Configuration Guides — Giyunu Gepiwa

Core Guides

Knowledge Graph and Schema

Visual diagram of Knowledge Graph entity nodes and relationship connections

Foundational 12 min read

Understanding the Knowledge Graph: Structure and Scope

Google's Knowledge Graph is not a single database — it's a federated system that draws from multiple sources including Wikidata, Wikipedia, Freebase (now largely absorbed), and Google's own crawled data. This guide explains its architecture, how entities are represented as nodes, and how relationships between entities are stored as edges with typed predicates.

The Knowledge Graph is queried when Google needs to understand what a search is about, not just which documents contain the query terms. That shift from document retrieval to entity retrieval is the fundamental change this guide unpacks.

Entity nodes Relationship edges Federated sources Query understanding

Developer examining JSON-LD schema markup code on monitor in studio environment

Schema 9 min read

Schema Markup as Entity Communication

Schema markup in JSON-LD format is the most direct way a webpage can communicate entity information to Google. This guide explains how schema.org types map to Knowledge Graph entity categories, which properties carry the most signal weight, and how Google processes structured data during indexing.

Particular attention is paid to the LocalBusiness type hierarchy, Organization properties, and the sameAs property — which explicitly links a webpage entity to its counterparts in external knowledge bases like Wikidata.

JSON-LD format LocalBusiness types sameAs property Wikidata linking

Research paper on entity salience scoring spread open on a studio desk with annotations

Patents 15 min read

Entity Salience: What the Patent Actually Describes

Google's entity salience patent describes a method for scoring how central an entity is to a document. A document where a business is the primary subject has high salience for that entity. A document that merely mentions the business in passing has low salience.

This guide walks through the patent's claims in plain English, explains the scoring mechanism as described, and discusses what observable search behaviors appear to align with the described system. The guide is careful to distinguish between what the patent claims and what can be inferred about live behavior.

Salience scoring Document centrality Content structure Patent analysis

Advanced Guides

Wikipedia, Wikidata, and External Signals

Wikipedia as an Entity Corroboration Source

Wikipedia doesn't just provide backlinks. When Google finds a Wikipedia article about an entity, it uses that article as a high-confidence corroboration of the entity's existence, category, and key attributes. This guide explains the mechanism, including how Wikipedia's structured data (Wikidata) feeds directly into the Knowledge Graph.

Notability signals Entity corroboration

Wikidata and the sameAs Bridge

Wikidata is a structured knowledge base that Wikipedia draws from. It's also one of the primary external sources for Google's Knowledge Graph. A Wikidata entry for your business, properly linked via sameAs in schema markup, creates a direct bridge between your web presence and Google's entity database.

Wikidata Q-codes sameAs linking

NAP Consistency as an Entity Signal

Name, address, and phone number consistency across the web is often discussed as a local SEO tactic. At a deeper level, it functions as an entity disambiguation signal. When multiple sources report the same NAP data, Google can more confidently assign mentions to the correct entity node in its graph.

NAP consistency Disambiguation

Knowledge Panel Signals and What Triggers Them

Knowledge Panels appear when Google is confident enough about an entity to display a structured summary. This guide examines what signals appear to influence Knowledge Panel triggering, based on documented Google behavior and patent descriptions of entity confidence scoring.

Knowledge Panels Confidence scoring

Local Business Guides

Entity Clarity for Local Businesses

A

Google Business Profile as an Entity Anchor

A verified Google Business Profile is the most direct entity signal available to local businesses. It creates a confirmed entity node in Google's system with a verified location, category, and name. This guide explains what GBP data feeds into the Knowledge Graph and how to think about profile completeness from an entity perspective.

B

Category Selection and Entity Classification

Google Business Profile categories are not just organizational labels. They map to entity types in Google's classification system. Choosing an overly broad category creates ambiguity. Choosing a specific, accurate category gives Google a precise entity type to work with. This guide examines how category signals propagate through entity understanding.

C

LocalBusiness Schema: Properties That Matter

Not all LocalBusiness schema properties carry equal weight in entity communication. This guide identifies the properties that appear most significant in entity recognition based on patent descriptions and documented Google behavior: name, address, telephone, url, sameAs, and geo coordinates.

D

Co-occurrence Signals and Geographic Entity Relationships

When your business name appears consistently alongside neighborhood names, city names, and geographic landmarks in web content, Google builds a geographic entity relationship. This guide explains how co-occurrence signals contribute to local entity understanding, with reference to Google's documented approach to geographic entity disambiguation.