4.4 Article Proceedings Paper

YAGO: A Large Ontology from Wikipedia and WordNet

期刊

JOURNAL OF WEB SEMANTICS
卷 6, 期 3, 页码 203-217

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ELSEVIER
DOI: 10.1016/j.websem.2008.06.001

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Ontologies; Information extraction; Knowledge representation

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This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO's precision at 95%-as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO's data. (c) 2008 Published by Elsevier B.V.

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