@inproceedings{stein-donatelli-2021-representing,
    title = "Representing Implicit Positive Meaning of Negated Statements in {AMR}",
    author = "Stein, Katharina  and
      Donatelli, Lucia",
    editor = "Bonial, Claire  and
      Xue, Nianwen",
    booktitle = "Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop",
    month = nov,
    year = "2021",
    address = "Punta Cana, Dominican Republic",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2021.law-1.3/",
    doi = "10.18653/v1/2021.law-1.3",
    pages = "23--35",
    abstract = "Abstract Meaning Representation (AMR) has become popular for representing the meaning of natural language in graph structures. However, AMR does not represent scope information, posing a problem for its overall expressivity and specifically for drawing inferences from negated statements. This is the case with so-called ``positive interpretations'' of negated statements, in which implicit positive meaning is identified by inferring the opposite of the negation{'}s focus. In this work, we investigate how potential positive interpretations (PPIs) can be represented in AMR. We propose a logically motivated AMR structure for PPIs that makes the focus of negation explicit and sketch an initial proposal for a systematic methodology to generate this more expressive structure."
}