Wikidata, Wikipedia, and Knowledge Graph entity engineering

Originally published at thatdevpro.com. Part of ThatDevPro's open SEO + AI framework library. ThatDevPro is an SDVOSB-certified veteran-owned web + AI engineering studio. Open-source AI citation toolkit: github.com/Janady13/aio-surfaces.

Establishing Entities in Google's Knowledge Graph — Wikidata, Wikipedia, and the Entity Web

A comprehensive installation and audit reference for establishing a business and its key entities in Google's Knowledge Graph, claiming and managing the Knowledge Panel, building reciprocal entity reconciliation across the web, and maintaining the entity authority that compounds across rankings, AI engines, and brand search results. This document is dual-purpose: installation manual and audit document.

Cross-stack implementation note: the code samples in this framework are written in plain HTML for clarity. For React, Vue, Svelte, Next.js, Nuxt, SvelteKit, Astro, Hugo, 11ty, Remix, WordPress, Shopify, and Webflow equivalents of every pattern below, see framework-cross-stack-implementation.md. For pure client-rendered SPAs (no SSR/SSG) see framework-react.md. For Tailwind-specific concerns (purge, dynamic classes, dark-mode CLS, focus accessibility) see framework-tailwind.md.

1. Document Purpose & How to Use This Document

1.1 What This Document Is

This is the canonical reference for establishing entities in Google's Knowledge Graph (KG). The Knowledge Graph is Google's database of entities and their relationships — people, places, organizations, products, concepts, events. When Google recognizes an entity in its Knowledge Graph, that recognition manifests as Knowledge Panels in search results, populates AI Overviews, drives entity-based ranking, and feeds the data that LLMs train on.

This framework specifies how to assess current entity recognition status, how to build the foundation for entity recognition (Wikidata being the primary path), how to pursue Wikipedia inclusion when notability supports it, how to claim and optimize the Knowledge Panel when it appears, and how to maintain entity authority over time. It also specifies entity reconciliation — the process by which Google associates external profiles, references, and data points with the canonical entity in its Knowledge Graph.

Entity authority compounds. Every authoritative reference, every Wikidata property added, every Wikipedia mention, every reciprocal external link reinforces Google's confidence in the entity. Conversely, weak or fragmented entity signals leave Google uncertain — and uncertain entities don't get Knowledge Panels, don't rank as authoritatively, and don't get cited by AI engines.

1.2 Three Operating Modes

Mode A — Install Mode: Building entity recognition from scratch or adding to existing presence. Follow Sections 2 → 14.

Mode B — Audit Mode: Evaluating existing Knowledge Graph status. Skip to Section 11.

Mode C — Hybrid Mode: Audit then install for gaps.

1.3 How Claude Code CLI Should Consume This Document

1. Read Section 2 — collect client variables, especially existing entity references
2. Read Section 3 — understand the Knowledge Graph and entity ecosystem
3. Run Section 4 — assess current entity recognition status
4. Install Sections 5-9 — Wikidata first, then external reconciliation, then Wikipedia if notable, then Knowledge Panel claim
5. Validate — Section 11
6. Generate report — Section 14

1.4 Conflict Resolution Rules

1.5 Required Tools

• Wikidata — wikidata.org — primary platform for entity creation and management
• Wikipedia — wikipedia.org — for notable entities
• Google Search Console — to verify Knowledge Panel claim eligibility
• Google Knowledge Graph Search API — developers.google.com/knowledge-graph — to verify entity recognition
• OpenRefine — openrefine.org — for batch entity reconciliation
• Wikidata Query Service — query.wikidata.org — for testing Wikidata entries

2. Client Variables Intake

# ============================================
# KNOWLEDGE GRAPH FRAMEWORK CLIENT VARIABLES
# ============================================

# --- Business Entity (REQUIRED) ---
business_name: ""                    # Canonical name as entity
business_alternate_names: []         # All variations
business_legal_name: ""              # If different from canonical
business_type: ""                    # Schema.org type
business_founded_year: ""
business_founder_names: []
business_founder_qids: []            # Wikidata QIDs if exist
business_industry: ""
business_industry_qid: ""            # Wikidata industry classification
business_headquarters_city: ""
business_headquarters_country: ""
business_official_website: ""

