Large lexicons for natural language processing: utilising the grammar coding system of LDOCE
Computational Linguistics - Special issue of the lexicon
Class-based n-gram models of natural language
Computational Linguistics
Computational Linguistics
Information Retrieval
Class-based probability estimation using a semantic hierarchy
Computational Linguistics
Word sense disambiguation in information retrieval revisited
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
A probabilistic account of logical metonymy
Computational Linguistics
met*: a method for discriminating metonymy and metaphor by computer
Computational Linguistics
Partial parsing via finite-state cascades
Natural Language Engineering
Towards a proper treatment of coercion phenomena
EACL '93 Proceedings of the sixth conference on European chapter of the Association for Computational Linguistics
Role of verbs in document analysis
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Clustering verbs semantically according to their alternation behaviour
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A statistical approach to the processing of metonymy
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Enjoy the paper: lexical semantics via lexicology
COLING '90 Proceedings of the 13th conference on Computational linguistics - Volume 2
Verb class disambiguation using informative priors
Computational Linguistics
Syntactic features and word similarity for supervised metonymy resolution
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Clustering polysemic subcategorization frame distributions semantically
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Semantically motivated subcategorization acquisition
ULA '02 Proceedings of the ACL-02 workshop on Unsupervised lexical acquisition - Volume 9
Metonymy resolution as a classification task
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Experiments on the Automatic Induction of German Semantic Verb Classes
Computational Linguistics
The second release of the RASP system
COLING-ACL '06 Proceedings of the COLING/ACL on Interactive presentation sessions
Comparing clusterings---an information based distance
Journal of Multivariate Analysis
A general feature space for automatic verb classification
Natural Language Engineering
Example-based metonymy recognition for proper nouns
EACL '06 Proceedings of the Eleventh Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
Proceedings of the 4th International Workshop on Semantic Evaluations
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Improving verb clustering with automatically acquired selectional preferences
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Unsupervised and constrained Dirichlet process mixture models for verb clustering
GEMS '09 Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
Latent variable models of selectional preference
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Acquiring human-like feature-based conceptual representations from corpora
CN '10 Proceedings of the NAACL HLT 2010 First Workshop on Computational Neurolinguistics
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The use of figurative language is ubiquitous in natural language texts and it is a serious bottleneck in automatic text understanding. A system capable of interpreting figurative expressions would be an invaluable addition to the real-world natural language processing (NLP) applications that need to access semantics, such as machine translation, opinion mining, question answering and many others. In this article we focus on one type of figurative language, logical metonymy, and present a computational model of its interpretation bringing together statistical techniques and the insights from linguistic theory. Compared to previous approaches this model is both more informative and more accurate. The system produces sense-level interpretations of metonymic phrases and then automatically organizes them into conceptual classes, or roles, discussed in the majority of linguistic literature on the phenomenon.