Relationship Extraction Distant Supervised

Relation extraction is an important task in the field of natural language processing, aiming to extract semantic relationships between entities from text. Distant supervision relation extraction leverages large-scale labeled datasets to automatically learn and identify types of relationships between entities, enhancing the model's generalization ability and efficiency. It is widely applied in areas such as knowledge graph construction, information retrieval, and intelligent question-answering systems.