Semantic Content Writing Rules are a comprehensive set of guidelines developed from Koray Tugberk GÜBÜR's Algorithmic Authorship framework. These rules govern how content should be structured, written, and optimized so that search engines can extract meaning, map entities, and rank pages based on semantic relevance rather than keyword density alone. For an introduction to key terminology, see the Semantic SEO Glossary.

Quick Stats: Comprehensive Writing Rules | 8 Categories | Based on Koray's Framework | Practical Examples Included

This guide organizes all rules into 8 thematic categories—from macro-context principles to sentence-level optimization and authorship signals—with real-world examples demonstrating each rule in practice. Explore all semantic SEO resources to deepen your understanding.

1. Semantic Precision & Authorship Signals

These rules focus on the micro-level precision of content delivery—ensuring certainty, contextual word choice, numeric specificity, and authorship verification. Mastering these rules differentiates expert-level content from generic, AI-generated output.

Rule 1: Be Certain — Eliminate Hedging Verbs

Avoid using sentences with "should," "need to," "might," or "could." Replace hedging verbs with factual, declarative statements. Certainty signals expertise and improves the content's information retrieval score.

Correct: "The sun rises every day."

Incorrect: "The sun will rise tomorrow."

Why: Hedging verbs introduce semantic uncertainty. Search engines process factual declarations as authoritative, while conditional language reduces the confidence score of the passage.

Rule 2: Use Contextual Relevance in Word Choice

Ensure all words in a paragraph have contextual relevance to the section's topic. Every term contributes to the contextual vector. Unrelated vocabulary dilutes the semantic signal and confuses entity recognition models.

Correct: In a paragraph about health, use words like "symptom," "treatment," "diagnosis," and "prognosis."

Incorrect: In a paragraph about health, using words like "investment," "download," or "architecture" without semantic justification.

Why: Contextual relevance directly impacts how search engines build the contextual vector for a passage. Off-topic vocabulary weakens the entire paragraph's relevance score.

Rule 3: Use Numeric Values — Not Vague Quantities

Use specific numbers, percentages, or exact quantities instead of vague terms like "several," "many," or "a lot." Precision signals that the author possesses expert-level knowledge.

Correct: "There are 5 main benefits of using a vision board."

Incorrect: "There are several benefits of using a vision board."

Why: Numeric specificity enables search engines to generate structured data (e.g., list snippets, knowledge panels) and signals factual authority. Vague quantities are an E-E-A-T negative signal.

Rule 4: Understand the Context of Verbs

Use verbs that signal the appropriate semantic domain. Verbs carry contextual meaning—"develop" signals a technology or security context, "treat" signals a health context, "invest" signals a financial context. Mismatched verbs break the contextual vector.

Example: Use "develop" when discussing software security, "treat" when discussing medical conditions, "cultivate" when discussing agriculture.

Why: Search engines use verbs as contextual anchors to disambiguate entities. "Apple develops" triggers a technology context; "Apple grows" triggers an agriculture context. Verb selection directly impacts entity disambiguation.

Rule 5: Give Examples After Plural Amounts

When stating a plural amount, provide specific examples immediately following the count. This satisfies both the user's need for a summary and their need for detail—improving responsiveness and featured snippet eligibility.

Correct: "There are 7 rare symptoms of this condition, such as fatigue, nausea, and dizziness."

Incorrect: "There are 7 rare symptoms of this condition." (no examples provided)

Why: Examples after plural quantities create multi-entity coverage within a single passage. This increases passage-level entity density and improves the content's information retrieval completeness.

Rule 6: Use Part-of-Speech Tags for Structured Lists

Structure lists with appropriate verb instructions at the beginning of each item. Consistent part-of-speech tags (POS tags) improve syntactic parsing and signal clear, actionable information.

Correct:

  • Do the preliminary keyword research
  • Create the topical map structure
  • Measure the contextual coverage
  • Validate entity-attribute completeness

Incorrect: Mixing "Creating," "You should research," "The measurement of," and "Validate" in the same list.

Rule 7: Optimize Subordinate Text After Conjunctions

Ensure the text after conjunctions like "if," "when," "because," and "although" is responsive and actionable. Subordinate clauses carry conditional information—make them informative, not vague.

