Named Entity Recognition

Named Entity Recognition (NER) is a natural language processing task focused on automatically identifying and classifying named entities (e.g., people, locations, organizations, medical terms) within text. Current research emphasizes improving NER performance in challenging scenarios, such as handling noisy text from OCR, low-resource languages, and domain-specific terminology, often leveraging large language models (LLMs) and transformer architectures alongside traditional methods like LSTMs and CRFs. The advancements in NER have significant implications for various applications, including clinical decision support, historical document analysis, and cyber-security threat detection, by enabling efficient extraction of structured information from unstructured text data.