Entities over keywords: what the Knowledge Graph means for your content

In 2012 Google announced the Knowledge Graph with a now-famous phrase: "things, not strings." It marked the shift from matching keywords to understanding entities — people, places, concepts — and the relationships between them.

Strings vs. things

A keyword is a string of characters. An entity is a thing the search engine knows about, with attributes and connections. "Apple" the company and "apple" the fruit are the same string but different entities, disambiguated by context.

For content, this means relevance is no longer about repeating a phrase. It's about covering an entity and its relationships completely so the system can confidently associate your page with the topic.

What the patent actually describes

This isn't just marketing language. Google's patent US 10,235,423 B2, "Ranking search results based on entity metrics," describes scoring results using metrics pulled from the Knowledge Graph itself — including a relatedness metric (how often an entity co-occurs with its entity type across web pages) and a notable type metric (how prominent that entity type is). In other words: the system reasons about entities and their types, not just the literal query string.

How to write for entities

• Map the entity, not just the keyword. Before writing, list the sub-topics, attributes, and related entities a complete resource would cover. That map is your outline.
• Use unambiguous language. Name things explicitly. Define the entity early. Connect it to related entities ("X, a type of Y, used for Z") so the relationships are on the page.
• Add structured data. schema.org markup is the most direct way to tell Google which entities a page is about. Use it.
• Be consistent across the site. Reinforce the same entity associations through internal links and repeated, accurate references.

Why this beats keyword stuffing

When you cover an entity thoroughly and unambiguously, you rank for hundreds of related queries you never explicitly targeted — because the system understands the topic, not just the phrase. That's the whole point of semantic SEO: become the most complete, most credible source on the entity, and the long tail follows.