# --- Existing Entity Recognition Status (REQUIRED) ---
business_in_knowledge_graph: false   # Use Knowledge Graph Search API to check
business_knowledge_panel_appears: false  # Search business name; does panel appear?
business_wikidata_qid: ""            # Existing Wikidata entry if any
business_wikipedia_article_exists: false
business_wikipedia_article_url: ""

# --- Founder Entity (REQUIRED) ---
founder_full_name: ""
founder_alternate_names: []
founder_birth_year: ""               # Optional but helps disambiguation
founder_credentials: []
founder_employer_qid: ""             # Wikidata QID for current/founded business
founder_in_knowledge_graph: false
founder_wikidata_qid: ""
founder_wikipedia_article_exists: false

# --- Notability Assessment (REQUIRED for Wikipedia) ---
business_independent_secondary_sources: []  # URLs of substantial coverage in independent publications
business_passes_wikipedia_notability_test: false
founder_independent_secondary_sources: []
founder_passes_wikipedia_notability_test: false

# --- External Profile Inventory (REQUIRED for sameAs reconciliation) ---
business_linkedin_url: ""
business_x_url: ""
business_facebook_url: ""
business_youtube_url: ""
business_github_org_url: ""
business_crunchbase_url: ""
business_bbb_url: ""
business_chamber_of_commerce_url: ""
business_industry_directory_urls: []

founder_linkedin_url: ""
founder_x_url: ""
founder_github_url: ""
founder_huggingface_url: ""
founder_orcid: ""
founder_personal_site_url: ""
founder_other_profile_urls: []

# --- Topical Entity Coverage (RECOMMENDED) ---
primary_topical_entities: []         # Topics covered with topical hub pages
topical_entity_qids: {}              # Existing Wikidata QIDs for major topics

# --- Knowledge Graph Strategy Status (REQUIRED) ---
has_strategy_for_kg_inclusion: false
plans_to_pursue_wikipedia_inclusion: ""  # "yes_now", "yes_when_notable", "no", "uncertain"
plans_to_create_wikidata_entries: false
has_kg_inclusion_timeline: false

# --- Entity Maintenance (REQUIRED ongoing) ---
wikidata_last_reviewed: ""
wikipedia_last_monitored: ""
knowledge_panel_last_audited: ""
external_profile_last_audited: ""

3. What the Knowledge Graph Is

Google's Knowledge Graph is a database of entities and their relationships. Launched in 2012, it powers:

• Knowledge Panels in search results (the boxes on the right side showing entity information)
• Featured snippets and rich results for entity-related queries
• AI Overview source selection — AI Overviews preferentially cite Knowledge Graph entities
• Voice search and assistant responses ("Hey Google, who is...")
• Entity-based ranking — pages associated with recognized entities benefit
• Disambiguation — when multiple entities share names, KG provides the disambiguation infrastructure

The Knowledge Graph contains hundreds of billions of facts about millions of entities. Most is automatically extracted from sources like Wikipedia, Wikidata, government databases, structured data on websites, and news mining. Some is manually curated.

Entity inclusion in the Knowledge Graph isn't binary — it's confidence-based. Google may have very high confidence in well-established entities (Apple Inc, Albert Einstein, Tokyo) and lower confidence in less-established entities. Confidence determines whether Knowledge Panels appear, how prominently the entity features in results, and how authoritatively the entity is treated in AI Overviews.

Entity confidence comes from:

1. Wikidata presence — Wikidata entries are direct input into Google's Knowledge Graph. A complete, well-cited Wikidata entry is the strongest single signal for entity inclusion.

2. Wikipedia presence — Wikipedia articles flow into Wikidata and are direct sources for Knowledge Panels. Wikipedia coverage is a strong signal but has higher notability requirements than Wikidata.

3. Schema markup with sameAs — Schema on the entity's official website that declares sameAs links to authoritative external profiles helps Google reconcile the entity.

4. Citation by other authoritative sources — When other recognized entities reference this entity, confidence increases.

5. Consistent factual data across sources — When the same facts appear across multiple authoritative sources, confidence increases.

6. Structured data accessibility — Sites that expose entity data via schema, API, or other structured formats are easier to ingest into KG.

The 2026 evolution of the Knowledge Graph is significant. AI engines (ChatGPT, Perplexity, Claude, Gemini) all rely on entity data overlapping with Google's KG. Entities recognized in KG get cited more frequently across AI engines. The Knowledge Graph is no longer just for Google search — it's foundational infrastructure for the entire AI search ecosystem.

