A computational model of metaphor interpretation
A computational model of metaphor interpretation
Karma: knowledge-based active representations for metaphor and aspect
Karma: knowledge-based active representations for metaphor and aspect
Head-driven statistical models for natural language parsing
Head-driven statistical models for natural language parsing
met*: a method for discriminating metonymy and metaphor by computer
Computational Linguistics
CorMet: a computational, corpus-based conventional metaphor extraction system
Computational Linguistics
Question answering based on semantic structures
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Metaphor-based meaning excavation
Information Sciences: an International Journal
Corpus-driven metaphor harvesting
FigLanguages '07 Proceedings of the Workshop on Computational Approaches to Figurative Language
Textual entailment as an evaluation framework for metaphor resolution: a proposal
STEP '08 Proceedings of the 2008 Conference on Semantics in Text Processing
Discourse topics and metaphors
CALC '09 Proceedings of the Workshop on Computational Approaches to Linguistic Creativity
Topic model analysis of metaphor frequency for psycholinguistic stimuli
CALC '09 Proceedings of the Workshop on Computational Approaches to Linguistic Creativity
OCCAM: ontology-based computational contextual analysis and modeling
CONTEXT'07 Proceedings of the 6th international and interdisciplinary conference on Modeling and using context
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
A game-theoretic model of metaphorical bargaining
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
CALC '10 Proceedings of the NAACL HLT 2010 Second Workshop on Computational Approaches to Linguistic Creativity
Metaphor identification using verb and noun clustering
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Statistical metaphor processing
Computational Linguistics
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Metaphors are ubiquitous in language and developing methods to identify and deal with metaphors is an open problem in Natural Language Processing (NLP). In this paper we describe results from using a maximum entropy (ME) classifier to identify metaphors. Using the Wall Street Journal (WSJ) corpus, we annotated all the verbal targets associated with a set of frames which includes frames of spatial motion, manipulation, and health. One surprising finding was that over 90% of annotated targets from these frames are used metaphorically, underscoring the importance of processing figurative language. We then used this labeled data and each verbal target's PropBank annotation to train a maximum entropy classifier to make this literal vs. metaphoric distinction. Using the classifier, we reduce the final error in the test set by 5% over the verb-specific majority class baseline and 31% over the corpus-wide majority class baseline.