Named entity recognition (NER)

Named Entity Recognition (NER) is a technique in natural language processing (NLP) that identifies and classifies key information in text, such as names of people, organizations, locations, dates, or quantities. It helps machines understand structured meaning from unstructured text.

NER is a fundamental task in machine learning and large language model applications. During model training, the system learns to recognize entities from labeled datasets and apply that knowledge to new text.

Common uses of NER include search engines, chatbots, and analytics tools. For example, in customer support, an AI agent might use NER to extract user details or product names from messages to deliver faster and more accurate responses.