For any business or individual seeking to be recognized as an authoritative entity in 2026, Knowledge Graph inclusion is foundational — not optional.

4. Current Entity Recognition Assessment

Before pursuing inclusion, understand current status.

4.1 Knowledge Graph Search API Check

Use Google's Knowledge Graph Search API to check if entities are already recognized:

curl "https://kgsearch.googleapis.com/v1/entities:search?query={{ENTITY_NAME}}&key={{API_KEY}}&limit=10"

The response shows whether Google has the entity, its type, description, and confidence score. If the entity returns:

• Strong match (resultScore >100): Entity is well-recognized
• Weak match (resultScore <100): Some recognition but not strong
• No match: No KG presence

For this site's primary entities (business, founder, key topics), document current status.

4.2 Knowledge Panel Search Test

In incognito mode, search for the entity name and document:

• Does a Knowledge Panel appear on the right side?
• What information is in the panel?
• Is the information accurate?
• Is the panel "claimed" (has owner verification)?
• What sources does the panel cite (Wikipedia, official website, etc.)?

Test variations:

• {{exact_business_name}}
• {{business_name}} {{location}}
• {{business_name}} {{founder_name}}
• {{founder_full_name}}
• who is {{founder_name}}

4.3 Wikidata Direct Search

Search Wikidata directly: wikidata.org/w/index.php?search={{ENTITY_NAME}}

Document:

• Existing entries that match
• Existing entries that conflict (other entities with same name)
• Whether existing entry is complete and accurate

4.4 Wikipedia Search

Search Wikipedia: en.wikipedia.org/w/index.php?search={{ENTITY_NAME}}

Document:

• Existing article if any
• Quality and completeness of article
• Whether the article links to the official website

4.5 External Profile Mapping

Document all existing external profiles for the entity. Each profile is a potential sameAs reconciliation point:

business_external_profiles:
  - platform: "LinkedIn"
    url: ""
    verified: false
    matches_official_data: true
  - platform: "X / Twitter"
    url: ""
    verified: false
    matches_official_data: true
  - platform: "Crunchbase"
    url: ""
    matches_official_data: true
  # ... etc

Identify any profiles with mismatched data (different addresses, different founding dates, etc.). These need correction before reconciliation, or they'll undermine entity confidence.

4.6 Recognition Status Summary

After assessment, classify status:

• Established entity — Strong KG presence, accurate Knowledge Panel, complete Wikidata, possible Wikipedia. Focus on maintenance and refinement.
• Recognized but partial — Some KG presence, partial info, no Knowledge Panel or unclaimed panel. Focus on completion and claiming.
• Minimal recognition — Some external profiles but no KG presence. Focus on creating Wikidata entry and reconciliation.
• No recognition — No external profiles, no Wikidata, no KG. Foundation must be built from scratch.

The implementation path varies by status.

5. Wikidata Implementation (Foundation)

Wikidata is the primary path to Knowledge Graph inclusion. Wikidata has a lower notability bar than Wikipedia and is direct input to Google's Knowledge Graph. Every entity that wants KG inclusion should have a Wikidata entry as foundation.

5.1 Wikidata Notability Requirements

To create a Wikidata entry, the entity must satisfy at least one notability criterion:

1. Has a Wikipedia article in any language (automatic notability)
2. Refers to an instance of a clearly identifiable conceptual or material entity (most businesses, people, places qualify)
3. Fulfills a structural need to make statements about other entities

For most businesses and individuals associated with businesses, criterion 2 applies. Notability bar is essentially: is this a real, identifiable entity that people might reasonably want to make statements about?

5.2 Wikidata Account Setup

Create a Wikidata account at wikidata.org. Use a real account with established edit history if possible — accounts with no history can have edits scrutinized more carefully.

Best practice: declare conflict of interest on user page if creating entry for own business or self.

5.3 Creating the Business Entity

Navigate to wikidata.org/wiki/Special:NewItem.

