Cross Document Relation Extraction

Cross-document relation extraction (CDRE) aims to identify relationships between entities mentioned in different documents, a task significantly more complex than single-document relation extraction. Current research focuses on improving the efficiency and accuracy of CDRE by employing graph-based models to capture inter-entity relationships, developing sophisticated methods for selecting relevant sentences and retrieving multi-hop evidence, and mitigating biases in training data. These advancements are crucial for improving knowledge discovery from large text corpora, with applications ranging from biomedical literature analysis to building more comprehensive knowledge graphs.