How it works
- Paste your text or enter a page URL — the tool fetches the live HTML and reads the rendered content.
- It parses the text into candidate entities, isolating proper nouns and meaningful noun phrases from ordinary words.
- Each candidate is classified by type — person, organization, place, product or concept — and its mentions are counted across the page.
- The tool scores entity richness (how many distinct entities you cover) and diversity (how balanced those types are).
- It then suggests where schema markup and sameAs links would define your key entities more clearly for machines.
What it extracts
- People — named individuals such as authors, founders, experts or public figures mentioned in the content.
- Organizations — companies, brands, institutions and agencies that the page references.
- Places — cities, countries, regions and locations that give the content geographic context.
- Products and works — named products, tools, services or titled works the page discusses.
- Concepts and topics — the key themes and subject-matter terms that define what the page is about.
- Mention counts and type guess — how often each entity appears and the category the tool assigns it.
Why it matters
Modern search doesn't just match keywords — it maps entities and the relationships between them. Google's Knowledge Graph and large language models understand a page by identifying the real-world things it names and how confidently they connect. A page rich in clearly defined entities is easier to place in the right topic, disambiguate from similar names, and cite in an AI answer. Thin or vague entity coverage leaves machines guessing which "Apple," "Jordan" or "Mercury" you mean, and your page loses ground to sources that spell it out.
How to improve entity coverage
Name your entities explicitly instead of leaning on pronouns or vague labels, and introduce each one in full before shortening it. Add Organization, Person and Product schema with sameAs links to authoritative profiles like Wikipedia, Wikidata or official sites so machines can resolve each entity to a known node. Cite recognized authorities and link to canonical sources for the concepts you cover. Broaden coverage by addressing closely related entities a thorough page would include, then re-run the extractor to confirm richer, more balanced results.
Frequently asked questions
What counts as an entity?
An entity is a distinct, real-world thing a page names — a person, organization, place, product or concept — rather than a generic word. Search engines treat entities as nodes in a knowledge graph, so identifying them clearly helps machines understand what your content is genuinely about.
Does the Entity Extractor work on pasted text as well as URLs?
Yes. You can paste raw content to analyze a draft before it goes live, or enter a URL to have the tool fetch and read the published page exactly as crawlers and AI models see it. Both routes return the same entity list, type guesses and scores.
How does entity coverage affect SEO and AI visibility?
Richer, clearly defined entities help Google and AI systems place your page in the right topic and disambiguate it from similar names. That improves your chances of ranking for entity-related queries and being cited in AI Overviews, ChatGPT and Perplexity answers about those topics.