---
language: en
title: "Knowledge graph"
description: "A knowledge graph represents entities and relationships using a defined structure and vocabulary. Learn how to check identity, connections, and data sources."
canonical: "https://tropk.ai/en/resources/glossary/knowledge-graph"
last_modified: "2026-10-12T16:10:06.990Z"
---

# Knowledge graph

Reviewed on 2026-10-07.

## What it means

A knowledge graph is a structured representation of entities and the relationships between them. An organization may manufacture a product, which belongs to a category and has a version. The graph makes these connections explicit using identifiers and a defined vocabulary. In RDF, one way to represent relationships is with triples consisting of a subject, predicate, and object.

## Why it matters for marketing

For marketing, this structure helps organize facts about brands, offers, and people without confusing their roles. When requesting a graph of their own, the team needs to decide which questions it should answer and which sources support its connections. An attractive visual connection is not enough: relationships without a defined meaning can lead to incorrect associations in later queries.

## Practical example

Imagine a distributor that offers equipment from three manufacturers. Its catalog lists the distributor’s name and the brands, but does not distinguish who manufactures each product. The team creates separate “distributes” and “manufactures” relationships, linked to official product pages. When asked who manufactures a piece of equipment, it can verify the relationship and correct the misattribution.

## How to apply or verify

Check [entity](/en/resources/glossary/entity) identifiers, relationship types, and the source of each claim. Test queries that follow relevant connections, such as product and manufacturer, and review duplicate names. Record dates and those responsible for maintenance. In the example catalog, a change of manufacturer requires updating the corresponding relationship and preserving evidence from the previous period.

## Important distinctions

A graph of your own is not the Google Knowledge Graph; a [knowledge panel](/en/resources/glossary/knowledge-panel) is a surface for presenting information in Search. [Schema.org](/en/resources/glossary/schema-org) provides a vocabulary, not a prepopulated graph. Publishing [JSON-LD](/en/resources/glossary/json-ld) does not guarantee inclusion in Google's graph. Graphs also differ from models' [parametric memory](/en/resources/glossary/parametric-memory), and you should not assume that every AI system queries one.

## Sources and references

- [RDF 1.1 Concepts and Abstract Syntax](<https://www.w3.org/TR/rdf11-concepts/>) — W3C
- [About knowledge panels](<https://support.google.com/knowledgepanel/answer/9163198?hl=en>) — Google
- [About Schema.org](<https://schema.org/docs/about.html>) — Schema.org

## Continue a leitura

- [Entity](</en/resources/glossary/entity>)
- [JSON-LD](</en/resources/glossary/json-ld>)
- [Schema.org](</en/resources/glossary/schema-org>)

## About the author

[Vinicius Pacheco](</en/team/vinicius-pacheco>)

Responsible for Tropk’s technical content, focusing on crawling, indexing, structured data, and agent access to content.

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