Poster
in
Workshop: Math AI for Education (MATHAI4ED): Bridging the Gap Between Research and Smart Education

GeoRE: A Relation Extraction Dataset for Chinese Geometry Problems

Wei Yu · Shuyu Miao · Xun Zhou · Jingdong Liu · Yongfu Zha · Yongjian Zhang · Mengzhu Wang · Xiaodong Wang

Abstract:

Relation extraction is an important foundation for many natural language understanding applications, as well as geometry problem solving. In this paper, we present GeoRE, a relation extraction dataset for Chinese geometry problems. To the best of our knowledge, GeoRE is the first Chinese relation extraction dataset about geometry problems. It consists of 12,901 geometry problems on 43 shapes, covering 19 positional relations and 4 quantitative relations. We experiment with various state-of-the-art (SOTA) models and the best model achieves only 70.3% F1 value on GeoRE. This shows that GeoRE presents a challenge for future research.