Correct: "If you want to improve your sleep efficiency, here are 3 tips: maintain consistent timing, reduce blue light exposure, and optimize room temperature."

Incorrect: "You can improve your sleep efficiency by doing these things."

Why: Responsive subordinate text creates featured snippet opportunities for conditional queries ("if I want to..."). Vague subordinate text wastes the conditional context without providing extractable information.

Rule 8: Match Anchor Text to Target Page Title

Align anchor text with the target page's H1 or title tag. The anchor text signals to search engines what the linked page is about. Mismatched anchors create conflicting contextual signals between source and target pages.

Correct: Use "Semantic SEO Glossary" as anchor text linking to a page titled "Semantic SEO Glossary."

Incorrect: Use "click here for terms" as anchor text linking to the same page.

Why: Anchor text acts as an external entity annotation for the target page. When anchor text matches the target's title, it reinforces the page's macro context across the semantic content network.

Rule 9: Do Not Delay the Answer

Provide the key information upfront. Delaying the answer with introductory fillers, background context, or rhetorical questions reduces the content's responsiveness score and frustrates users.

Correct: "The 5 benefits of using a vision board are: clarity, motivation, focus, accountability, and visualization reinforcement. Each benefit operates through..." (answer first, then details)

Incorrect: "Vision boards have been used for decades. Many people have found them helpful. In this article, we will explore..." (delays the answer)

Why: Search engines prioritize passages that provide immediate answers. Delayed answers reduce the passage's featured snippet eligibility and increase the page's cost-of-retrieval for search engines.

Rule 10: Bold the Answer — Not the Search Term

Use bold formatting on the answer section, not on the search query or keyword. Bold text carries contextual weight—it signals to both users and search engines which part of the content is the answer.

Correct: "The 3 main symptoms of this condition are fatigue, chronic pain, and cognitive impairment."

Incorrect: "The 3 main symptoms of this condition are fatigue, chronic pain, and cognitive impairment."

Why: Bolding the answer increases its contextual coverage weight, making it easier for search engines to extract the relevant information for featured snippets and passage ranking.

Rule 11: Make Content Cheaper for Search Engines

Ensure the content is easy for search engines to process at minimum computational cost. Use simple, clear language with direct subject-verb-object structures. Lower cost-of-retrieval improves ranking potential.

How: Use short sentences, avoid nested clauses, maintain one idea per paragraph, and structure using semantic HTML. Pages with lower cost-of-retrieval rank higher when topical authority is equal.

Why: Search engines allocate processing resources based on cost-of-retrieval. Content that requires less processing to extract meaning is preferred over content with equivalent topical coverage but higher extraction cost. Learn more about how this connects to Koray's AI Agents for Semantic SEO.

Rule 12: Increase Query Responsiveness

Focus on providing the correct information to search engines for each query your page targets. Query responsiveness measures how directly your content answers the user's search intent.

Correct: For the query "What are the benefits of using a vision board?" — directly list the benefits with definitions: "The 5 benefits of using a vision board are clarity, motivation, focus, accountability, and visualization reinforcement."

Incorrect: Writing about vision boards in general without directly answering the "benefits" question.

Why: Responsiveness is the measure of how well your content satisfies the specific need behind a query. A page can be topically relevant but not responsive—responsive content ranks higher.

Rule 13: Identify Authorship Signals — Detect AI Content

Use techniques to detect and eliminate AI-generated content patterns. AI-generated content often lacks entity specificity, uses hedging language, repeats generic structures, and fails to provide source citations. Human authorship is identifiable through unique perspectives, precise data, and expert-level domain vocabulary.

AI Content Signals to Avoid:

  • Overuse of transitional phrases ("furthermore," "moreover," "in addition")
  • Generic statements without specific numbers or sources
  • Lack of first-person expert experience or cited authorities
  • Repetitive sentence structures across paragraphs

Why: Algorithmic authorship requires human expert signals. Content that reads as machine-generated fails E-E-A-T evaluation. The key differentiator is specificity, source citation, and domain-expert vocabulary. Need help ensuring your content passes authorship quality checks? Get in touch.

Rule 14: Understand Contextual Connections in Competing Pages

Analyze how words and concepts are connected in top-ranking pages for your target query. Contextual connections reveal the semantic relationships that search engines expect to find in high-quality content.

