Year: 2020
Type: preprint
Abstract: In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese. CLUENER2020 contains 10 categories. Apart from common labels like person, organization, and location, it contains more diverse categories. It is more challenging than current other Chinese NER datasets and could better reflect real-world applications. For comparison, we implement several state-of-the-art baselines as sequence labeling tasks and report human performance, as well as its analysis. To facilitate future work on fine-grained NER for Chinese, we release our dataset, baselines, and leader-board.
Source: arXiv (Cornell University)
Authors: Xu, Liang, tong, Yu, Dong, Qianqian, Liao, Yixuan, Yu, Cong, Tian, Yin, Liu, Weitang, Li, Lu, Liu, Caiquan, Zhang, Xuanwei
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2998811572