Yago: a core of semantic knowledge

  • Authors:

  • Fabian M. Suchanek;Gjergji Kasneci;Gerhard Weikum

  • Affiliations:

  • Max-Planck-Institute for Computer Science;Max-Planck-Institute for Computer Science;Max-Planck-Institute for Computer Science

  • Venue:
  • Proceedings of the 16th international conference on World Wide Web
  • Year:
  • 2007

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Abstract

We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuristic methods described in this paper. The resulting knowledge base is a major step beyond WordNet: in quality by adding knowledge about individuals like persons, organizations, products, etc. with their semantic relationships - and in quantity by increasing the number of facts by more than an order of magnitude. Our empirical evaluation of fact correctness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, we show how YAGO can be further extended by state-of-the-art information extraction techniques.