Example: For the query "ultrasonic cleaning," analyze how words like "ultrasonic," "cleaning," "wave," "frequency," and "cavitation" are connected in top-ranking pages. These contextual connections form the expected semantic pattern.

Why: Search engines build expected contextual patterns from top-ranking documents. Content that matches these contextual connections signals comprehensive coverage. Missing connections signal incomplete topical coverage and reduce ranking potential.

2. Macro Context & Page Focus

These foundational rules ensure every page has a clear, singular topical purpose. Without a defined macro context, search engines cannot accurately classify or rank the content.

Rule 15: One Macro Context Per Page

Each page must focus on a single primary topic (macro context). Combining multiple unrelated topics on one page dilutes relevance and confuses search engine classifiers.

Correct: A page about "What is Topical Authority" focuses entirely on defining, explaining, and exemplifying topical authority.

Incorrect: A page about "What is Topical Authority" that also extensively covers "How to Do Keyword Research" and "Best SEO Tools 2026."

Why: When a single macro context is maintained, the heading vector, entity mentions, and contextual terms all reinforce one relevance signal. Multiple macro contexts create competing signals that reduce the page's information retrieval score.

Rule 16: Define User Intent Before Writing

Before writing any content, identify the primary user intent, target audience, and locale. The macro context, heading structure, and entity coverage must align with the intent behind the query.

Example: For the query "how to build a topical map," the intent is informational-procedural. The content should provide step-by-step instructions, not a product comparison or opinion piece.

Rule 17: Match Macro Context to Query Context

The page's macro context must align with all possible interpretations of the target query. If the query has multiple semantic facets, the content should address each facet within the boundaries of the single macro context.

Example: The query "entity SEO" could mean: (1) optimizing content for entity recognition, (2) using Entity-Attribute-Value models, or (3) building knowledge graph entries. A comprehensive page addresses all three facets under the unified macro context of "Entity SEO."

3. Heading Hierarchy & Document Structure

Headings form the contextual skeleton of your document. Proper heading hierarchy signals the relationship between topics and sub-topics to search engines.

Rule 18: Use H2 Headings as User Questions

Structure H2 headings as direct questions that users would search for. This aligns document structure with query semantics and improves information extraction.

Correct: <h2>What Is Topical Authority in Semantic SEO?</h2>

Incorrect: <h2>Topical Authority</h2>

Why: Question-format headings match search queries more closely, enabling search engines to extract the subsequent paragraph as a direct answer (featured snippet potential).

Rule 19: Never Skip Heading Levels

Follow proper heading hierarchy: H1 → H2 → H3 → H4. Never jump from H1 to H3 or from H2 to H4. Each level represents a contextual layer within the document's semantic structure.

Correct Hierarchy:

H1: Semantic Content Writing Rules
  H2: What Is Macro Context?
    H3: How to Define Macro Context
  H2: What Is Heading Hierarchy?

Rule 20: One H1 Per Page

Every page must have exactly one H1 tag that represents the page's primary topic. The H1 should contain the central entity and primary query terms.

Example: <h1>Semantic Content Writing Rules for Algorithmic Authorship</h1>

Rule 21: Headings Must Reflect Content Beneath

A heading must accurately describe the content that follows it. Misleading headings break contextual flow and reduce the document's information retrieval score.

Common Mistake: Using "Introduction" or "Overview" as H2s. These are contextless labels—replace them with question-formatted headings that carry semantic weight.

4. Extractive Answers & Information Responsiveness

These rules ensure your content directly satisfies the user's query. Responsiveness is not about being relevant—it is about providing the exact answer.

Rule 22: Provide a 40-Word Extractive Answer

Immediately after each H2, provide a concise, approximately 40-word answer that directly responds to the heading question. This is the extractive answer—the passage search engines pull for featured snippets.

Example:

H2: What Is a Topical Map?

"A topical map is a semantic content network structure that organizes content based on source context, central entity, central search intent, core section, and outer section. It connects related web documents to build topical authority through contextual hierarchy and internal linking." (38 words)

Rule 23: Answer All Possible Needs Behind the Query

The web document must satisfy all possible needs behind the query, not just address the surface-level question. This is the difference between relevance (matching topics) and responsiveness (satisfying intent).

Example: For "how to create a topical map," address: what tools are needed, what data to gather, how to structure sections, how to connect nodes, and how to validate the map.

