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Knowledge Atom Field Dictionary (Opinion/Data/Evidence/Case/Method): Required Fields, Naming Rules & Citation Standard | AB客
AB客 provides a practical field dictionary for five types of knowledge atoms—Opinion, Data, Evidence, Case, and Method—covering required fields, naming conventions, and citation requirements (source type, public availability, timestamp, scope, definitions, limitations, owner, and versioning) to improve AI readability and team reuse in GEO programs.
In GEO (Generative Engine Optimization), knowledge atoms are the smallest traceable units of enterprise knowledge that can be read, extracted, cited, and audited by AI systems (e.g., ChatGPT, Perplexity, Gemini) and reused consistently across FAQs, expert content, and distribution channels.
This page (by AB客) provides a practical field dictionary for five atom types—Opinion, Data, Evidence, Case, Method—including required fields, naming conventions, and a citation standard designed for AI readability and team-scale reuse in external-facing GEO programs (especially for B2B export-oriented organizations).
Why a Field Dictionary Matters in AI Search
AI systems don’t “rank pages” the same way traditional search does. They assemble answers from a knowledge network and prefer information that is well-defined, scoped, timestamped, and verifiable.
- A field dictionary makes each atom consistent (same structure, same meaning).
- Citation rules make atoms traceable (source, availability, scope, limitations).
- Versioning keeps reuse auditable across content updates and multi-language publishing.
Knowledge Atom Types (5) and When to Use Each
| Atom type | Purpose (AI-friendly intent) | Typical use in GEO content |
|---|---|---|
| Opinion | A clearly scoped viewpoint or judgment with boundaries and rationale | Positioning statements, expert takes, decision principles, evaluation criteria |
| Data | A measurable value with definition, unit, and scope | Specs, benchmarks, metrics, controlled comparisons (only when verified) |
| Evidence | A verifiable proof point that supports a claim | Certifications, audit trails, regulatory documents, public references |
| Case | A bounded scenario describing context → action → outcome (with limits) | Implementation notes, lessons learned, constraints, applicability guidance |
| Method | A repeatable procedure or checklist with inputs/outputs | SOPs, playbooks, QA steps, content operations, governance workflows |
Note: avoid mixing multiple atom types in one record. One atom should represent one primary intent to maximize AI extractability and internal reuse.
Global Required Fields (Apply to All Atom Types)
These fields ensure each knowledge atom is traceable, scoped, and maintainable:
| Field | Required | What to write (standard) | Why it helps GEO |
|---|---|---|---|
| atom_id | Yes | Stable unique ID (do not reuse) | Supports referential integrity across content and versions |
| atom_type | Yes | Opinion / Data / Evidence / Case / Method | Improves extraction and routing to correct templates |
| title | Yes | Short, descriptive, non-marketing label | Enables precise citation and deduplication |
| owner | Yes | Person/team accountable for updates | Ensures governance and auditability |
| version | Yes | Semantic version (e.g., 1.0 → 1.1) | Prevents silent changes across reused content |
| created_at / updated_at | Yes | ISO timestamp; updated on any substantive change | Adds recency signals and supports “as of” statements |
| scope | Yes | Applies to what product/market/region/language/timeframe | Reduces hallucinated generalization; improves precision |
| definition_notes | Recommended | Key terms, measurement definitions, assumptions | Makes atoms interpretable by humans and machines |
| limitations / counterexamples | Recommended | Where this atom does not apply, known constraints | Boosts trust by showing boundaries and falsifiability |
| source | Yes | Source type, public availability, link/path, captured time | Enables citation, verification, and compliance review |
GEO rule of thumb: if an atom cannot be traced back to a source (even internal), it may be useful for brainstorming, but it should not be treated as a cite-ready knowledge asset.
Naming Conventions (Stable, Searchable, Reusable)
Recommended pattern
Use a predictable structure so atoms can be found and merged across teams and languages:
[Domain] / [Topic] / [AtomType] / [Scope] / [KeyClaimOrMetric] / v[Version]
Required naming rules
- One title = one atom: avoid bundling multiple claims.
