Entity Extraction
Also called: entity detection, named entity recognition, NER, entity identification
Entity extraction is the natural language processing task of automatically identifying and classifying named things (people, places, organizations, dates, products) in unstructured text, then linking them to known records. It is also called named entity recognition (NER) or entity detection.
Content is unstructured: text and images a machine cannot reason over directly. Extraction fixes that. A pipeline detects a span (“Delta”), classifies its type (ORGANIZATION, not the Greek letter or a river delta), and where possible resolves it to a canonical record. Google’s Cloud Natural Language API models this exactly. Its analyzeEntities method returns each entity with a type, a salience score (how central the entity is to the document), and, when it can match one, a Knowledge Graph mid plus a wikipedia_url. Salience matters because it signals what the page is actually about, not just what words it contains.
The same mechanic drives AI search
Google’s Knowledge Graph stores structured facts about billions of entities and their relationships, and AI Overviews, AI Mode, and Gemini lean on it to disambiguate a query and decide which brands to name. Large language models run their own extraction over your content and increasingly ground answers against entity databases. So a page is not a bag of keywords; it is a set of entities a machine tries to recognize and connect.
The practical point: make your entities unambiguous. Consistent naming, sameAs links to Wikidata and Wikipedia, and Organization or Person schema all help a parser resolve you to one stable record instead of guessing between look-alikes.
How it affects your traffic
If a model can't cleanly extract and resolve your brand, product, or author as an entity, you get skipped when AI Overviews, ChatGPT, and Perplexity choose who to cite, even when you rank in classic results. Entity work (schema, consistent naming, sameAs links, a claimed Knowledge Graph presence) is a core part of our AI SEO service and directly shapes whether generative engines name you or a competitor. It also feeds classic rankings, because Google's entity understanding decides which pages actually match a query's intent.
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