Rule 24: Be Direct — Declaration First

Start sentences with the primary declaration. Place the main information at the beginning of the sentence, not at the end after qualifiers or conditions.

Correct: "Topical Authority requires both topical coverage and historical data."

Incorrect: "When we consider the various factors and elements that contribute to building an online presence, it becomes clear that topical authority requires both topical coverage and historical data."

5. Entity & Attribute Coverage

Entity coverage is the backbone of semantic content. These rules ensure every relevant entity is defined, connected, and contextualized within the content.

Rule 25: Define Every Entity You Mention

If you mention an entity, you must define it within the content. An undefined entity is an uncovered entity—simply mentioning or stuffing entity names does not count as coverage.

Correct: "A contextual vector is a vocabulary list created with macro-context for each unique term from a domain, based on term occurrences across ranked documents."

Incorrect: "Use contextual vectors and semantic embeddings to improve your content optimization strategy."

Rule 26: Connect Entities to Each Other

Entities must be connected through explicit relationships, not just co-mentioned. Use predicates that explain how Entity A relates to Entity B.

Correct: "The central entity gives its main attributes to the core section and its minor attributes to the outer section of the topical map."

Incorrect: "Central entity, core section, and outer section are important parts of SEO."

Rule 27: Cover Entity-Attribute-Value Completely

For each entity, identify and cover its attributes (properties) and values (specific data). Incomplete EAV coverage means incomplete topical coverage.

Example for Entity "Topical Map":

  • Attribute: Structure → Value: Source Context, Central Entity, Core Section, Outer Section
  • Attribute: Purpose → Value: Organize semantic content network for topical authority
  • Attribute: Creator → Value: Koray Tugberk GUBUR

Rule 28: Use Factual Information Over Opinion

Prioritize factual, verifiable statements over personal opinions, analogies, or everyday language. Experts provide facts, definitions, and data—not speculation.

Correct: "BM25 calculates relevance using term frequency (TF) and inverse document frequency (IDF)."

Incorrect: "I think BM25 is basically like a scoring system that sort of figures out which pages are better."

6. Sentence & Paragraph Optimization

These micro-level rules govern how individual sentences and paragraphs are constructed for maximum semantic clarity.

Rule 29: Use Short Sentences

Short sentences increase clarity and reduce ambiguity for both readers and NLP models. Long, nested sentences create parsing difficulties and scatter relevance across multiple clauses.

Correct: "Topical coverage is determined by the structured process of information. Each entity must be defined and connected. Missing definitions mean missing coverage."

Incorrect: "Topical coverage, which is one of the two components of topical authority and is determined by the structured process of information on web documents that are designed for possible and related search activities, requires that each entity must be properly defined and connected because missing definitions would mean missing coverage."

Rule 30: Cut Contextless Words

Remove words that carry no semantic weight. Filler words, vague qualifiers, and unnecessary transitions dilute the contextual density of your content.

Words to remove: "basically," "actually," "in order to," "it is important to note that," "as a matter of fact," "needless to say"

Rule 31: Do Not Break Context Across Paragraphs

A single context must be completed within one paragraph. Do not split a definition, explanation, or argument across multiple paragraphs—this fragments the contextual vector and weakens relevance.

Rule 32: Proper Word Sequence Matters

Word order affects how relevance is distributed across entities. The subject position carries the highest prominence.

Example: "Search engines use semantic analysis to rank pages" gives prominence to search engines. "Semantic analysis is used by search engines to rank pages" gives prominence to semantic analysis. Choose word sequence based on which entity you want to emphasize.

Rule 33: Understand the Context of Verbs (Predicates)

Verbs carry contextual signals. "Analyze," "examine," and "investigate" may seem synonymous, but each activates a different semantic frame. Choose predicates that match the specific context of your topic.

Example: "Google crawls pages" vs "Google processes pages" vs "Google indexes pages" — each predicate signals a different stage of the search pipeline.

Rule 34: Avoid Starting Sentences with "If"

Sentences starting with "if" create conditional structures that delay the main declaration. Place the declaration first, then add the condition if necessary.

Correct: "Content configuration is required when semantic distances change after a core update."

Incorrect: "If semantic distances change after a core update, content configuration is required."

7. Contextual Flow & Content Network

These rules govern how content flows within a page and connects to other pages in your semantic content network.

