@inproceedings{dankers-etal-2020-neighbourly,
    title = "Being neighbourly: Neural metaphor identification in discourse",
    author = "Dankers, Verna  and
      Malhotra, Karan  and
      Kudva, Gaurav  and
      Medentsiy, Volodymyr  and
      Shutova, Ekaterina",
    editor = "Klebanov, Beata Beigman  and
      Shutova, Ekaterina  and
      Lichtenstein, Patricia  and
      Muresan, Smaranda  and
      Wee, Chee  and
      Feldman, Anna  and
      Ghosh, Debanjan",
    booktitle = "Proceedings of the Second Workshop on Figurative Language Processing",
    month = jul,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/Author-page-Marten-During-lu/2020.figlang-1.31/",
    doi = "10.18653/v1/2020.figlang-1.31",
    pages = "227--234",
    abstract = "Existing approaches to metaphor processing typically rely on local features, such as immediate lexico-syntactic contexts or information within a given sentence. However, a large body of corpus-linguistic research suggests that situational information and broader discourse properties influence metaphor production and comprehension. In this paper, we present the first neural metaphor processing architecture that models a broader discourse through the use of attention mechanisms. Our models advance the state of the art on the all POS track of the 2018 VU Amsterdam metaphor identification task. The inclusion of discourse-level information yields further significant improvements."
}