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YAGO: a core of semantic knowledge
Abstract We present YAGO, a light-weight and extensWe 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.the-art information extraction techniques.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Comments "Our empirical evaluation of fact correctness shows an accuracy of about 95%" p. 697
Conclusion The resulting knowledge base is a major stThe 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.the-art information extraction techniques.
Data source Experiment responses  + , Websites  + , Wikipedia pages  +
Doi 10.1145/1242572.1242667 +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22YAGO%3A%2Ba%2Bcore%2Bof%2Bsemantic%2Bknowledge%22  +
Has author Fabian M. Suchanek + , Gjergji Kasneci + , Gerhard Weikum +
Has domain Computer science +
Has topic Semantic relatedness + , Ontology building +
Pages 697-706  +
Peer reviewed Yes  +
Publication type Conference paper  +
Published in WWW '07 Proceedings of the 16th international conference on World Wide Web +
Research design Experiment  +
Research questions We present YAGO, a light-weight and extensWe 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.heuristic methods described in this paper.
Revid 11,113  +
Theories Undetermined
Theory type Design and action  +
Title YAGO: a core of semantic knowledge
Unit of analysis Article  +
Url http://dl.acm.org/citation.cfm?id=1242667  +
Wikipedia coverage Main topic  +
Wikipedia data extraction Dump  +
Wikipedia language English  +
Wikipedia page type Article  +
Year 2007  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:36:47  +
Categories Semantic relatedness  + , Ontology building  + , Computer science  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:34:23  +
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