Solving Geometry Problems: Combining Text and Diagram Interpretation

Minjoon Seo, Hannaneh Hajishirzi, Ali Farhadi, Oren Etzioni, Clint Malcolm
2015 Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing  
This paper introduces GEOS, the first automated system to solve unaltered SAT geometry questions by combining text understanding and diagram interpretation. We model the problem of understanding geometry questions as submodular optimization, and identify a formal problem description likely to be compatible with both the question text and diagram. GEOS then feeds the description to a geometric solver that attempts to determine the correct answer. In our experiments, GEOS achieves a 49% score on
more » ... ves a 49% score on official SAT questions, and a score of 61% on practice questions. 1 Finally, we show that by integrating textual and visual information, GEOS boosts the accuracy of dependency and semantic parsing of the question text.
doi:10.18653/v1/d15-1171 dblp:conf/emnlp/SeoHFEM15 fatcat:e5a5hp6d3zeutofrdfkm47vsc4