Exploring Graph-Algebraic CCG Combinators for Syntactic-Semantic AMR Parsing

Sebastian Beschke


Abstract
We describe a new approach to semantic parsing based on Combinatory Categorial Grammar (CCG). The grammar’s semantic construction operators are defined in terms of a graph algebra, which allows our system to induce a compact CCG lexicon. We introduce an expectation maximisation algorithm which we use to filter our lexicon down to 2500 lexical templates. Our system achieves a semantic triple (Smatch) precision that is competitive with other CCG-based AMR parsing approaches.
Anthology ID:
R19-1014
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Editors:
Ruslan Mitkov, Galia Angelova
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
112–121
Language:
URL:
https://aclanthology.org/R19-1014
DOI:
10.26615/978-954-452-056-4_014
Bibkey:
Cite (ACL):
Sebastian Beschke. 2019. Exploring Graph-Algebraic CCG Combinators for Syntactic-Semantic AMR Parsing. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 112–121, Varna, Bulgaria. INCOMA Ltd..
Cite (Informal):
Exploring Graph-Algebraic CCG Combinators for Syntactic-Semantic AMR Parsing (Beschke, RANLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/R19-1014.pdf