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Yago - a core of semantic knowledge

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44738

Kasneci,  Gjergji
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45572

Suchanek,  Fabian
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45720

Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Fulltext (public)

MPI-I-2006-5-006.pdf
(Any fulltext), 252KB

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Citation

Kasneci, G., Suchanek, F., & Weikum, G.(2006). Yago - a core of semantic knowledge (MPI-I-2006-5-006). Saarbrücken: Max-Planck-Institut für Informatik.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0014-670A-A
Abstract
We present YAGO, a light-weight and extensible ontology with high coverage and quality. YAGO builds on entities and relations and currently contains roughly 900,000 entities and 5,000,000 facts. This includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as relation{hasWonPrize}). The facts have been automatically extracted from the unification of Wikipedia and 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.