[目的/意义]红色文献数量庞大、类型多样，给红色文献细粒度标注带来诸多困难，如何利用少量已有标注数据开展红色文献的自动化数据标注研究是促进红色文献智能化处理与应用研究中亟待解决的重要问题之一。文章设计红色文献的元数据表示体系，并尝试利用迁移学习技术对未标注文献进行标注实验，实现红色文献元数据知识的自动化标注。[方法/过程]首先，构建融合预训练模型、双向长短时记忆网络、多头注意力机制和条件随机场的BERT-BiLSTM-MHA-CRF模型；其次，根据红色文献的内容特征，设计多组红色文献的元数据表示体系；最后，探究在不同类型的红色文献自动化标注任务中，元数据表示体系与迁移学习模型的适配性。[结果/结论]MRS 6元数据表示体系可作为通用型红色文献的元数据表示体系，“BERT-BiLSTM-MHA-CRF+MRS 6”适用于不同场景的红色文献自动化标注，在同类型红色文献的自动化标注实验中具有较好的泛化能力。

[Purpose/significance] The huge quantity and diverse types of red literature bring many difficulties to the fine-grained annotation of red literature, and how to utilize a small amount of existing annotated data to carry out the re⁃search on automated data annotation of red literature is one of the important problems to be solved in the promotion of intelligent processing and application research of red literature. We design the metadata representation system of red literature and try to use transfer learning technology to conduct annotation experiments on unannotated literature to re⁃alize the automated annotation of metadata of red literature.[Method/process] Firstly, BERT-BiLSTM-MHA-CRF model incorporating pre-trained model, bi-directional long and short-term memory network, multi-head attention and conditional random field was constructed. Secondly, according to the content characteristics of red literature, the meta⁃
data representation system of multiple groups of red literature is designed. Finally, the suitability of metadata represen⁃tation systems with transfer learning models in different types of automated red literature annotation tasks was explored.[Result/conclusion] The MRS 6 Metadata Representation System can be used as a metadata representation system for generic red literature. The“BERT-BiLSTM-MHA-CRF + MRS 6”is suitable for the automated annotation of red doc⁃uments in different scenarios, and it has good generalization ability in the automated annotation experiments of the same type of red documents.