BERT BiGRU CRF

BERT-BiGRU-CRF models represent a powerful approach to named entity recognition (NER), leveraging the contextual understanding of BERT with the sequential modeling capabilities of BiGRU and the structured prediction of CRF. Current research focuses on improving NER performance across diverse domains, including clinical text, financial reports, and social media, often exploring variations in model architecture and incorporating external knowledge sources like knowledge graphs to address challenges like word ambiguity and abbreviation. These advancements enhance information extraction from unstructured text, impacting various applications such as text-to-speech systems, data visualization tools, and knowledge discovery in specialized fields.