lack of class definitions and the lack of significant taxonomical links. The objective of this work is to enrich DBpedia with OWL-defined classes and taxonomical links using open information extraction from Wikipedia. We propose a pattern-based approach that relies on SPARQL to automatically extract axioms from Wikipedia definitions. We run the system on 12,901,822 Wikipedia pages (including disambiguation pages). The resulting knowledge base, AXIOpedia benefits from a rich and consistent ontology with complex axioms, rdf:subclassOf and rdf:type relations. Keyword. Ontology Learning, Knowledge Extraction, DBpedia.