A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
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Selection and information: a class-based approach to lexical relationships
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ANLC '97 Proceedings of the fifth conference on Applied natural language processing
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EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
Learning surface text patterns for a Question Answering system
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
HLT '93 Proceedings of the workshop on Human Language Technology
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Artificial Intelligence
Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites
Computational Linguistics
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CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
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ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
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COLING '04 Proceedings of the 20th international conference on Computational Linguistics
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AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
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COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
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WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
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International Journal of Human-Computer Studies
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KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
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Data & Knowledge Engineering
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Web Intelligence and Agent Systems
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Journal of Intelligent Information Systems
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This paper describes an automatic approach to identify lexical patterns that represent semantic relationships between concepts in an on-line encyclopedia. Next, these patterns can be applied to extend existing ontologies or semantic networks with new relations. The experiments have been performed with the Simple English Wikipedia and WordNet 1.7. A new algorithm has been devised for automatically generalising the lexical patterns found in the encyclopedia entries. We have found general patterns for the hyperonymy, hyponymy, holonymy and meronymy relations and, using them, we have extracted more than 2600 new relationships that did not appear in WordNet originally. The precision of these relationships depends on the degree of generality chosen for the patterns and the type of relation, being around 60-70% for the best combinations proposed.