@InProceedings{liang-EtAl:2016:COLINGDEMO,
  author    = {Liang, Chao-Chun  and  Tsai, Shih-Hong  and  Chang, Ting-Yun  and  Lin, Yi-Chung  and  Su, Keh-Yih},
  title     = {A Meaning-based English Math Word Problem Solver with Understanding, Reasoning and Explanation},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {151--155},
  abstract  = {This paper presents a meaning-based statistical math word problem (MWP) solver
	with understanding, reasoning and explanation. It comprises a web user
	interface and pipelined modules for analysing the text, transforming both body
	and question parts into their logic forms, and then performing inference on
	them. The associated context of each quantity is represented with proposed
	role-tags (e.g., nsubj, verb, etc.), which provides the flexibility for
	annotating the extracted math quantity with its associated syntactic and
	semantic information (which specifies the physical meaning of that quantity).
	Those role-tags are then used to identify the desired operands and filter out
	irrelevant quantities (so that the answer can be obtained precisely). Since the
	physical meaning of each quantity is explicitly represented with those
	role-tags and used in the inference process, the proposed approach could
	explain how the answer is obtained in a human comprehensible way.},
  url       = {http://aclweb.org/anthology/C16-2032}
}