Document Level Relation Extraction

Document-level relation extraction (DocRE) aims to identify relationships between entities mentioned across multiple sentences within a document, a task crucial for automatically building knowledge bases from unstructured text. Current research focuses on improving accuracy and efficiency using various approaches, including large language models (LLMs), graph neural networks (GNNs), and methods that leverage syntactic information or incorporate knowledge from external resources like knowledge graphs. DocRE's advancements are significant for numerous applications, such as enhancing information retrieval, enabling more sophisticated question answering systems, and facilitating the automated construction of comprehensive knowledge repositories.