Source identity
| Field | Recorded value |
|---|---|
| Source type | GitHub source |
| Original record | Janady13/thatstupidcomputer / private/standards/SEO-AIO-Library.txt |
| Date | Not specified in source |
| Repository | Janady13/thatstupidcomputer |
| Revision | 57555cde46910102dd25d6c1c1fb2c359e9655bd |
| Branch | main |
| Path or archive member | private/standards/SEO-AIO-Library.txt |
| Original SHA-256 | c6febf4b0a1e694d2753ff702c0688e92e7cafb9158ec3b92368ed488634fe7f |
| Git blob SHA | 4bf06ecb5ebbc46b401270161bf034c373e1d486 |
| Reading-copy SHA-256 | c6febf4b0a1e694d2753ff702c0688e92e7cafb9158ec3b92368ed488634fe7f |
Recovered source transcript
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SEO / AIO GRAPH SYSTEMS — RESEARCH AND IMPLEMENTATION EXPANSION
============================================================
Release: 2026.09.12-g40
Research review date: September 12, 2026
Intended use: accurate human instruction and evidence-led AI-assisted implementation.
Status: a researched library expansion, not a deployed website or live graph audit.
READ THIS FIRST
---------------
This expansion defines 40 selected graph types, representations, and practical graph views. It is not a claim that there are exactly 40 relevant graphs in computer science, that search engines disclose all of their graphs, or that these 40 views are 40 independent ranking systems. Many are different views over one source-linked data model. The names and priorities organize this library; they are not professional certifications or provider-mandated departments.
There are four different kinds of authority here:
1. Documented provider systems, such as Google's Knowledge Graph and Shopping Graph.
2. Standards and protocols, such as RDF, JSON-LD, PROV-O, SKOS, SHACL, and Open Graph.
3. Published methods, such as GraphRAG and HNSW approximate-neighbor indexing.
4. This library's proposed analytical and operating views, including an E-E-A-T evidence graph, a SERP observation graph, and a release-evidence graph.
A standard can define valid structure without certifying truth. A provider can describe a system without exposing its current internals. A useful internal graph can improve consistency without being a ranking factor. Sources S01–S49 are listed at the end and in Research/sources.json; individual cards identify their relevant source basis. Standards are pinned references, not claims that no later specification exists.
1. WHAT THE SUPPLIED LIBRARY ALREADY HAS
--------------------------------------
The supplied TXT is a conversion of 135 embedded documents from the HTML release 2026.09.09-d26. Its R11 charter already requires stable identifiers, truthful Person/business/document distinctions, exact identity links, graph consistency, and claim provenance. The public entity plan already prohibits inventing organizations, credentials, or Wikidata identities. Those foundations are retained.
The supplied master index lists framework-eeat.md, SERP-Optimization.md, and framework-entitysalience.md as legacy, not fully verified. Those index entries are not equivalent to complete, freshly researched graph lessons. The export also references companion artifacts that are not included in the TXT. This expansion does not claim to have recovered or revalidated an unseen original archive.
The additions here are a typed graph catalog; practical personal/business modeling; explicit E-E-A-T and SERP evidence views; private AI-retrieval and governance views; examples and blocked templates; and executable offline package checks. No commercial tier, role number, or original text has been silently rewritten. R11 remains the graph/structured-data lead. R14 governs factual claims; R08 URL contracts; R12 AI observations; R16 measurement; R20 privacy; R24 integration; R25 authorized release; R26 scoped acceptance.
2. START WITH A RELATIONSHIP, NOT A PICTURE
-----------------------------------------
A graph contains nodes and relationships. A typed semantic example is:
[article] --author--> [person]
[article] --publisher--> [organization]
[service] --provider--> [organization]
In RDF, the basic unit is a subject–predicate–object triple; datasets can separate graphs. JSON-LD is one way to serialize linked data using JSON. A visual network diagram is only a view: the useful asset is the inspectable identity, relationship, evidence, and version record. [S12, S13]
For this library, a relationship that makes a material real-world claim must also identify its basis. "Joseph founded Organization A" is not merely a line to draw. It is an assertion requiring the right person, the right organization, an actual founding relationship, and evidence. Ownership, founding, employment, operating a website, publishing an article, and using a brand must not be substituted for one another.
Use a durable entity registry and a separate claim registry. The registry distinguishes things from their documents. A person may have multiple profile pages without becoming multiple people. An organization may publish several websites without those sites becoming the same page. A brand may identify a commercial offering without being a separate legal organization.
