An Improved Approach for Semantic Graph Composition with CCG

Austin Blodgett, Nathan Schneider


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.
Anthology ID:
W19-0405
Volume:
Proceedings of the 13th International Conference on Computational Semantics - Long Papers
Month:
May
Year:
2019
Address:
Gothenburg, Sweden
Venues:
IWCS | WS
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
55–70
Language:
URL:
https://aclanthology.org/W19-0405
DOI:
10.18653/v1/W19-0405
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/W19-0405.pdf