Semantic Parsing of Pre-university Math Problems
Takuya Matsuzaki, Takumi Ito, Hidenao Iwane, Hirokazu Anai, Noriko H. Arai
Abstract
We have been developing an end-to-end math problem solving system that accepts natural language input. The current paper focuses on how we analyze the problem sentences to produce logical forms. We chose a hybrid approach combining a shallow syntactic analyzer and a manually-developed lexicalized grammar. A feature of the grammar is that it is extensively typed on the basis of a formal ontology for pre-university math. These types are helpful in semantic disambiguation inside and across sentences. Experimental results show that the hybrid system produces a well-formed logical form with 88% precision and 56% recall.- Anthology ID:
- P17-1195
- Volume:
- Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- July
- Year:
- 2017
- Address:
- Vancouver, Canada
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 2131–2141
- Language:
- URL:
- https://aclanthology.org/P17-1195
- DOI:
- 10.18653/v1/P17-1195
- Cite (ACL):
- Takuya Matsuzaki, Takumi Ito, Hidenao Iwane, Hirokazu Anai, and Noriko H. Arai. 2017. Semantic Parsing of Pre-university Math Problems. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2131–2141, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Semantic Parsing of Pre-university Math Problems (Matsuzaki et al., ACL 2017)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/P17-1195.pdf