Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Conceptual Indexing: A Better Way to Organize Knowledge
Conceptual Indexing: A Better Way to Organize Knowledge
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Automatic construction of a hypernym-labeled noun hierarchy from text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Projecting corpus-based semantic links on a thesaurus
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Ontology learning: state of the art and open issues
Information Technology and Management
Disambiguating hypernym relations for Roget's thesaurus
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
Corpus-Driven hyponym acquisition for turkish language
CICLing'12 Proceedings of the 13th international conference on Computational Linguistics and Intelligent Text Processing - Volume Part I
Learning Hierarchical Lexical Hyponymy
International Journal of Cognitive Informatics and Natural Intelligence
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Many lexical semantic relations, such as the hyponymy relation, can be extracted from text as they occur in detectable syntactic constructions. This paper shows how a hypernym-hyponym based lexicon for Swedish can be created directly from a news paper corpus. An algorithm is presented for building partial hierarchical structures from non domain-specific texts.