Required initial fields:

Label — {{business_name}} (canonical form, capitalized correctly)

Description — Concise (under 250 char), defining sentence. Examples:

• "American technology company headquartered in Cupertino, California" (Apple Inc.)
• "Service-Disabled Veteran-Owned web development and SEO firm based in Cassville, Missouri" (ThatDeveloperGuy)

Aliases — All alternate names. List every legitimate alternate spelling, abbreviation, DBA name.

After creating the basic entry, populate properties.

5.4 Required Wikidata Properties for Businesses

Add these properties (Wikidata uses property IDs like P31, P17 — find each on Wikidata's property documentation):

Example of a populated business entry:

Item: Q138610626 (ThatDeveloperGuy)
Label (en): ThatDeveloperGuy
Description (en): Service-Disabled Veteran-Owned web development and SEO firm based in Cassville, Missouri

Statements:
- instance of (P31): business (Q4830453)
- country (P17): United States of America (Q30)
- headquarters location (P159): Cassville (Q...)
- founder (P112): Joseph Anady (Q... if created)
- inception (P571): 2020
- industry (P452): web development (Q386275)
- official website (P856): https://thatdeveloperguy.com
- coordinates (P625): 36.6770° N, 93.8730° W

External Identifiers:
- LinkedIn (P4264): {{linkedin_handle}}
- Crunchbase (P2087): {{crunchbase_id}}

5.5 Required References for Each Property

Every statement should be supported by a reference:

inception (P571): 2020
References:
- stated in: official website (P856) of subject
- reference URL: https://thatdeveloperguy.com/about/
- retrieved: 2026-04-29

Without references, statements can be challenged. With strong references, the entry is robust against editor revisions.

5.6 Creating the Founder Person Entity

Same process for founder. Required Person properties:

External Identifier properties for founder:

5.7 Topical Entity Wikidata Entries

For unique topical entities the site is the authority on (specific frameworks, methods, tools the site has created), create Wikidata entries. Most general topics already have entries.

For example, if the site has authored a specific framework called "SDVOSB Engine Optimization Methodology," that could be a Wikidata entity:

Item: Q... (SDVOSB Engine Optimization Methodology)
Label (en): SDVOSB Engine Optimization Methodology
Description (en): A 14-tier framework for search engine and AI engine optimization developed by Joseph Anady at ThatDeveloperGuy

Statements:
- instance of (P31): methodology (Q1799072)
- developed by (P178): Joseph Anady (Q...)
- subclass of (P279): search engine optimization (Q180711)
- depicts (P180): 14-tier framework

5.8 Cross-Linking via External Identifiers

Wikidata's external identifier properties allow direct linking to authoritative external databases. Add as many as apply:

For businesses:

• LinkedIn company ID (P4264)
• Crunchbase organization ID (P2087)
• BBB business profile (... if property exists)
• Industry-specific identifiers (BSI, NAICS code, etc.)

For people:

• LinkedIn personal ID (P6634)
• ORCID (P496)
• Google Scholar author ID (P1960)
• ResearchGate profile (P6178)
• GitHub username (P2037)

External identifiers strengthen entity reconciliation — they tell systems unambiguously that this Wikidata entity is the same entity as in those external sources.

5.9 Wikimedia Commons Logo Upload

Upload the business logo to Wikimedia Commons:

1. Visit commons.wikimedia.org/wiki/Special:UploadWizard
2. Confirm copyright (logo must be licensed permissively or be your own work you license)
3. Upload with descriptive filename: ThatDeveloperGuy-logo.svg
4. Add to Wikidata entry as logo image (P154)

The logo is then available for use in Knowledge Panels and other systems.

5.10 Patience for Wikidata Propagation

After creating Wikidata entries, allow time for propagation:

• 24-72 hours for community visibility
• 1-4 weeks for Google's Knowledge Graph ingestion
• 1-3 months for stable Knowledge Panel appearance (typically requires multiple signals beyond Wikidata)

Don't expect immediate Knowledge Panel from Wikidata alone. Wikidata is foundational; other signals build on it.

6. External Reconciliation Strategy

Beyond Wikidata, build the network of references that reinforce entity recognition.

