Proceedings Abstracts of the Twenty-Fifth International Joint Conference on Artificial Intelligence

A Tag-Based Statistical English Math Word Problem Solver with Understanding, Reasoning and Explanation / 4254
Chao-Chun Liang, Kuang-Yi Hsu, Chien-Tsung Huang, Chung-Min Li, Shen-Yu Miao, Keh-Yih Su

This demonstration presents a tag-based statistical English math word problem (MWP) solver with understanding, reasoning, and explanation. It analyzes the text and transforms both body and question parts into their tag-based logic forms, and then performs inference on them. The proposed tag (e.g., Agent, Verb, etc.) provides the flexibility for annotating an extracted math quantity with its associated syntactic and semantic information, which can be used to identify the desired operand 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 tags and used in the inference process, the proposed approach could explain how the answer is obtained in a human comprehensible way.