The Unified Framework: Connecting Knowledge Graphs, Entity Search, and Search Insights for Topical Authority

This framework is a systematic process for designing content that is retrievable by AI, aligned with entities, and engaging for humans.

It's a dual-path process:

1. Brand & Content Architecture: Brand Ontology -> Taxonomy -> Content Hubs Architecture -> AI Chunks + Human Writing.

2. User & Search Alignment: Entity Search -> Query Mapping -> Persona/Sentiment/SERP Matching -> Measure & Refresh.

Let's break down each pillar step-by-step, using a practical example: a company (like Atomic Mass Games) that sells a tabletop miniature game (Star Wars: Legion).

Pillar 1: Build Your Brand Ontology (The Master Schema)

Before we can write a single word, we must define our universe. 

An ontology is a formal map of your domain's concepts (entities) and the relationships between them. For our example, we don't just have one; we have four that we must build and then merge.

1. The Brand Ontology: This is your company. Who are you? It includes your legal entity, founders, key people, brand reputation, partners, and business units.

2. The Product Ontology: This is what you sell. For Star Wars: Legion, this includes Factions (Galactic Republic, Rebel Alliance), Eras (Age of Rebellion), Unit Types (Commander, Operative), specific SKUs (Ahsoka Tano unit, 501st Legion set), and rules.

3. The Lore Ontology: This is the world your product lives in. For Star Wars, this includes Characters (Skywalker lineage), Species (Wookies, Togruta), Planets (Hoth, Tatooine), Organizations (Jedi Order), and key Events (Clone Wars, Battle of Yavin).

4. The Hobby Ontology: This is what customers do with your product. For miniature wargaming, this is the "I-want-to-do" intent. It includes Painting Techniques (basecoating, layering, Non-Metallic Metal), Tools (brushes, airbrush), and Processes (assembling, priming, varnishing) and playing strategies and tactics.

The Magic: Merging Your Knowledge Graphs

This is the most critical step. Having four separate knowledge graphs (KGs) is good. Merging them into one unified "semantic backbone" is game-changing.

We do this through entity matching. We establish sameAs links to connect the dots (or, better, skos:exactMatch, skos:closeMatch, owl:equivalentClass, owl:equivalentProperty).

• For example: The Anakin_Skywalker_Unit (from the Product KG) is sameAs the StarWars:Anakin_Skywalker_Character (from the Lore KG).

• This unit (from the Product KG) can be painted with Acrylic_Paintings (from the Hobby KG).

• This character (from the Lore KG) participatedIn the Clone_Wars (from the Lore KG).

By discovering and inferring these new relationships, we create a unified graph that can answer incredibly complex, high-intent questions, aka the very kind of questions users are now asking AI.

Example Query: "Show me all the 'Rebel Alliance' units from the 'Age of New Republic' era and the recommended 'contrast paints' for their miniatures."

No single blog post can answer that. But a system built on a merged ontology can. This allows us to inform content clustering, related product features, and content gap analysis at a strategic level.

However, remember also these essential tasks:

1. Ground the ontology on real-world knowledge. In my example, we should involve domain experts like product managers and competitive painters.

2. Plan for recurring maintenance because new techniques emerge, new products are released, and Lucasfilm produces new movies, series, video games, etc 

Pillar 2: From Ontology to Taxonomy (The User Map)

Your ontology is your abstract map. Your taxonomy is the user-facing navigation and site architecture that brings it to life.

Stop basing your taxonomy only on your manufacturing catalogue. A list of "Unit expansion," "Commander expansion," and "Battle Force pack" is logical for a factory, but it's not how a customer thinks.

Instead, use your merged ontology to create alternative, meaningful ways to navigate. Because you mapped your units (Product) to their lore events (Lore), you can now create a navigation menu called "Shop by Battle":

• Kashyyyk: Wookie Warriors, Yoda, B1 Battle Droids

• Scarif: Jyn Erso, Cassian Andor, Rebel Commandos, Imperial Shoretroopers

• Hoth: Blizzard Force, General Veers, Snowtroopers, T-47 Airspeeder

• Endor: Ewok Warriors, Han Solo, Darth Vader

This taxonomy, aligned with your ontology, becomes a powerful map. It reinforces topical depth, clarifies your domain expertise, creates pages that act as semantic gateways, and anticipates how users will actually explore your topic.

Pillar 3: Advanced Query Expansion (Smarter Research)

Classic keyword research is failing us. It’s too narrow and misses the vast majority of user intents. It's time to move on from classic keyword research and embrace query expansion.

Our goal is to map the full semantic intent related to our entities. We find this in the wild:

• People Also Ask (PAA): These are expanded queries, a prototype of query fan-out.

• Topic Filters: The clickable bubbles in Google Search (e.g., "Expansion," "Reviews," "Price").

• People Also Search For (PASF): The "next step" in a user's journey.

• Image Search Tags: A visual ontology of related concepts and attributes.

• AI Mode/Overviews and LLMs Query Fan-Out.

By scraping and analyzing these sources for an entity like "Rebel Commandos," we don't just get "Star Wars Legion Rebel Commandos price." We get a full spectrum of user intents (as seen on Slide 53):

• Comparative: "Rebel Commandos vs Rebel Pathfinders comparison"

• Counter-Strategy: "How to counter Imperial Death Troopers with rebel commandos"

• Tactical Guidance: "best upgrade cards for rebel commandos"

• Value Assessment: "Are rebel commandos worth their points?"

