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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 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.
