Can LLM Substitute Human Labeling? A Case Study of Fine-grained Chinese Address Entity Recognition Dataset for UAV Delivery
Yuxuan Yao, Sichun Luo, Haohan Zhao, Guanzhi Deng, Linqi Song · 2024
We present CNER-UAV, a fine-grained C hinese N ame E ntity R ecognition dataset specifically designed for the task of address resolution in U nmanned A erial V ehicle delivery systems. The dataset encompasses a diverse range of five categories, enabling comprehensive training and evaluation of NER models. To construct this dataset, we sourced the data from a real-world UAV delivery system and conducted a rigorous data cleaning and desensitization process to ensure privacy and data integrity. The resulting dataset, consisting of around 12,000 annotated samples, underwent human experts and L arge L anguage M odel annotation. We evaluated classical NER models on our dataset and provided in-depth analysis. The dataset and models are publicly available at https://github.com/zhhvvv/CNER-UAV.