Do not infer that an absent fact is false. An unknown founder, office address, credential, or legal name remains unknown. A graph that leaves unsupported attributes empty is preferable to one that invents a complete-looking biography.
3. PERSONAL AND BUSINESS MODEL FOR JOSEPH
---------------------------------------
Joseph's name and the domains ThatDevPro.com and ThatDeveloperGuy.com are user-supplied context. This task has not independently audited their live pages, legal structures, official profiles, ownership evidence, or search-engine recognition. Do not turn the following decision process into published claims without verification.
First establish Joseph's approved public identity and its canonical profile home. Then inventory each actual operating organization, trading name, brand, website, and service. Decide which distinctions are real before choosing types. Keep a register of ambiguities instead of guessing that the two domains are either the same legal business or separate legal businesses.
The proposed logical model is:
Joseph (Person)
↔ actual authored work and approved profile pages
↔ only verified professional or business relationships
Operating organization(s), once established
→ real brand(s), where applicable
→ actual service(s)
→ website(s) and published work
ThatDevPro.com / ThatDeveloperGuy.com (websites)
→ their verified publisher/operator
→ distinct pages and purpose
Choose one stable public identity for a person or organization and reuse it consistently wherever that exact entity is represented. A page's canonical URL and the identity of its subject are separate decisions. Do not migrate an existing identity or page solely because this document shows a cleaner-looking example.
Schema.org's sameAs identifies the same item through an unambiguous reference. It is not an "all my websites" field, an ownership relationship, or a way to borrow authority from related Wikipedia topics. [S04] The packet's example deliberately omits sameAs because no actual third-party identity URLs have been verified here.
For an appropriate biography page, ProfilePage can point through mainEntity to the Person. A real article can reference its actual author and publisher. A real service can reference its provider. ProfilePage is not a universal type for every business landing page. [S03, S07]
Implementation sequence proposed for Joseph:
- Approve actual person, organization, brand, website, and service identities.
- Record evidence and the canonical-home decision before minting production IDs.
- Render approved facts consistently in visible HTML and applicable JSON-LD.
- Check existing public profiles for exact identity, then add only justified identity references.
- Test all selected representations and record engine observations separately.
The general library should retain this decision process and a neutral synthetic example, not hard-code Joseph's private facts into every future client build.
4. THE E-E-A-T GRAPH THAT IS USEFUL TO BUILD
-------------------------------------------
Google discusses experience, expertise, authoritativeness, and trustworthiness as qualities associated with useful content; E-E-A-T itself is not a specific ranking factor. Google does not supply an "E-E-A-T graph" specification or public score for this library to implement. [S01]
Our proposed E-E-A-T evidence view instead asks a concrete question: what supports this particular experience or expertise claim?
claim about capability
→ actual work performed
→ original evidence with scope and date
→ an attributable explanation
→ authorized publication
→ independent corroboration, when it genuinely exists
Examples of defensible inputs are a documented repair, an original design process, a reproducible test, a relevant qualification actually held, or a correction made when evidence changed. A case study must distinguish observed outcomes from causality. A public methodology article can teach a process without pretending that a client engagement occurred.
Store the source owner and whether each mention is owned, paid, syndicated, or independently earned. Two sites owned by the same person can truthfully describe that person's work, but they should not be counted as two independent endorsements merely because they use different domains. The anti-circularity rule is part of this library's evidence design.
Use the view to find unsupported assertions, stale biographies, overbroad claims, missing author responsibility, and public evidence gaps. Do not convert it into an invented Google score or require artificial citations for every sentence. The objective is justified claims and useful instruction, not graph density.
5. THE SERP GRAPH THAT CAN ACTUALLY BE MEASURED
----------------------------------------------
SERP means search engine results page. The proposed graph is an observation model, not an exposed internal search-engine graph. Each result appearance belongs to a snapshot; the same URL appearing twice or in different features should not be flattened into a timeless "ranks for" edge.
Record engine, surface, query, observation time with time zone, language, location setting at the least sensitive useful resolution, device class, collection method, personalization assumptions, result feature, position definition, raw URL, and evidence reference. Unknown values remain null. Do not infer the user's precise location or private search history.
Represent the relationship as:
snapshot --for-query--> query
snapshot --contains--> result occurrence
result occurrence --points-to--> URL
result occurrence --has-feature--> organic / local / ad / other observed feature
Query-to-document graphs are naturally modeled with two node sets; the detailed snapshot design here is our own use of that representation. [S40]
To compare two observed result sets A and B, a simple descriptive overlap is:
Jaccard(A, B) = |A intersection B| / |A union B|
Define whether the members are full URLs, canonical pages, or domains before calculating. Do not mix definitions between comparisons. If the union is empty, record the result as undefined, not as perfect similarity or zero visibility. A position-sensitive metric needs its own explicitly declared weighting and is still not an engine's proprietary weight.