6.1 Schema sameAs on Official Website

The official website's Organization and Person schema must include sameAs links to all authoritative external profiles AND to the Wikidata entry:

<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://{{domain}}/#organization",
  "name": "{{business_name}}",
  "sameAs": [
    "https://www.wikidata.org/wiki/{{business_qid}}",
    "https://en.wikipedia.org/wiki/{{business_wiki_slug}}",
    "{{linkedin_company_url}}",
    "{{x_company_url}}",
    "{{facebook_url}}",
    "{{crunchbase_url}}",
    "{{bbb_url}}",
    "{{youtube_channel_url}}",
    "{{github_org_url}}",
    "{{industry_directory_urls}}"
  ]
}
</script>

This declares: "All these URLs refer to the same entity." Google uses this for entity reconciliation.

6.2 Reciprocal sameAs from External Profiles

Where possible, add the website URL to external profiles so reconciliation is bidirectional:

• LinkedIn company page: lists official website
• X bio: includes website URL
• Crunchbase profile: official website field
• Personal LinkedIn: lists company and website
• GitHub org/user: website field

Some platforms allow rel="me" markup for verified mutual claiming. Where supported (Mastodon, personal sites), use rel="me" to formally declare the relationship.

6.3 Authority-Building Profile Coverage

Build presence on platforms that contribute to entity authority:

For businesses:

• LinkedIn Company Page
• Google Business Profile
• Crunchbase
• BBB (where applicable)
• Trustpilot
• Industry-specific directories (Clutch for B2B services, etc.)
• Local Chamber of Commerce
• State business registry (already exists if formally registered)

For founders:

• LinkedIn personal profile
• GitHub (for developers)
• Hugging Face (for AI work)
• ResearchGate or ORCID (for academics)
• Industry-specific profiles
• Personal domain with comprehensive bio

6.4 Industry-Specific Authoritative Listings

Each industry has authoritative directories Google trusts:

• Medical: NPI registry, state medical board, hospital staff directory
• Legal: Bar association directory, Avvo, Martindale-Hubbell
• Financial: BrokerCheck, SEC IAPD, Form ADV
• Real estate: NAR, state real estate licensing
• Construction: state contractor licensing, BBB

Listing on these sources contributes to entity authority and provides additional sameAs targets.

6.5 Earned Media Coverage

When the entity is featured in articles, news, or industry publications, ensure:

• The publication's article links to the official website
• The article uses the canonical entity name
• The article references factual data consistent with Wikidata/official sources

Inconsistencies across earned media weaken entity confidence. Reach out to publications to correct factual errors when they appear.

6.6 Press Kit With Canonical Entity Data

Maintain a press kit at /press/ with canonical entity facts:

• Official entity name and acceptable abbreviations
• Founding year
• Founder names with correct spellings
• Headquarters location
• Industry classification
• Brief description (matching Wikidata description)
• High-resolution logos
• Founder photos
• Recent press releases

Make it easy for journalists to use correct facts. Inconsistent facts in earned media create entity confusion that takes time to resolve.

7. Wikipedia Strategy

Wikipedia has a higher notability bar than Wikidata. Don't pursue Wikipedia until notability is genuinely demonstrable.

7.1 Wikipedia Notability Test

Wikipedia's notability requirement: "significant coverage in independent reliable secondary sources."

Tests:

• Significant coverage — multiple paragraphs about the entity, not just passing mention
• Independent — not the entity's own marketing, press releases, or affiliated sources
• Reliable — established publications with editorial standards (newspapers, trade publications, academic journals, books)
• Secondary sources — not primary sources like the entity's own website or interviews

For most businesses, Wikipedia notability requires:

• Coverage in 3+ independent reliable sources
• Coverage that's substantive (not just listings or brief mentions)
• Coverage spanning more than a single time period

For most individuals, similar tests but framed around the person's accomplishments, work, recognition.

If notability is genuinely there, Wikipedia inclusion follows. If it's not, attempting to create a Wikipedia article will result in deletion, often with administrative rebuke that makes future attempts harder.

7.2 Don't Create Your Own Wikipedia Article

Wikipedia has strong policies against creating articles about yourself or your business (conflict of interest). Articles created by COI editors are flagged, scrutinized, often deleted.

