Automatic retrieval and clustering of similar words
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Automatic identification of non-compositional phrases
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Robust, applied morphological generation
INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Extracting the unextractable: a case study on verb-particles
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
A statistical approach to the semantics of verb-particles
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
Detecting a continuum of compositionality in phrasal verbs
MWE '03 Proceedings of the ACL 2003 workshop on Multiword expressions: analysis, acquisition and treatment - Volume 18
Picking them up and figuring them out: verb-particle constructions, noise and idiomaticity
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Prepositions in applications: A survey and introduction to the special issue
Computational Linguistics
Classifying particle semantics in English verb-particle constructions
MWE '06 Proceedings of the Workshop on Multiword Expressions: Identifying and Exploiting Underlying Properties
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This paper describes a distributional approach to the semantics of verb particle constructions (e.g., put up, make off). In common with many other varieties of multiword expression, verb-particles vary in the extent to which the component words of the phrase contribute independent meanings. A technique for automatically detecting when and how a component word is making such a contribution would be very useful in the construction of lexicons. Using verb particles as a test case we suggest that a comparison of the lexical contexts in which the phrase and the components occur can provide us with vital information in this regard. Our hypothesis is that the lexical contexts in which a given verb-particle construction occurs across a corpus will be more similar to those of a given component word if that component word is contributing an independent meaning to the phrase. We demonstrate a convincing correlation between contextual similarity and the compositionality judgements of expert and non-expert annotators. ors.