Use overlap to discover candidate clusters and competing answers, then inspect user intent and content. A competitor sharing several results does not prove its schema, page length, or internal-link pattern caused the ranking. A sampled absence is not proof that a website never appears anywhere.
6. AI CITATIONS NEED THEIR OWN OBSERVATION LAYER
-----------------------------------------------
Bing's current AI Performance documentation supports analysis of grounding-query and cited-page relationships and explicitly separates citation observations from ranking, authority, and traffic. Grounding phrases must not be relabeled as the original user prompts. Coverage, aggregation, and denominators matter. [S22, S23]
Keep separate record types for an actual captured answer, an aggregated report row, a citation occurrence, and a source-support assessment. An aggregated report must not be converted into fabricated individual answers. A page cited by an answer may support only one part of that answer; inspect the relevant source passage before asserting support.
Google's current guidance also points to a Generative AI performance report in Search Console. Reconfirm the available report, account coverage, and field definitions before building an importer; a private graph cannot substitute for actual account access. [S21]
Recommended outputs are a dated citation-observation table, a source/claim support map, and a separate referral/lead view. Keep unavailable evidence explicit. Never multiply citation counts by assumed click-through or conversion rates and present the product as measured customers.
OpenAI documents different access roles for search, training, and user-directed retrieval. Treat those as distinct controls and observations. A search crawler's permitted access does not prove that a page was selected or that a private library was learned. [S27]
7. WHAT PUBLIC GRAPHS AND APIS DO NOT GIVE YOU
---------------------------------------------
Google's Knowledge Graph is a documented entity system. Its older Knowledge Graph Search API is read-only, returns matching entities rather than a connected-graph export, includes a migration notice, and warns against a production-critical dependency. An API response score is not a website authority or E-E-A-T measurement. Recheck the current replacement product and terms before designing a new integration. [S10, S11]
Google has also described Shopping Graph and, historically, a Topic Layer associated with Knowledge Graph. These are useful concepts to teach, but historical announcements are not complete current architecture specifications. Merchant data and relevant public content are inputs through supported mechanisms, not an interface for writing arbitrary ranking relationships. [S31, S44]
Wikidata and OpenAlex offer useful public entity and scholarly-data resources. Use them for reference discovery and identifier reconciliation with source and identity checks. Do not create misleading entries, copy unsupported attributes, or treat inclusion as an endorsement. [S36, S37]
Open Graph is the social-preview protocol, not Google Knowledge Graph. Its metadata should be accurate and useful to sharing consumers, but it does not replace your entity or evidence model. [S35]
8. PUBLIC PUBLISHING VERSUS PRIVATE AI RETRIEVAL
-----------------------------------------------
Maintain two deliberate projections of the approved data:
PUBLIC
Actual useful pages, approved identity facts, accurate bylines, applicable
structured data, images, navigation, and supported feeds when relevant.
PRIVATE
Raw evidence, client records, ownership documentation, review decisions,
graph-extraction candidates, source lineage, permissions, tests, and workflows.
Do not publish the private corpus, AGENTS instructions, logs, access tokens, client messages, or inferred relationships to make a graph easier for crawlers to discover. A robots directive is not a substitute for access control.
Google's generative-search guidance does not require special AI files or special schema. Private GraphRAG chunking is an internal retrieval choice, not a reason to break every public article into tiny pages. A custom public /graph.json endpoint should exist only for a named consumer and a reviewed contract, not because it supposedly forces all engines to use it. [S21]
The practical architecture is one governed registry with multiple adapters. Generate selected public facts into HTML and suitable structured data. Use private source-backed records for AI retrieval and audits. Keep public and private storage and authorization boundaries enforceable, not merely decorative visibility labels.
9. GRAPH-RAG IS AN OPTIONAL RETRIEVAL METHOD, NOT AN SEO SWITCH
---------------------------------------------------------------
Microsoft GraphRAG organizes source material using extracted entities and relationships and can combine graph-linked information with original text units. Its documentation describes multiple retrieval strategies. [S24, S25]
For this library, retain the source text and version first. Extract candidate entities, resolve them carefully, and store candidate relationships with provenance. Generated summaries are derived artifacts and inherit restrictions from their sources. They must not become new independent evidence just because another model wrote them.
