Large-scale Cloze Test Dataset Created by Teachers
Qizhe Xie, Guokun Lai, Zihang Dai, Eduard H. Hovy · 2018
Cloze tests are widely adopted in language exams to evaluate students' language proficiency.In this paper, we propose the first large-scale human-created cloze test dataset CLOTH 1 2 , containing questions used in middle-school and high-school language exams.With missing blanks carefully created by teachers and candidate choices purposely designed to be nuanced, CLOTH requires a deeper language understanding and a wider attention span than previously automaticallygenerated cloze datasets.We test the performance of dedicatedly designed baseline models including a language model trained on the One Billion Word Corpus and show humans outperform them by a significant margin.We investigate the source of the performance gap, trace model deficiencies to some distinct properties of CLOTH, and identify the limited ability of comprehending the long-term context to be the key bottleneck.