Hyunjae Kim, Jaehyo Yoo, Seunghyun Yoon, Jinhyuk Lee, Jaewoo Kang
TL;DR本研究提出了一种问答式自动生成命名实体识别数据的方法,使用生成的数据进行训练的模型在多项 NER 评测中表现优异,并在少样本 NER 中取得了新的最佳表现。
Abstract
Recent named entity recognition (NER) models often rely on human-annotated
datasets, requiring the significant engagement of professional knowledge on the
target domain and entities. This research introduces an ask-to-generate
approach that automatically generates NER datasets by askin