Evaluate a pilot against ordinary text search and a vector-retrieval baseline using tasks such as:
- Find the current claim and supporting source for one structured-data rule.
- Distinguish a person from an organization with a similar name.
- Retrieve an older rule only when the question concerns the older date.
- Refuse a request to expose private evidence in public markup.
- Identify conflicting source statements without inventing a resolution.
Measure answer support, entity-resolution errors, missed applicable sources, restricted-data leakage, latency, and cost. Do not assume the graph approach wins every task. An HNSW index is a graph of approximate vector-neighbor relationships, not the same thing as a graph of verified facts. [S26]
10. MACHINE-READABLE CLAIM CONTRACT
-----------------------------------
The supplied claim.schema.json is a library record schema, not Schema.org markup. It keeps candidate facts separate from publication approval. The object is either a referenced entity or a literal; the two forms are not interchangeable. Example and candidate records remain intentionally blocked for publication-readiness purposes.
Required concepts include:
claim ID and namespace-qualified predicate;
subject and typed object;
evidence class and source locators;
observation time and effective interval, when known;
status: candidate, supported, disputed, retired, or unknown;
confidence rationale, not an uncalibrated ranking-like number;
owner/source independence classification;
verification state and reviewer record;
private/public-approval state and actual authority to publish;
example flag, review date, and dependent graph views.
The schema can test form. The included Python helper tests a deliberately limited structural readiness policy. Neither can verify that a reviewer is real, that evidence supports a statement, or that a client authorized publication. Human or otherwise genuinely authorized review must evaluate actual evidence. The helper always reports authorization_granted=false.
Changing a candidate to "supported" by editing JSON does not create support. A source URL without a relevant locator does not establish a claim. A copied article with a different URL is not independent corroboration. A missing field must not be filled with a plausible guess solely to satisfy validation.
11. ACCEPTANCE LAYERS
---------------------
Use separate outcomes for separate checks:
A. Record validity: JSON parses; required fields and types are present.
B. Identity consistency: IDs are unique and refer to intended distinct entities.
C. Relationship validity: selected predicates fit the intended meaning.
D. Evidence review: material assertions have relevant source-backed support.
E. Temporal applicability: historical or superseded instructions are not used as current.
F. Privacy and permission: the actual system prevents unauthorized disclosure.
G. Page agreement: public structured data agrees with visible approved facts.
H. Feature eligibility: the current targeted provider requirements are satisfied.
I. Observed discovery: actual crawl/index/result/citation evidence is recorded.
J. Business outcome: actual qualified inquiries or revenue are measured separately.
SHACL provides a standards-based way to check graph constraints; this package supplies a JSON Schema rather than claiming to ship a full SHACL implementation. Neither syntax nor shape conformance proves factual truth. [S16] Public feature validation is a separate task. [S08]
For each required check, retain PASS, FAIL, BLOCKED, or NOT_APPLICABLE with rationale. Missing live access is BLOCKED, not a fabricated pass. A local fixture is not production evidence, and a second pass by the same assistant is not an independent audit.
12. EVALUATION WITHOUT FAKE AUTHORITY SCORES
-------------------------------------------
These are proposed internal quality measures, not search-engine metrics:
Provenance coverage: supported material public claims divided by material public claims in the declared sample. Report the sample, exclusions, and manual-review method.
Identity-resolution precision: reviewed correct accepted matches divided by reviewed accepted matches. Keep ambiguous and unreviewed matches outside the numerator and report their counts separately.
Reference closure: internal references resolving to expected records divided by tested internal references. External URLs require separate checks; they are not unresolved just because they are not nodes in the local graph.
Staleness exposure: number of current-use artifacts depending on claims whose review is overdue under the chosen internal policy. Overdue means review needed, not automatically false.
Contradiction burden: unresolved material disputes and their dependent outputs. Do not hide them in one average confidence score.
Retrieval support rate: sampled answers whose material assertions are supported by the retrieved sources, using an explicit review rubric. This needs actual evaluated answers, not a theoretical score.
For a zero denominator, report undefined or not applicable with reason rather than manufacturing a perfect percentage. Metrics should identify useful next actions, not become optimization targets detached from truth.
13. CURRICULUM AND WORKED CHECKS
-------------------------------
Lesson 1 — Identity versus document.
Exercise: one developer has two websites and three social profiles. How many people exist?
Expected answer: the records may describe one person, but exact matches require evidence. Websites and profile pages are separate entities/documents. Do not infer the number of legal businesses from the number of domains.
