Grasping the Finer Point: A Supervised Similarity Network for Metaphor Detection
Computation and Language
2017-09-05 v1 Machine Learning
Neural and Evolutionary Computing
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.
Keywords
Cite
@article{arxiv.1709.00575,
title = {Grasping the Finer Point: A Supervised Similarity Network for Metaphor Detection},
author = {Marek Rei and Luana Bulat and Douwe Kiela and Ekaterina Shutova},
journal= {arXiv preprint arXiv:1709.00575},
year = {2017}
}
Comments
EMNLP 2017