Joint NER and Classification

Joint Named Entity Recognition and Classification refers to the task of simultaneously performing named entity recognition and text classification in natural language processing. This task aims to accurately identify entities with specific significance from the given text and classify the entire text to meet the needs of information extraction and content understanding. By integrating these two technologies, processing efficiency and accuracy can be improved, and it is widely applied in sentiment analysis, news classification, medical diagnosis, and other fields.