Text2Math: End-to-end parsing text into math expressions

Abstract

We propose Text2Math, a model for semantically parsing text into math expressions. The model can be used to solve different math related problems including arithmetic word problems (Roy and Roth, 2017; Liang et al., 2018) and equation parsing problems (Roy et al., 2016). Unlike previous approaches, we tackle the problem from an end-to-end structured prediction perspective where our algorithm aims to predict the complete math expression at once as a tree structure, where minimal manual efforts are involved in the process. Empirical results on benchmark datasets demonstrate the efficacy of our approach.