How I Got the Knowledge Graph Panel from Google

On May 1, 2026, my nearly 90-day journey to get my name into Google’s Knowledge Graph Panel finally came to an end. I successfully obtained a Person entity record in the Google Knowledge Graph.

Google Knowledge Graph is a semantic database used to store entities, their relationships, and attributes. It was introduced in 2012 based on data from Freebase. Today, the Knowledge Graph serves as Google’s repository of facts and data collected from Wikipedia, Wikidata, IMDb, Goodreads, Google’s own services (such as Google Maps and Google Business Profile), and many other third-party data providers.

Here is how my name appears in the Knowledge Graph Panel:

You can verify it here.

For those unfamiliar with it, the Google Knowledge Panel is an information card (a visual showcase of structured data) that appears in search results for a brand, entity, or person.

This is an example of a more advanced search result displaying a description and images directly in Google Search.

If you read articles online about getting into the Knowledge Graph, you will usually see recommendations such as publishing in trusted media outlets and having a Wikipedia or Wikidata entry.

That is why my case is particularly interesting, as I managed to get into the Knowledge Graph without using:

• Wikidata
• Wikipedia
• Trusted media publications
• IMDb manipulation techniques
• Publishing a book
• A musician profile (many people use MusicBrainz)

It’s worth noting something for those who obtained a Knowledge Panel years ago.

A few years ago, it was relatively easy to obtain a Knowledge Panel by publishing an audio file through Google Podcasts, but the service was shut down in 2024 and this loophole disappeared.

Many well-known SEO specialists from CIS countries who had a Google Knowledge Panel actually obtained it through this method.

How Did I Do It?

I used a set of trusted websites that Google relies on when building its Knowledge Graph.

Here is a small list:

ResearchGate.net
Featured.com
ProvenExpert.com
Crunchbase.com
HelpAReporter.com
About.me
ORCID.org
Hackernoon.com
Issuu.com
Google Scholar

Among the most important platforms are Google Scholar, Crunchbase, and ORCID. Google treats these websites as trusted sources and uses them to verify entities.

I did not treat these platforms as a simple collection of backlinks. Instead, I assigned each one a specific role in building my entity profile:

About.me — the core identity hub: establishes the primary description, name, and profession, creating the initial anchor point for the entity.

Crunchbase — activity verification database: reinforces professional status, projects, and relationships, serving as a source of structured information about a person.

ORCID + Google Scholar + ResearchGate — a unified professional and academic profile block: connects a name with publications, citations, and research activities, strengthening topical authority and helping Google recognize the same entity across multiple scientific and professional systems.

Featured — expert profile: creates a public description of competencies and strengthens consistency across professional representations.

Hackernoon — publishing platform: generates textual mentions and expands the entity’s digital footprint across the open web.

Issuu — publication archive: adds indexable documents and articles, increasing entity visibility through structured content.

What does verification mean? Google needs a way to distinguish between entities, especially people who share the same first and last name. To achieve this, Google uses Named Entity Recognition (NER), a technology that extracts named entities and their attributes from text.

What is an attribute? For example, it can be your date of birth. Information is stored as triples, such as:

Evhen Moldovanu was born in 1986.

Using these triples, Google can identify specific entities because different people have different birth dates, biographies, educational backgrounds, and so on. To ensure attribute accuracy, Google typically looks for at least three independent confirmations across trusted sources.

Google also tries to identify a trusted (canonical) source for an entity. This can be your website, LinkedIn profile, Facebook profile, or YouTube channel. This helps Google reconcile data when information is incomplete or inconsistent.

It is also useful to implement Schema markup. Adding structured data such as Person or Organization to your official website can strengthen entity understanding.

I created a dedicated page describing my entity using Person Schema.

The page serves several purposes:

• Strengthens E-E-A-T signals on the website.
• Provides an entity description for AI chatbots.
• Contains an extended Person Schema.

I also created additional pages on my website containing various structured data implementations. For example, you can see one here.

I also built hub pages and interlinked all profiles. The reason was simple: because much of the content was generated with AI chatbots, indexing was often weak, requiring the use of indexing services.

Timeline of Obtaining a Knowledge Graph Panel (Less Than 90 Days)

The following information is essential for inclusion in the Knowledge Graph:

• 🔘 First and Last Name
• 🔘 Date of Birth
• 🔘 Place of Birth
• 🔘 Biography
• 🔘 Education
• 🔘 Occupation / Profession

How to Check Whether You Are in Google Knowledge Graph

The first method is to use the official Knowledge Graph API.

Open the link and you will see a result like this:

Submit a query and you will receive:


{
"@context": {
"@vocab": "http://schema.org/",
"resultScore": "goog:resultScore",
"EntitySearchResult": "goog:EntitySearchResult",
"detailedDescription": "goog:detailedDescription",
"goog": "http://schema.googleapis.com/",
"kg": "http://g.co/kg"
},
"@type": "ItemList",
"itemListElement": [
{
"@type": "EntitySearchResult",
"result": {
"@id": "kg:/g/11z004p72k",
"name": "Evhen Moldovanu",
"@type": [
"Person"
]
},
"resultScore": 24
}
]
}


The code shows that an entity named Evhen Moldovanu of type Person has been found.

kg:/g/11z004p72k is the KGMID.

KGMID (Google Knowledge Graph ID) is a unique alphanumeric identifier assigned by Google to a specific entity (person, company, place, or concept) within its semantic knowledge network.

You can try searching for your own entity using different spellings, transliterations, and name variations. The order of first and last name matters.

In the Knowledge Graph, resultScore represents Google’s confidence score or relevance rating for a specific query.

Since the API interface is not particularly user-friendly, you can use my tool for searching Google Knowledge Graph. It uses the same official API but provides free public access.

Mistakes I Made

I could probably have entered the Knowledge Graph twice as fast (it took me about 90 days), but I made several mistakes:

• I occasionally created conflicting records and incorrectly specified entity attributes.
• I did not link all of my social media profiles together, which helps Google identify verified sources more quickly.
• I used photos generated by Gemini (Nano Banana) based on my real images. It turned out Google does not seem to favor this approach, especially because such images contain a SynthID watermark.
• The biggest mistake was failing to fully merge my multilingual entities: Evhen Moldovanu, Евгений Молдовану, and Євген Молдовану. Google apparently did not have enough trusted sources to confidently combine them into a single entity.

Despite all these challenges, I successfully obtained a Google Knowledge Graph Panel record completely free of charge and without manipulation. However, it is important to understand that the panel currently satisfies only the minimum requirements and could disappear at any time. That is why further entity building and reinforcement are still necessary. But that’s a topic for future posts.