@inproceedings{mckenna-steedman-2020-learning,
    title = "Learning Negation Scope from Syntactic Structure",
    author = "McKenna, Nick  and
      Steedman, Mark",
    booktitle = "Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics",
    month = dec,
    year = "2020",
    address = "Barcelona, Spain (Online)",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.starsem-1.15",
    pages = "137--142",
    abstract = "We present a semi-supervised model which learns the semantics of negation purely through analysis of syntactic structure. Linguistic theory posits that the semantics of negation can be understood purely syntactically, though recent research relies on combining a variety of features including part-of-speech tags, word embeddings, and semantic representations to achieve high task performance. Our simplified model returns to syntactic theory and achieves state-of-the-art performance on the task of Negation Scope Detection while demonstrating the tight relationship between the syntax and semantics of negation.",
}