Better path:

1. Build genuine notability over time
2. Wait for organic article creation by an independent editor
3. If asked, provide factual support to editors but don't draft the article

7.3 If You Must Create a Wikipedia Article

If notability is genuinely strong and no organic editor is creating an article, the legitimate path:

1. Disclose conflict of interest on user page
2. Use Articles for Creation process (en.wikipedia.org/wiki/Wikipedia:Articles_for_creation) rather than direct creation
3. Submit through draft review by uninvolved editors
4. Accept their feedback and revisions

The article must:

• Be written in encyclopedic tone, not promotional
• Cite multiple independent reliable sources
• Cover both achievements and any controversies fairly
• Avoid superlatives, marketing language, original research
• Use neutral point of view

7.4 Maintaining the Wikipedia Article

Once created, monitor the article but don't edit it directly:

• Watch for changes via Wikipedia's watchlist feature
• Use Talk page to suggest corrections with citations
• Engage with editors who request information
• Provide source materials when requested
• Accept that the article belongs to Wikipedia community, not the subject

Inappropriate editing of own Wikipedia article causes:

• Edit reverts
• Articles flagged for COI review
• Sometimes article deletion
• Editor account sanctions

7.5 What Wikipedia Inclusion Adds

When/if Wikipedia article exists:

• Knowledge Graph confidence increases dramatically
• Knowledge Panel typically appears in search results
• AI engines cite the entity more confidently
• The Wikipedia article becomes input into many derivative systems (LLM training data, AI knowledge bases, etc.)

Wikipedia is force-multiplying for entity authority. But it must be earned, not engineered.

8. Knowledge Panel Claiming

Once an entity has Knowledge Graph recognition, claim the Knowledge Panel for control.

8.1 Verifying Eligibility

Knowledge Panels can be claimed when:

• The entity is recognized in Google's Knowledge Graph (Knowledge Panel appears)
• You can demonstrate official representation (own the website, are the entity, or are authorized representative)

To check if a Knowledge Panel exists for your entity, search the entity name in Google. The panel appears on the right side (desktop) or below results (mobile).

8.2 Claiming Process

If a Knowledge Panel exists:

1. Click "Claim this knowledge panel" link in the panel (typically at bottom)
2. Sign in with Google account
3. Verify ownership through one of:
   • Authorized social profile (verified Twitter/X, official LinkedIn, etc.)
   • YouTube channel
   • Official Twitter/X account
   • Other verified Google service
4. Wait for Google review (typically days to weeks)

Once claimed, you can:

• Suggest edits to information in the panel
• Add or update images
• Request corrections to factual errors
• Update social profile links

8.3 Maintaining the Knowledge Panel

After claiming:

• Monthly: review panel for accuracy
• After business changes (address, hours, name): suggest update
• After credentials/awards: suggest addition
• Quarterly: verify all linked profiles still active

8.4 What If No Knowledge Panel Exists

If no Knowledge Panel exists despite Wikidata presence and external profile coverage, possible reasons:

• Recognition exists but below threshold for panel display
• Entity is too new (give it 3-6 months after building foundation)
• Entity confusion (Google can't disambiguate from other entities with same name)
• Insufficient cross-source consistency

Continue building entity signals: more authoritative external profiles, more earned media, more consistent factual data across sources, possibly Wikipedia inclusion if notability allows. Knowledge Panel typically follows when entity confidence reaches threshold.

9. Topical Entity Strategy

Beyond business and founder entities, topical entities matter.

9.1 Major Topic Wikidata Entries

Most major topics (web development, SEO, AI, etc.) already have Wikidata entries. Reference them in your content schema:

<script type="application/ld+json">
{
  "@type": "Article",
  "about": [
    {
      "@type": "Thing",
      "name": "Search engine optimization",
      "sameAs": "https://www.wikidata.org/wiki/Q180711"
    }
  ]
}
</script>

Topical hub pages similarly use the Wikidata QID for their primary topic.

9.2 Custom Methodology Entities

If the site has authored unique methodologies, frameworks, or tools, create Wikidata entries for them. See Section 5.7.

9.3 Person-Topic Affinity

Connect people entities to topical entities via Wikidata:

For founder entry, add:

• field of work (P101): SEO QID
• field of work (P101): Web development QID
• field of work (P101): AI optimization QID

This declares topical authority in Wikidata, which compounds with on-site knowsAbout schema.

10. Common Mistakes & Anti-Patterns

10.1 Self-Created Wikipedia Article

Anti-pattern: Creating own Wikipedia article without notability.

Why it fails: Almost certainly deleted. Editor account sanctioned. Future legitimate attempts harder.

Fix: Build notability first. Use Wikidata in the meantime. Wait for organic Wikipedia creation.

