Retrieving collocations from text: Xtract
Computational Linguistics - Special issue on using large corpora: I
Noun-phrase co-occurrence statistics for semiautomatic semantic lexicon construction
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
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
Automatic identification of non-compositional phrases
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Geometry and Meaning
A graph model for unsupervised lexical acquisition
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
An empirical model of multiword expression decomposability
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
Unsupervised type and token identification of idiomatic expressions
Computational Linguistics
Automatic identification of English verb particle constructions using linguistic features
Prepositions '06 Proceedings of the Third ACL-SIGSEM Workshop on Prepositions
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This paper describes a technique for extracting idioms from text. The technique works by finding patterns such as "thrills and spills", whose reversals (such as "spills and thrills") are never encountered. This method collects not only idioms, but also many phrases that exhibit a strong tendency to occur in one particular order, due apparently to underlying semantic issues. These include hierarchical relationships, gender differences, temporal ordering, and prototype-variant effects.