- No marketing language: keep titles descriptive and verifiable.
- Include scope words when ambiguity is likely (region, timeframe, product line, audience).
- Version is part of identity: if the meaning changes, increment version and keep history.
Citation Standard (Traceable Fields for AI-Ready Knowledge)
A citation in a knowledge atom is not only a URL. It is a verification package that answers: Where did this come from, when was it true, what exactly does it mean, and where does it apply?
| Citation field | What it must include | Notes for governance |
|---|---|---|
| source_type | Public web / internal doc / contract / lab test / compliance record (choose one) | Enforce controlled vocabulary to avoid ambiguity |
| public_availability | Public / private / NDA-limited | Prevents accidentally publishing non-public materials |
| locator | URL, file path, repository ID, or record number | Must be accessible to the intended reviewers |
| timestamp | Captured date; and “valid as of” if time-sensitive | Required for specs, prices, policies, performance claims |
| scope | Market/region/language/product model/user segment | Avoids over-applying a local rule globally |
| definitions & metric notes | Units, calculation, inclusion/exclusion criteria, test conditions | Makes data interpretable and comparable |
| limitations / counterexamples | Known constraints, failure modes, exceptions | Improves trust; supports safe reuse in FAQs |
| owner & update policy | Responsible person/team; review frequency or trigger | Ensures atoms don’t become stale “zombie facts” |
| versioning | Version number; change summary; link to previous version | Supports audits and multi-channel consistency |
Operational note for GEO teams:
If a source is not publicly available, the atom can still exist for internal reasoning and controlled sales enablement, but it should be tagged for restricted use to prevent accidental publication and to keep external content citable.
Type-Specific Required Fields (Opinion / Data / Evidence / Case / Method)
Opinion atom
- claim: the opinion stated as a single sentence.
- rationale: reasoning and assumptions.
- applicability: where it applies (scope) and for whom.
- limitations: when the opinion should not be used.
Data atom
- metric_name: unambiguous metric label.
- value + unit: numeric value with unit.
- measurement_method: how it was measured or calculated.
- conditions: test conditions / timeframe / environment.
Evidence atom
- evidence_item: what the evidence is (document, certificate, record).
- issuer / authority: who issued it.
- verification_path: how to verify (public registry link, reference number, internal process).
- validity: effective date, expiration, applicable models/locations.
Case atom
- context: industry, customer type, constraints.
- action: what was done (steps or decisions).
- outcome: results stated carefully with scope and timeframe (avoid over-claims).
- transferability: what must be true for similar outcomes.
Method atom
- inputs: prerequisites, tools, data required.
- steps: ordered procedure (SOP-style).
- outputs: what is produced and how success is checked.
- quality_checks: review gates, responsible roles, rollback plan.
How AB客 Uses This in a B2B GEO Program
In AB客’s foreign trade B2B GEO solution, knowledge atoms are the building blocks for “AI-understandable” enterprise knowledge. The field dictionary standardizes how teams produce and govern atoms so they can be reused across:
- FAQ systems (customer questions mapped to cite-ready atoms)
- Expert content (opinions supported by data/evidence atoms)
- Multi-language site structures (SEO + GEO-friendly content networks)
- Distribution channels (consistent claims with traceable citations)
This approach supports the GEO goal: moving from “AI cannot understand you” to “AI can cite you reliably,” which is foundational for being included in AI-generated recommendations.
Implementation Checklist (Team-Ready)
- Define controlled vocabularies: atom types, source types, availability tags, scope dimensions.
- Adopt naming rules: enforce unique titles and version increments on semantic changes.
- Make citation mandatory for externally publishable atoms; tag restricted atoms clearly.
- Add limitation fields: require “where it does not apply” for high-risk claims.
- Operationalize ownership: each atom has an owner and review trigger (policy updates, spec changes, new market entry).
Practical Use
Use this field dictionary as your internal standard for creating AI-readable, citable, auditable knowledge assets. When your knowledge atoms are consistent, your FAQ and expert content can reuse the same trusted building blocks—reducing contradictions and improving the chance that AI systems can correctly interpret and cite your information.
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