Named entity recognition (NER) is a natural language processing technique that identifies and classifies named entities in text — people, organizations, loca…
Named entity recognition (NER) is a natural language processing technique that identifies and classifies named entities in text — people, organizations, locations, dates, products, and other proper nouns — into predefined categories. NER is a foundational component of knowledge graph construction and AI content understanding.
NER is the first step in how AI systems extract structured information from unstructured content. Content that uses clear, unambiguous named entities — full company names, specific people with titles, named locations — produces better NER results than content that relies on abbreviations, pronouns, or vague references. Better NER results mean more accurate entity extraction, more reliable attribution, and stronger entity signals across the knowledge graph.