@inproceedings{rei-etal-2017-grasping,
    title = "Grasping the Finer Point: A Supervised Similarity Network for Metaphor Detection",
    author = "Rei, Marek  and
      Bulat, Luana  and
      Kiela, Douwe  and
      Shutova, Ekaterina",
    editor = "Palmer, Martha  and
      Hwa, Rebecca  and
      Riedel, Sebastian",
    booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
    month = sep,
    year = "2017",
    address = "Copenhagen, Denmark",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/D17-1162/",
    doi = "10.18653/v1/D17-1162",
    pages = "1537--1546",
    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."
}