10.2 Inconsistent Entity Names Across Sources

Anti-pattern: "ThatDeveloperGuy" on website, "That Developer Guy LLC" on LinkedIn, "TDG Inc" on Crunchbase.

Why it fails: Google can't reconcile these as the same entity. Entity confidence stays low.

Fix: Pick canonical name. Use consistently everywhere. Document acceptable variations as alternateName only.

10.3 Wikidata Without References

Anti-pattern: Wikidata entry created with statements but no supporting references.

Why it fails: Entry is fragile; community editors may revise or remove unsupported statements.

Fix: Cite sources for every statement.

10.4 No Schema sameAs

Anti-pattern: Site has Wikidata entry, but Organization schema doesn't include sameAs link to Wikidata.

Why it fails: Google has to reconcile via other means; loses easy direct signal.

Fix: sameAs link to Wikidata in all relevant schema.

10.5 Sparse External Profile Coverage

Anti-pattern: Only website and one social profile. Nothing else.

Why it fails: Entity reconciliation needs multiple signals. Sparse coverage means low confidence.

Fix: Build coverage on 8-15 authoritative platforms.

10.6 Outdated Wikidata Information

Anti-pattern: Wikidata entry created years ago, never updated. Address has changed, founder roles changed, founding date inaccurate.

Why it fails: Inconsistent data across sources weakens entity confidence.

Fix: Quarterly Wikidata review; keep current.

10.7 Edit Warring on Wikipedia

Anti-pattern: Repeatedly editing your own Wikipedia article to add favorable content.

Why it fails: Article flagged for COI review. Editor account sanctioned. Trust damaged.

Fix: Use Talk page to suggest changes. Provide sources. Let community editors decide.

10.8 Knowledge Panel Errors Ignored

Anti-pattern: Knowledge Panel showing wrong information, no action taken.

Why it fails: Wrong information at the most prominent position in search results. Long-term reputation damage.

Fix: Claim panel; suggest corrections; provide source documentation for corrections.

10.9 Multiple Wikidata Entries for Same Entity

Anti-pattern: Creating new Wikidata entry without checking if one already exists, resulting in duplicates.

Why it fails: Confusion. Statements split across entries. Reconciliation issues.

Fix: Search before creating. If duplicates exist, use Wikidata's merge process.

10.10 Trying to Game Knowledge Graph

Anti-pattern: Creating fake Wikipedia citations, manipulating Wikidata, fabricating earned media to inflate entity authority.

Why it fails: Detection by Wikipedia community is high. Wikidata has data quality processes. Fabricated earned media is detectable. Caught manipulation = catastrophic reputation damage.

Fix: Build genuine entity authority through real work, real notability, real recognition.

11. Audit Mode

11.1 Knowledge Graph Status Audit

Score: 15. World-class KG status: 13+/15.

11.2 Entity Authority Strength Score

For each primary entity (business, founder, key topics), score:

Per entity: 21 max. Strong entity: 18+/21.

12. Maintenance Schedule

12.1 Monthly

• Verify Wikidata entries still accurate; correct if facts changed
• Monitor Wikipedia article for changes (if exists)
• Check Knowledge Panel for accuracy
• Review external profiles for consistency

12.2 Quarterly

• Comprehensive entity authority audit
• Update press kit with new earned media, achievements
• Refresh photos and logos if updated
• Cross-check NAP across all profiles

12.3 Annually

• Strategic entity review
• Pursue new Wikipedia inclusion if notability has grown
• Add new topical entities as the site's authority expands
• Update Wikidata with significant year's developments

12.4 Event-Driven

• Address change → update everywhere within 7 days
• Founder change → update Wikidata, Knowledge Panel, schema
• New significant earned media → add to press kit, update Wikidata reference
• New award/certification → update credentials in Wikidata, schema, About page

13. Cross-Reference to the 14-Tier Framework

Knowledge Graph implementation touches:

• Tier 3 KGO — Knowledge Graph Optimization is named for this exact work
• Tier 3 WIK — Wikipedia & Wikidata Optimization is the foundational work this framework specifies
• Tier 1 SDO — Structured Data Optimization implements schema sameAs for KG reconciliation
• Tier 1 EEA — E-E-A-T Entity Optimization with Person/Organization schema
• Tier 4 PBO — Personal Brand Optimization extends founder entity work
• Tier 4 CHO — Citation/Honors Optimization documents the awards and recognitions that build entity authority

