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Yago: A Core of Semantic Knowledge - Unifying WordNet and Wikipedia

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

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

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

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Citation

Suchanek, F. M., Kasneci, G., & Weikum, G. (2007). Yago: A Core of Semantic Knowledge - Unifying WordNet and Wikipedia. In C. L. Williamson, M. E. Zurko, P. F. Patel-Schneider, & P. J. Shenoy (Eds.), WWW 2007: 16th International World Wide Web Conference (pp. 697-706). New York, NY, USA: ACM.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-213D-F
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 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.