@inproceedings{ehren-etal-2020-supervised,
    title = "Supervised Disambiguation of {G}erman Verbal Idioms with a {B}i{LSTM} Architecture",
    author = "Ehren, Rafael  and
      Lichte, Timm  and
      Kallmeyer, Laura  and
      Waszczuk, Jakub",
    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/add-emnlp-2024-awards/2020.figlang-1.29/",
    doi = "10.18653/v1/2020.figlang-1.29",
    pages = "211--220",
    abstract = "Supervised disambiguation of verbal idioms (VID) poses special demands on the quality and quantity of the annotated data used for learning and evaluation. In this paper, we present a new VID corpus for German and perform a series of VID disambiguation experiments on it. Our best classifier, based on a neural architecture, yields an error reduction across VIDs of 57{\%} in terms of accuracy compared to a simple majority baseline."
}