An Improved Approach for Semantic Graph Composition with CCG
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.
Keywords
Cite
@article{arxiv.1903.11770,
title = {An Improved Approach for Semantic Graph Composition with CCG},
author = {Austin Blodgett and Nathan Schneider},
journal= {arXiv preprint arXiv:1903.11770},
year = {2019}
}
Comments
IWCS 2019 Camera-ready