Difference between revisions of "Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia"
(infobox) |
(Cats.) |
||
(One intermediate revision by one other user not shown) | |||
Line 10: | Line 10: | ||
== Overview == | == Overview == | ||
Authors present YAGO, a lightweight 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 hasWonPrize). The facts have been automatically extracted from [[Wikipedia]] and unified with [[WordNet]], using a carefully designed combination of rule-based and heuris-tic 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. Authors empirical evaluation of fact cor-rectness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, authors show how YAGO can be further extended by state-of-the-art [[information extraction]] techniques. | Authors present YAGO, a lightweight 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 hasWonPrize). The facts have been automatically extracted from [[Wikipedia]] and unified with [[WordNet]], using a carefully designed combination of rule-based and heuris-tic 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. Authors empirical evaluation of fact cor-rectness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, authors show how YAGO can be further extended by state-of-the-art [[information extraction]] techniques. | ||
+ | |||
+ | == Embed == | ||
+ | === Wikipedia Quality === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Suchanek, Fabian M.; Kasneci, Gjergji; Weikum, Gerhard. (2007). "[[Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia]]".DOI: 10.1145/1242572.1242667. | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === English Wikipedia === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | {{cite journal |last1=Suchanek |first1=Fabian M. |last2=Kasneci |first2=Gjergji |last3=Weikum |first3=Gerhard |title=Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia |date=2007 |doi=10.1145/1242572.1242667 |url=https://wikipediaquality.com/wiki/Yago:_a_Core_of_Semantic_Knowledgeunifying_Wordnet_and_Wikipedia}} | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === HTML === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Suchanek, Fabian M.; Kasneci, Gjergji; Weikum, Gerhard. (2007). &quot;<a href="https://wikipediaquality.com/wiki/Yago:_a_Core_of_Semantic_Knowledgeunifying_Wordnet_and_Wikipedia">Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia</a>&quot;.DOI: 10.1145/1242572.1242667. | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | |||
+ | |||
+ | [[Category:Scientific works]] |
Latest revision as of 03:55, 29 December 2020
Authors | Fabian M. Suchanek Gjergji Kasneci Gerhard Weikum |
---|---|
Publication date | 2007 |
DOI | 10.1145/1242572.1242667 |
Links | Original |
Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia - scientific work related to Wikipedia quality published in 2007, written by Fabian M. Suchanek, Gjergji Kasneci and Gerhard Weikum.
Overview
Authors present YAGO, a lightweight 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 hasWonPrize). The facts have been automatically extracted from Wikipedia and unified with WordNet, using a carefully designed combination of rule-based and heuris-tic 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. Authors empirical evaluation of fact cor-rectness shows an accuracy of about 95%. YAGO is based on a logically clean model, which is decidable, extensible, and compatible with RDFS. Finally, authors show how YAGO can be further extended by state-of-the-art information extraction techniques.
Embed
Wikipedia Quality
Suchanek, Fabian M.; Kasneci, Gjergji; Weikum, Gerhard. (2007). "[[Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia]]".DOI: 10.1145/1242572.1242667.
English Wikipedia
{{cite journal |last1=Suchanek |first1=Fabian M. |last2=Kasneci |first2=Gjergji |last3=Weikum |first3=Gerhard |title=Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia |date=2007 |doi=10.1145/1242572.1242667 |url=https://wikipediaquality.com/wiki/Yago:_a_Core_of_Semantic_Knowledgeunifying_Wordnet_and_Wikipedia}}
HTML
Suchanek, Fabian M.; Kasneci, Gjergji; Weikum, Gerhard. (2007). "<a href="https://wikipediaquality.com/wiki/Yago:_a_Core_of_Semantic_Knowledgeunifying_Wordnet_and_Wikipedia">Yago: a Core of Semantic Knowledgeunifying Wordnet and Wikipedia</a>".DOI: 10.1145/1242572.1242667.