• Hobby Guidance: "Star Wars Legion Rebel Commandos Painting Guide"

• Hobby Customization: "Best color scheme for Endor rebel commandos"

• Lore: "lore behind rebel specforce commandos"

This is our real search ecosystem for developing a relevant content strategy.

Once we have retrieved our Search Ecosystems, we must execute the two following tasks to make it “work” with our merged Knowledge Graph:

1. NER for entity extraction:

   1. Sabine Wren, Cassian Andor, Proton charge, Slapchop...

2. Normalization of intents/questions:

   1. “how to (assemble, paint...)”

   2. ”best paint scheme for...”

   3. “rules clarification for...”

   4. ”comparison with...”

Pillar 4: Designing the Content Hub Architecture

Now, we connect the pillars. We map the unstructured data from our Search Insights (Pillar 3) against the structured, contextual framework of our knowledge graph (Pillar 1).

• Query data shows a high volume of searches for "Cassian Andor" in relation to "Rebel Commandos."

• Our KGraph confirms this relationship: Rebel Commandos -> Is_Related_To -> Cassian Andor.

The search data prioritizes the relationships that our ontology already defines. We now know we must create content about this specific synergy.

This allows us to design a complete, resilient content hub architecture. 

For our "Rebel Commandos" entity, the hub looks like this:

• Pillar Page: Star Wars: Legion Rebel Commandos Ultimate Guide

  • Gameplay Cluster: "Unit Guide: Rules & Keywords," "Best Loadouts: Snipers vs. Saboteurs," "Competitive List with Cassian Andor"

  • Painting Cluster: "How to Paint Rebel Commandos: Step-by-Step," "3 Easy Camouflage Schemes (Endor, Scarif)," "Basing Your Commandos"

  • Lore Cluster: "The Heroes of Scarif: Lore Behind the Commandos," "Rebel Alliance Special Forces in Canon"

This model is contextually interlinked by default, justified by search data, and provides complete topical coverage.

Pillar 5: Advanced Clustering (The Expert Level)

A great topical content hub is not enough. We must go deeper and cluster our content by three advanced layers: intent, format, and persona.

1. Clustering for Intent (The Full Journey) We map our content directly to the "I-want-to..." micro-moments, covering the entire messy middle.

• I Want to Know (Theoretical): "Who are the Rebel Commandos in Star Wars Canon?" (Lore)

• I Want to Know (Practical): "Which units synergize best with Commandos?" (Tactics)

• I Want to Go: "Rebel Alliance Unit Expansions" (A category page)

• I Want to Do: "How to paint Rebel Commandos for the Scarif scenario?" (Hobby guide)

• I Want to Buy (Need Help): "Are Rebel Commandos worth it in the 2025 meta?" (FAQ/Analysis)

• I Want to Buy (Know What): The Rebel Commandos product page (PDP).

2. Clustering for Format (The SERP) To every micro-moment corresponds a set of dominant SERP features. Our content must match the format users expect.

• An "I-want-to-know" (comparative) query like "Commandos vs. Pathfinders" demands tables and snippetable text for easy comparison.

• An "I-want-to-do" (hobby) query like "How to Paint Rebel Commandos" demands video blocks, image blocks, and step-by-step guides.

• An "I-want-to-buy (need help)" query like "Are they worth it?" demands discussion/forum blocks and long-form text analysis. If the SERP is 80% video, you cannot win with a 3,000-word article alone.

3. Clustering for Persona & Sentiment (The Human Layer) This is the most crucial layer. Search queries, especially conversational ones, are packed with emotional context. Effective content responds to the implied sentiment.

A "New Player" and an "Expert Painter" might type the same query but have completely different needs.

• Query: "Are Rebel Pathfinders worth it in 2025 meta?"

  • New Player Sentiment: Reassurance/Anxiety. ("Am I wasting my money?")

  • Expert Painter Sentiment: Curiosity/Interest. ("Are they iconic enough to be a fun painting project?")

Our content must be able to answer both. The "New Player" needs a clear "Yes/No" and a simple pros/cons list. The "Expert Painter" is looking for inspiration, lore connections, and conversion (kitbashing) ideas.

Pillar 6: Practical Content Creation (Format for AI, Write for Humans)

Finally, we create the content following these simple rules:

• Format for AI: Apply the inverted pyramid not just to the whole page, but to every section. Give the core answer/takeaway first, then the supporting detail. Use clear headings (H2, H3), bullet points, and tables to create distinct, retrievable "chunks" for AI models.

• Use Schema Correctly: Use @id fields and proper types (like WebPage, Article, HowTo, Product) to build a consistent semantic web across your site. This isn't about rich results; it's about facilitating parsing and indexing.

• Signal E-E-A-T: Treat Experience, Expertise, Authoritativeness, and Trust as a semiotic framework. These are signals of credibility. We show them by referencing named entities, attributing techniques to recognized practitioners, and using specific, precise language.

• Write for Humans: This is the most important rule. Use plain, approachable language. Favor an active voice. Avoid jargon.

• Share What Only Humans Can: AI can summarize what already exists. It cannot tell personal stories, offer contextual judgment, share firsthand experimentation, or articulate failure and inspiration. Your unique artistic methods, team experiences, and behind-the-scenes insights are the only things AI cannot synthesize. This originality is what makes your content "worth quoting," not just "worth summarizing."