Hirokazu Anai
2017
Semantic Parsing of Pre-university Math Problems
Takuya Matsuzaki
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Takumi Ito
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Hidenao Iwane
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Hirokazu Anai
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Noriko H. Arai
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
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.
2013
The Complexity of Math Problems – Linguistic, or Computational?
Takuya Matsuzaki
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Hidenao Iwane
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Hirokazu Anai
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Noriko Arai
Proceedings of the Sixth International Joint Conference on Natural Language Processing
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