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
- 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)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/R19-1014.pdf