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.
REF propose a large-scale Chinese reading comprehension dataset, ChID, to study the comprehension a unique language phenomenon in Chinese.
ChID: A Large-scale Chinese IDiom Dataset for Cloze Test
Association for Computational Linguistics (ACL-2019)
Computer Science