Named Entity Recognition (NER) is a natural language processing technique that identifies specific entities mentioned in text and assigns them meaningful categories. These can include people, organizations, locations, dates, products, and other identifiable entities. An NER model analyzes the words and their surrounding context to determine which terms represent entities and what type of entity each one is.
For example, an AI system processing a news article can identify a company name, a city, and a person mentioned in the same sentence. This makes unstructured text easier to organize, search, and analyze. NER is useful in document processing, search engines, customer support, information extraction, content classification, and knowledge graph creation.