14. Implementation/Audit Report Templates

14.1 Implementation Report Template

# Knowledge Graph Implementation Report

**Site**: {{BUSINESS_NAME}}
**Implementation Date**: {{TODAY}}

## Wikidata Entries Created
- Business: {{QID}} — {{COMPLETENESS_PERCENTAGE}}% properties populated
- Founder: {{QID}} — {{COMPLETENESS_PERCENTAGE}}% properties populated
- Custom methodologies: {{LIST_OF_QIDS}}

## External Reconciliation Status
- Schema sameAs links: {{COUNT}}
- External profiles claimed: {{COUNT}}
- NAP consistency: {{PERCENTAGE}}% across all profiles

## Knowledge Panel Status
- Business: {{APPEARS/DOES_NOT_APPEAR}}, {{CLAIMED/UNCLAIMED}}
- Founder: {{APPEARS/DOES_NOT_APPEAR}}, {{CLAIMED/UNCLAIMED}}

## Wikipedia Status
- Notability assessment: {{ASSESSMENT}}
- Action: {{NONE/ARTICLE_CREATED/ARTICLE_AWAITED}}

## Topical Entity Coverage
{{LIST_OF_TOPICS_AND_QIDS}}

## Press Kit Established
{{STATUS}}

## Sign-Off

14.2 Audit Report Template

# Knowledge Graph Audit Report

**Site**: {{BUSINESS_NAME}}
**Audit Date**: {{TODAY}}

## Overall KG Status
{{ESTABLISHED / RECOGNIZED_PARTIAL / MINIMAL / NONE}}

## KG Status Score
{{X}}/15

## Entity Authority Strength
- Business: {{X}}/21
- Founder: {{X}}/21
- Primary topics: {{ASSESSMENT}}

## Wikidata Findings
{{DETAILED_FINDINGS}}

## Wikipedia Findings
{{DETAILED_FINDINGS}}

## External Reconciliation Findings
{{DETAILED_FINDINGS}}

## Knowledge Panel Findings
{{DETAILED_FINDINGS}}

## Critical Failures
{{LIST}}

## Recommended Implementation Order
{{PRIORITIZED_LIST}}

## Sign-Off

End of Framework Document

Document version: 1.0
Last updated: 2026-04-29
Maintained by: ThatDeveloperGuy

Knowledge Graph inclusion is foundational entity authority infrastructure for 2026. Without it, entities operate at a permanent confidence disadvantage in search rankings, AI citations, and brand recognition. With it, every other quality signal compounds — E-E-A-T is stronger when the entity is recognized, content ranks better when its primary entity is authoritative, AI engines cite the entity preferentially.

The work is methodical. Wikidata first. External reconciliation. Wikipedia when notable. Knowledge Panel claim. Then maintain. The compound returns over time are substantial.

Companion documents:

• framework-eeat.md
• framework-ymyl.md
• framework-hcs.md
• framework-sqrg.md
• framework-coreupdates.md
• framework-infogain.md
• framework-entitysalience.md
• framework-aicitations.md

About this framework library

This article is the Dev.to republish of a framework reference document from ThatDevPro's SEO + AI engineering library. Canonical source: https://www.thatdevpro.com/insights/framework-knowledgegraph/

ThatDevPro is an SDVOSB-certified veteran-owned web + AI engineering studio operating from Cassville, Missouri. The studio runs the full 14-tier Engine Optimization stack and ships open-source tooling for AI citation engineering.

Companion 14-tier Engine Optimization stack (each tier is its own article):

1. Tier 1 — Foundation
2. Tier 2 — Search Visibility
3. Tier 3 — AI Domination
4. Tier 4 — Entity and Authority
5. Tier 5 — Local Domination
6. Tier 6 — Content and Multimedia
7. Tier 7 — Social and Community
8. Tier 8 — Data, Analytics, Conversion
9. Tier 9 — Monitoring and Intelligence
10. Tier 10 — Workflow and Operations
11. Tier 11 — Marketplace and Retail
12. Tier 12 — International
13. Tier 14 — Advanced and Immersive

Need this framework implemented on your site? See the Engine Optimization service or hire through ThatDevPro contact.