Entity Extractor for SEO
Extract and classify named entities from your content using AI-powered named entity recognition (NER). Identify the people, organizations, locations, products, technologies, and concepts that Google's Knowledge Graph associates with your text — and discover entity gaps that may be hurting your rankings.
From content to entity insights.
Understand what Google sees in your text — beyond keywords, at the entity level.
Paste Your Content
Paste up to 10,000 characters of text from any source — blog posts, landing pages, competitor articles, or product descriptions. The AI analyzes every sentence to identify and classify named entities that Google's NLP system would recognize in the same content.
Get Classified Entities
The extractor returns entities grouped by type: People, Organizations, Locations, Products, Technologies, Concepts, Events, and more. Each entity is labeled with its semantic category, giving you a complete view of the topical signals your content sends to search engines.
Identify Entity Gaps
Compare your entity list against competitor content to find missing entities. Adding entities that top-ranking pages mention — but your content does not — strengthens semantic relevance and helps Google understand that your page comprehensively covers the topic.
Frequently Asked Questions
What is entity extraction in SEO?
Entity extraction (named entity recognition) is the process of identifying and classifying named entities — people, organizations, locations, products, concepts, and events — in text content. For SEO, entity extraction reveals the topical signals your content sends to Google's Knowledge Graph, helping you optimize for semantic search rather than keyword matching alone.
How do entities affect Google rankings?
Google uses named entity recognition to understand what a page is really about, beyond keyword matching. Pages with strong entity coverage — mentioning the same entities that top-ranking competitors mention — signal topical depth and expertise. Entity-rich content is more likely to appear in featured snippets, knowledge panels, and People Also Ask results.
What is an entity gap analysis?
An entity gap analysis compares the entities in your content against entities in top-ranking competitor pages. Entities that appear in competitor content but not in yours are "entity gaps" — topical blind spots that may prevent your page from ranking. Filling these gaps by naturally integrating missing entities can significantly improve rankings.
How much text can I analyze at once?
You can analyze up to 10,000 characters per request. For longer content, paste your most important sections — the introduction, main body, and key arguments. These sections typically contain the highest density of topically relevant entities.
What entity types does the tool identify?
The extractor classifies entities into types including People, Organizations, Locations, Products, Technologies, Concepts, Events, Medical Terms, Financial Terms, and more. Each entity is labeled with its semantic category so you can quickly assess which topical dimensions your content covers.
What is the difference between entities and keywords?
Keywords are search terms users type into Google. Entities are real-world things — people, places, organizations, concepts — that exist in Google's Knowledge Graph as distinct objects with attributes and relationships. Entity SEO optimizes for meaning and topical coverage; keyword SEO optimizes for term matching. Modern SEO requires both.
Can I compare my entities against competitors?
This free tool extracts entities from text you paste. For automated entity comparison against the top 10 SERP results for any keyword, use Serplight's SERP Analyzer — it performs entity gap analysis automatically, showing exactly which entities your content is missing compared to ranking competitors.
How do I add missing entities to my content naturally?
Don't just list entity names — discuss them in context. Explain why each entity is relevant to your topic, how it relates to other entities in your content, and what value it provides to the reader. Google's NLP evaluates entity context, not just presence. A well-contextualized mention is far more valuable than a keyword-stuffed list.