@inproceedings{blodgett-schneider-2019-improved,
    title = "An Improved Approach for Semantic Graph Composition with {CCG}",
    author = "Blodgett, Austin  and
      Schneider, Nathan",
    editor = "Dobnik, Simon  and
      Chatzikyriakidis, Stergios  and
      Demberg, Vera",
    booktitle = "Proceedings of the 13th International Conference on Computational Semantics - Long Papers",
    month = may,
    year = "2019",
    address = "Gothenburg, Sweden",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W19-0405/",
    doi = "10.18653/v1/W19-0405",
    pages = "55--70",
    abstract = "This paper builds on previous work using Combinatory Categorial Grammar (CCG) to derive a transparent syntax-semantics interface for Abstract Meaning Representation (AMR) parsing. We define new semantics for the CCG combinators that is better suited to deriving AMR graphs. In particular, we define relation-wise alternatives for the application and composition combinators: these require that the two constituents being combined overlap in one AMR relation. We also provide a new semantics for type raising, which is necessary for certain constructions. Using these mechanisms, we suggest an analysis of eventive nouns, which present a challenge for deriving AMR graphs. Our theoretical analysis will facilitate future work on robust and transparent AMR parsing using CCG."
}