Entity Audit Toolkit

Before adding structured data, you need to know whether Google sees your content the way you intend. This lesson introduces an entity audit toolkit built on two Google APIs and a three-step process for diagnosing your own site, benchmarking competitors and checking that entities are named and linked consistently. Its core message is to fix the foundations first, because markup added on top of confused content only amplifies the wrong signals.

What this lesson covers

• The two APIs in the toolkit: the Cloud Natural Language API and the Knowledge Graph Search API
• Analysing your top pages for entities, salience and Knowledge Graph IDs
• Common issues such as high-salience navigation and malformed entity names
• Comparing your entity profile with a small set of competitors
• Checking naming consistency and linking mentions to definitive entity pages
• Finding and fixing orphan entities

Step one applies the Natural Language API to your most important pages. You extract entities, review their salience and check whether they carry a Knowledge Graph identifier. Typical findings include navigation elements outranking core topics, which points to HTML or page structure problems, and inconsistent entity names on the same page. All of these can block proper recognition and should be resolved before any schema work.

Step two runs the same analysis on a handful of competitors to find entity gaps. Fewer core entities mean weaker authority signals, and missing related concepts mean fewer of the topical connections LLMs draw on for comprehensive answers. The aim is to understand which entity patterns drive citations and to find angles competitors have not yet covered. Copying them is not the point. Step three focuses on consistency and relationships. A site search for your primary entity shows whether you refer to yourself in several different ways, such as a legal suffix in one place and a generic product label in another, which confuses recognition. Each mention should link to a definitive entity page so Google can build a graph from your content. The lesson also explains orphan entities: things you mention across the site but never define on a dedicated page. These break the chain, because LLMs have no clear source to cite. The target is consistent naming, every mention linked to its hub, and no orphans.

This lesson belongs to the first core module, Understanding Entity-Based Search in the LLM Era. It follows the hands-on Knowledge Graph lesson and leads into correction strategies. It suits SEOs and content teams preparing to audit a site’s entity foundations before investing in structured data.