Named Entity Recognition (NER) is a natural language processing task that identifies and classifies named entities in text, such as people, organizations, locations, and dates.
NER scans unstructured text and tags spans of it as specific entity types, which is a foundational step for turning raw scraped text — articles, listings, reviews — into structured, queryable data.
Once entities are identified via NER, relation extraction techniques can connect them into a knowledge graph, linking, for example, a company entity to a product entity it manufactures.
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