Rule 35: Maintain Linear Contextual Flow

Content should flow linearly from macro-context to micro-context. Start with the broadest definition, then progressively narrow into specific details, examples, and sub-topics.

Flow: Definition → Components → How it works → Examples → Related concepts

Rule 36: Separate Main Content from Supplementary Content

Main content processes the macro-context with all context-terms and main entities. Supplementary content touches micro-contexts and provides internal links to side-topics.

Rule: Main content should not contain too many internal links unless they are within the macro-context. Internal links to related but different topics belong in the supplementary content section.

Rule 37: Use Contextual Bridges Between Sections

When transitioning between sections, use contextual bridges—sentences that connect the previous topic to the next topic. Avoid abrupt topic changes that break the reader's contextual flow.

Rule 38: Hub-and-Spoke Internal Linking

Structure internal links following the hub-and-spoke model. The root document (hub) links to node documents (spokes), and spokes link back to the hub. This propagates topical authority throughout the semantic content network.

Example: A "Semantic SEO Guide" (hub) links to "What Is Topical Authority" (spoke), "How to Build Topical Maps" (spoke), and "Entity-Attribute-Value in SEO" (spoke). Each spoke links back to the hub.

Rule 39: Contextual Coverage Weight Through Typography

Use bold, headings, and lists to adjust contextual coverage weight. A term that appears in a heading or bold text carries more contextual weight than the same term in regular body text.

8. Quality, Precision & Validation Rules

These rules ensure the content meets the highest standards of factual accuracy, contextual precision, and semantic completeness.

Rule 40: Be Certain — Avoid Hedging Language

Present information with certainty. Hedging language ("might be," "could possibly," "it seems like") reduces the authority signal of your content.

Correct: "Topical Authority requires topical coverage and historical data."

Incorrect: "Topical Authority might require topical coverage and could possibly also need historical data."

Rule 41: Use Numeric Values — Be Specific

Experts are specific. Use exact numbers, percentages, and quantities instead of vague qualifiers like "many," "several," or "a lot."

Correct: "Koray Tugberk GUBUR has created 48 AI agents across 9 categories."

Incorrect: "Koray has created many AI agents across several categories."

Rule 42: Cite Sources and Authorities

Always cite the source or authority before making a claim. This strengthens E-E-A-T signals and provides factual anchoring for your statements.

Correct: "According to Koray Tugberk GUBUR, topical authority is ranking over an authoritative website with lower cost-of-retrieval."

Incorrect: "Topical authority means ranking well against competitors."

Rule 43: Avoid Opinions, Analogies, and Everyday Language

Semantic content must be factual and precise. Opinions introduce subjectivity, analogies introduce unrelated semantic domains, and everyday language lacks the specificity needed for semantic processing.

Rule 44: Expand Evidence with Variations and Examples

After stating a fact or definition, provide multiple examples and variations that demonstrate the concept in different contexts. This increases contextual coverage and strengthens entity understanding.

Rule 45: Use Same POS Tag for List Item First Words

When creating lists, start each item with the same part of speech (noun, verb, adjective). This maintains syntactic consistency and improves readability for both humans and parsers.

Correct (all verbs):

  • Define the macro context
  • Identify the central entity
  • Structure the heading hierarchy
  • Write extractive answers

Incorrect (mixed POS):

  • The macro context definition
  • Identify the central entity
  • Good heading hierarchy
  • You should write extractive answers

Rule 46: No Rhetoric Without Information

Every sentence must carry informational value. Rhetorical questions, generic motivational statements, and vague introductions waste contextual space without providing semantic signals.

Avoid: "Have you ever wondered what makes great content? In today's digital landscape, content is king and everyone knows that good content matters..."

Rule 47: Optimize the First Words of Paragraphs

The first words of each paragraph carry disproportionate weight in semantic processing. Start paragraphs with informative, contextually relevant terms—not filler phrases.

Correct: "Contextual hierarchy adjusts a context's coverage weight through typography and visuals."

Incorrect: "It is also worth noting that contextual hierarchy adjusts a context's coverage weight."

Advanced & Implementation Rules

These final rules cover advanced optimization techniques for publication, structured data, and content network management.

