Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Measures of distributional similarity
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Discovering relations among named entities from large corpora
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Proceedings of the 16th international conference on World Wide Web
Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Cross-lingual query suggestion using query logs of different languages
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Automatically refining the wikipedia infobox ontology
Proceedings of the 17th international conference on World Wide Web
Harvesting relations from the web: quantifiying the impact of filtering functions
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Deriving a large scale taxonomy from Wikipedia
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Decoding wikipedia categories for knowledge acquisition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Turning web text and search queries into factual knowledge: hierarchical class attribute extraction
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
SemEval-2007 task 17: English lexical sample, SRL and all words
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Researcher affiliation extraction from homepages
NLPIR4DL '09 Proceedings of the 2009 Workshop on Text and Citation Analysis for Scholarly Digital Libraries
Learning 5000 relational extractors
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
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A set of labeled classes of instances is extracted from text and linked into an existing conceptual hierarchy. Besides a significant increase in the coverage of the class labels assigned to individual instances, the resulting resource of labeled classes is more effective than similar data derived from the manually-created Wikipedia, in the task of attribute extraction over conceptual hierarchies.