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
- Venue:
- IWCS
- SIG:
- SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 55–70
- Language:
- URL:
- https://aclanthology.org/W19-0405
- DOI:
- 10.18653/v1/W19-0405
- Cite (ACL):
- Austin Blodgett and Nathan Schneider. 2019. An Improved Approach for Semantic Graph Composition with CCG. In Proceedings of the 13th International Conference on Computational Semantics - Long Papers, pages 55–70, Gothenburg, Sweden. Association for Computational Linguistics.
- Cite (Informal):
- An Improved Approach for Semantic Graph Composition with CCG (Blodgett & Schneider, IWCS 2019)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/W19-0405.pdf