  An arithmetic word problem typically includes a textual description
containing several constant quantities. The key to solving the problem is to
reveal the underlying mathematical relations (such as addition and subtraction)
among quantities, and then generate equations to find solutions. This work
presents a novel approach, Quantity Tagger, that automatically discovers such
hidden relations by tagging each quantity with a sign corresponding to one type
of mathematical operation. For each quantity, we assume there exists a latent,
variable-sized quantity span surrounding the quantity token in the text, which
conveys information useful for determining its sign. Empirical results show
that our method achieves 5 and 8 points of accuracy gains on two datasets
respectively, compared to prior approaches.