Rule 48: Implement Structured Data for Key Entities

Use JSON-LD structured data (Schema.org) to explicitly declare entities, their types, attributes, and relationships. Structured data helps search engines map your content directly to their knowledge graph.

Rule 49: Optimize Images with Subject and Object Entities

Every image should have a subject entity (the most prominent object) and object entities (contextual elements). Alt text, file names, and surrounding text must reference these entities.

Rule 50: Maintain Publication Frequency (Momentum)

Regular publication signals an active, growing content network to search engines. Momentum, combined with vastness and depth, determines how quickly you can build topical authority.

Rule 51: Configure Content After Algorithm Updates

After each Broad Core Algorithm Update, reconfigure content based on changed semantic distances and similarities. Content configuration is an ongoing process, not a one-time optimization.

Rule 52: Use Contextual Borders Between Sections

The transition from main content to supplementary content must be gradual, not abrupt. Use contextual border sections that slowly shift from macro context to micro context.

Rule 53: Align Anchor Text with Synonym Value

Internal link anchor text should contain the central entity with synonym value. Avoid generic anchors like "click here" or "read more"—each anchor must carry semantic weight.

Correct: <a href="...">Topical Authority in Semantic SEO</a>

Incorrect: <a href="...">Learn more here</a>

Rule 54: Validate Content with Macro and Micro Semantics

Before publishing, audit the content at both levels: macro semantics (site-wide N-grams, heading vectors, heaviest context terms) and micro semantics (word-by-word optimization, sequence modeling, predicate accuracy).

Rule 55: Publish as Part of a Semantic Content Network

No page exists in isolation. Every published page must be connected to your semantic content network through contextual bridges, internal links, and shared entity references. Quality issues in one node affect rankings across the entire network.

Need Help Applying a Topical Map for Your Project?

Implementing these semantic content writing rules requires a well-structured topical map tailored to your niche. I build custom topical maps using Koray's framework — covering entity analysis, contextual vectors, heading hierarchy, and hub-and-spoke internal linking — to help businesses establish topical authority and achieve sustainable rankings.

Explore my Semantic SEO Services or get in touch directly.

Get a Custom Topical Map →

Implementation Checklist

Use this checklist before publishing any content:

  1. Single macro context confirmed for the page
  2. User intent defined and matched to content
  3. One H1 with central entity present
  4. All H2s formatted as user questions
  5. Heading hierarchy follows H1 → H2 → H3 without skipping
  6. 40-word extractive answer below each H2
  7. All mentioned entities are defined and connected
  8. Entity-Attribute-Value coverage is complete
  9. Sentences are short with declarations first
  10. Contextless words removed
  11. No context broken across paragraphs
  12. Facts cited with sources—no opinions or analogies
  13. Contextual flow is linear (macro → micro)
  14. Internal links follow hub-and-spoke model
  15. Structured data implemented
  16. Page connected to semantic content network
  17. All hedging verbs replaced with factual statements
  18. Contextual relevance verified for all paragraph vocabulary
  19. Vague quantities replaced with numeric values
  20. Verb context matches semantic domain
  21. Examples provided after all plural amounts
  22. Anchor text aligned with target page titles
  23. Answers provided upfront — no delayed responses
  24. Bold applied to answers, not search terms
  25. AI-generated content patterns eliminated

Frequently Asked Questions

Semantic Content Writing Rules are guidelines developed from Koray Tugberk GUBUR's Algorithmic Authorship framework. They govern how content should be structured, written, and optimized so search engines can extract meaning, map entities, and rank pages based on semantic relevance.

One macro context per page prevents topic dilution and ensures the page maintains a clear, focused relevance signal. When multiple macro contexts compete on a single page, search engines struggle to determine the primary topic and may rank the page lower for all intended queries.

The 40-word extractive answer rule states that immediately after each H2 heading, you should provide a concise 40-word answer that directly responds to the question. This format is optimized for featured snippets and information extraction by search engines.

These rules are the content-level implementation of Topical Authority. While Topical Authority operates at the site-wide level through semantic content networks, these writing rules ensure each individual page is semantically optimized with proper entity coverage, contextual hierarchy, and information responsiveness.

The core structural rules (macro context, heading hierarchy, extractive answers, entity coverage) should be applied to every page. Advanced rules like contextual border management and content configuration after algorithm updates apply more to comprehensive pillar content and ongoing optimization.