@inproceedings{pedinotti-lenci-2020-dont,
    title = "Don`t Invite {BERT} to Drink a Bottle: Modeling the Interpretation of Metonymies Using {BERT} and Distributional Representations",
    author = "Pedinotti, Paolo  and
      Lenci, Alessandro",
    editor = "Scott, Donia  and
      Bel, Nuria  and
      Zong, Chengqing",
    booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "International Committee on Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest_wac_2008/2020.coling-main.602/",
    doi = "10.18653/v1/2020.coling-main.602",
    pages = "6831--6837",
    abstract = "In this work, we carry out two experiments in order to assess the ability of BERT to capture the meaning shift associated with metonymic expressions. We test the model on a new dataset that is representative of the most common types of metonymy. We compare BERT with the Structured Distributional Model (SDM), a model for the representation of words in context which is based on the notion of Generalized Event Knowledge. The results reveal that, while BERT ability to deal with metonymy is quite limited, SDM is good at predicting the meaning of metonymic expressions, providing support for an account of metonymy based on event knowledge."
}