Relation Extraction Model

Relation extraction models automatically identify relationships between entities mentioned in text, a crucial task for building knowledge graphs and enabling advanced natural language understanding. Current research emphasizes improving model performance across diverse domains and languages, including low-resource settings and code-switching scenarios, often leveraging transformer-based architectures and incorporating knowledge graph embeddings to enhance contextual understanding. These advancements are vital for various applications, such as enriching scientific databases, improving financial analysis, and facilitating biomedical research by extracting key relationships from large text corpora.