CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese

Autor:	Xu, Liang, tong, Yu, Dong, Qianqian, Liao, Yixuan, Yu, Cong, Tian, Yin, Liu, Weitang, Li, Lu, Liu, Caiquan, Zhang, Xuanwei
Rok vydání:	2020
Předmět:	Computer Science - Computation and Language Computer Science - Information Retrieval Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: 6 pages, 5 tables, 1 figure
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2001.04351 Zobrazit plný text záznamu View this record from Arxiv