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Phrase-Level Metaphor Identification using Distributed Representations of Word Meaning

Publication Type: 
Refereed Conference Meeting Proceeding
Metaphor is an essential element of human cognition which is often used to express ideas and emotions that might be difficult to express using literal language. Processing metaphoric language is a challenging task for a wide range of applications ranging from text simplification to psychotherapy. Despite the variety of approaches that are trying to process metaphor, there is still a need for better models that mimic the human cognition while exploiting fewer resources. In this paper, we present an approach based on distributional semantics to identify metaphors on the phrase-level. We investigated the use of different word embeddings models to identify verb-noun pairs where the verb is used metaphorically. Several experiments are conducted to show the performance of the proposed approach on benchmark datasets.
Conference Name: 
The First Workshop on Figurative Language Processing (FigLang 2018) in conjunction with NAACL 2018
Proceedings of the First Workshop on Figurative Language Processing (FigLang 2018)
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Conference Location: 
United States of America
Research Group: 
National University of Ireland, Galway (NUIG)
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