Difference between revisions of "Models of metaphor in NLP"
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=== Met* System (Fass, 1991) === | === Met* System (Fass, 1991) === | ||
| + | - First attempt | ||
| + | - Capable of discriminating between literalness, metonymy, metaphor and anomaly | ||
=== Goatly (1997) === | === Goatly (1997) === | ||
Revision as of 15:27, 7 October 2012
Contents
Citation
E. Shutova. 2010. Models of Metaphor in NLP. In Proceedings of ACL 2010, Uppsala, Sweden.
Online version
Introduction
This is a review paper of modeling metaphors in NLP. The author devised it into two main tasks: "metaphor recognition" and "metaphor interpretation".
Metaphor Recognition
Met* System (Fass, 1991)
- First attempt - Capable of discriminating between literalness, metonymy, metaphor and anomaly
Goatly (1997)
Peters & Peters (2000)
CorMet System (Mason, 2004)
TroFi System(Birke & Sarkar, 2006)
Gedigan et al. (2006)
Krishnakumaran & Zhu (2007)
Metaphor Interpretation
MIDAS System (Martin, 1990)
KARMA System (Narayanan, 1997), ATT-Meta (Barnden and Lee, 2002)
Veale and Hao (2008)
Shutova (2010)
Metaphor Resources
Metaphor Annotation in Corpora
Metaphor & Polysemy
Metaphor Identification
Pragglejaz Procedure
Source - Target Domain Vocabulary
Annotating Source and target Domains
Related papers
The widely cited Pang et al EMNLP 2002 paper was influenced by this paper - but considers supervised learning techniques. The choice of movie reviews as the domain was suggested by the (relatively) poor performance of Turney's method on movies.
An interesting follow-up paper is Turney and Littman, TOIS 2003 which focuses on evaluation of the technique of using PMI for predicting the semantic orientation of words.
