distant supervision is a widely applied approach to automatic training of
relation extraction systems and has the advantage that it can generate large
amounts of labelled data with minimal effort. However, this d
本文提出了一种新的 DSRE-NLI 框架,该框架利用现有知识库的远程监督和预训练语言模型的间接监督,通过半自动关系语言表达机制为间接监督提供能量,进而巩固远程注释以便于多分类 RE 模型,并通过数据整合策略实现训练数据的质量提高,大量实验证明该框架显著提高了远程监督 RE 基准数据集的性能(高达 7.73%的 F1)