Artificial Intelligence - Special volume on natural language processing
Computational Linguistics
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Understanding metonymies in discourse
Artificial Intelligence
met*: a method for discriminating metonymy and metaphor by computer
Computational Linguistics
Generalizing case frames using a thesaurus and the MDL principle
Computational Linguistics
A statistical approach to the processing of metonymy
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Probabilistic text structuring: experiments with sentence ordering
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
On metonymy recognition for geographic information retrieval
International Journal of Geographical Information Science
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
GYDER: maxent metonymy resolution
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UP13: knowledge-poor methods (sometimes) perform poorly
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
UTD-HLT-CG: semantic architecture for metonymy resolution and classification of nominal relations
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
XRCE-M: a hybrid system for named entity metonymy resolution
SemEval '07 Proceedings of the 4th International Workshop on Semantic Evaluations
Sense-based interpretation of logical metonymy using a statistical method
ACLstudent '09 Proceedings of the ACL-IJCNLP 2009 Student Research Workshop
Combining collocations, lexical and encyclopedic knowledge for metonymy resolution
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Ensemble models for dependency parsing: cheap and good?
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Unsupervised learning of selectional restrictions and detection of argument coercions
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
| Hi-index | 0.00 |
Computational approaches to metonymy resolution have focused almost exclusively on the local context, especially the constraints placed on a potentially metonymic word by its grammatical collocates. We expand such approaches by taking into account the larger context. Our algorithm is tested on the data from the metonymy resolution task (Task 8) at SemEval 2007. The results show that incorporation of the global context can improve over the use of the local context alone, depending on the types of metonymies addressed. As a second contribution, we move towards unsupervised resolution of metonymies, made feasible by considering ontological relations as possible readings. We show that such an unsupervised approach delivers promising results: it beats the supervised most frequent sense baseline and performs close to a supervised approach using only standard lexico-syntactic features.