Abstract
This paper presents a semantic parsing and reasoning approach to automatically solving math word problems. A new meaning representation language is designed to bridge natural language text and math expressions. A CFG parser is implemented based on 9,600 semi-automatically created grammar rules. We conduct experiments on a test set of over 1,500 number word problems (i.e., verbally expressed number problems) and yield 95.4% precision and 60.2% recall.
Cite
CITATION STYLE
Shi, S., Wang, Y., Lin, C. Y., Liu, X., & Rui, Y. (2015). Automatically solving number word problems by semantic parsing and reasoning. In Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing (pp. 1132–1142). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d15-1135
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