Abstract
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.- Anthology ID:
- P19-1075
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 778–787
- Language:
- URL:
- https://aclanthology.org/P19-1075
- DOI:
- 10.18653/v1/P19-1075
- Cite (ACL):
- Chujie Zheng, Minlie Huang, and Aixin Sun. 2019. ChID: A Large-scale Chinese IDiom Dataset for Cloze Test. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 778–787, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- ChID: A Large-scale Chinese IDiom Dataset for Cloze Test (Zheng et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/P19-1075.pdf
- Code
- chujiezheng/ChID-Dataset
- Data
- ChID