Cloze-style reading comprehension in Chinese is still limited due to the lack of various corpora. In this paper we propose a large-scale Chinese cloze test dataset ChID, which studies the comprehension of idiom, a unique language phenomenon in Chinese. In this corpus, the idioms in a passage are replaced by blank symbols and the correct answer needs to be chosen from well-designed candidate idioms. We carefully study how the design of candidate idioms and the representation of idioms affect the performance of state-of-the-art models. Results show that the machine accuracy is substantially worse than that of human, indicating a large space for further research.
@article{arxiv.1906.01265,
title = {ChID: A Large-scale Chinese IDiom Dataset for Cloze Test},
author = {Chujie Zheng and Minlie Huang and Aixin Sun},
journal= {arXiv preprint arXiv:1906.01265},
year = {2020}
}