@InProceedings{matsuzaki-EtAl:2017:Long,
  author    = {Matsuzaki, Takuya  and  Ito, Takumi  and  Iwane, Hidenao  and  Anai, Hirokazu  and  H. Arai, Noriko},
  title     = {Semantic Parsing of Pre-university Math Problems},
  booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  month     = {July},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {2131--2141},
  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.},
  url       = {http://aclweb.org/anthology/P17-1195}
}