SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction 事件

SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction arXiv:2605.23440v2 Announce Type: replace Abstract: Joint Entity and Relation Extraction (JERE) is highly susceptible to weak generalization due to low-quality training data. Data augmentation is a common strategy to enhance model generalization across different domains. However, existing data augmentation methods often overlook text relevance and may disrupt semantic structures and dependencies, making it dif