Grasping the Finer Point: A Supervised Similarity Network for Metaphor Detection
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Peer-reviewed
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Authors
Rei, M
Bulat, LT
Kiela, D
Shutova, E
Abstract
The ubiquity of metaphor in our everyday communication makes it an important problem for natural language understanding. Yet, the majority of metaphor processing systems to date rely on hand engineered features and there is still no consensus in the field as to which features are optimal for this task. In this paper, we present the first deep learning architecture designed to capture metaphorical composition. Our results demonstrate that it outperforms the existing approaches in the metaphor identification task.
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Journal Title
EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings
Conference Name
Conference on Empirical Methods in Natural Language Processing
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Publisher
Association for Computational Linguistics
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Cambridge Assessment (unknown)