Entity Recognition

Entity recognition (NER) is a natural language processing task focused on automatically identifying and classifying named entities (e.g., people, organizations, locations) within text. Current research emphasizes improving NER accuracy and robustness across diverse domains and languages, often leveraging large language models (LLMs) and transformer architectures, along with techniques like few-shot learning and data augmentation to address data scarcity and noise. The advancements in NER have significant implications for various applications, including biomedical literature mining, clinical data analysis, and information extraction from unstructured documents, ultimately facilitating knowledge discovery and improved decision-making.