Lesson 2 — Exact identity versus relationship.
Exercise: two brands share an owner. Should they be linked with sameAs?
Expected answer: no, not merely for shared ownership. Record the actual relationship and keep their identities distinct. Use sameAs only when the reference unambiguously identifies the same item. [S04]
Lesson 3 — Provenance versus repetition.
Exercise: six articles repeat one press release. How many independent sources support its central claim?
Expected answer: this dataset shows one underlying origin unless independent investigation is demonstrated. Six publication URLs alone do not establish six independent confirmations.
Lesson 4 — Evidence versus E-E-A-T scoring.
Exercise: an AI writes "internationally recognized expert" because the entity graph has many edges.
Expected answer: reject or rewrite the claim unless real evidence supports it. A graph's density is not an expertise credential or an official E-E-A-T score.
Lesson 5 — Snapshot versus timeless ranking.
Exercise: a service page is absent from one mobile result snapshot in one city.
Expected answer: report that bounded observation. It does not establish absence from every search or a causal reason for the result.
Lesson 6 — Citation versus business outcome.
Exercise: a report shows 100 citations but no referral or CRM data.
Expected answer: report the citations with scope. Referral sessions, leads, and revenue are unavailable, not zero and not estimated actuals.
Lesson 7 — Shape versus truth.
Exercise: a valid JSON-LD graph says an invented person earned an invented award.
Expected answer: syntax may pass, but evidence/publication checks fail. A shape validator cannot establish the real-world claim.
Lesson 8 — Retrieval versus publication.
Exercise: GraphRAG finds a useful client email proving an outcome.
Expected answer: use only within authorized private scope; do not publish or disclose it without actual permission and redaction review. A derived summary can still leak confidential content.
Lesson 9 — Time and authority.
Exercise: a fresh blog contradicts an older applicable official specification.
Expected answer: inspect scope, effective dates, and source authority. Freshness alone does not resolve the conflict.
Lesson 10 — Delivery versus discovery.
Exercise: public JSON-LD renders correctly, but there is no engine observation.
Expected answer: report successful delivery checks only. Indexing, panel inclusion, citations, and rankings remain unobserved.
14. IMPLEMENTATION ORDER
------------------------
Priority P0: personal identity; actual organizations/brands; cross-domain relationships; entity resolution; authorship; claim provenance; internal navigation; canonical policy; crawl/render evidence; public representation consistency; acceptance; permissions.
Deliverable: a small approved registry, source-backed claims, limited public projection, and an inspectable test report. Do not publish candidate identities merely to make the graph look complete.
Priority P1: E-E-A-T evidence, reputation, topics, query/page relevance, SERP and AI-citation observation, conversion semantics, Open Graph, curriculum, and workflow routing. Local and migration modules activate when applicable.
Deliverable: useful explanations and evidence, working observation definitions, and isolated public/private data flows. A module marked applicable still needs actual data and tests.
Priority P2: private GraphRAG pilot, vector-neighbor indexing when needed, temporal/supersession controls, contradictions, source-impact mapping, citation projections, and co-occurrence analysis.
Deliverable: measured retrieval comparisons and a maintenance process. Do not choose an infrastructure stack by fashion or a hypothetical SEO boost.
Priority P3: commerce, localization, media, professional/social graphs, scholarly data, and events as the actual website or teaching objective requires.
Deliverable: specialized contracts and truthful data, not empty graph templates represented as deployed capabilities.
These priorities are a proposed dependency order, not provider mandates or a guarantee of search improvement. Preserve original 26-role routing rather than launching 40 independent agents or creating 40 databases.
15. MAINTENANCE AND SOURCE GOVERNANCE
------------------------------------
Every source record needs a title, publisher, exact URL, reviewed date, scope, and limitations. The supplied source register does not pretend that a review date is a publication date or that source pages were archived. Add actual effective dates when established.
Proposed maintenance policy: re-open fast-changing platform guidance before a deployment decision that depends on it; run a periodic change review for provider features; review identity claims when the owner reports a change; and review evidence permissions before every new public use. Select actual scheduling and ownership in the host project. Nothing in this packet installs a scheduler or background monitor.
On change, record the specific altered claim, evaluate applicability, mark affected artifacts for review, test proposed revisions, and publish a bounded changelog. A changed webpage hash is only a signal to inspect; navigation edits are not necessarily policy changes. Keep superseded lessons available as history with their dates, but out of default current-use retrieval.
16. AI PROJECT INTEGRATION CONTRACT
-----------------------------------
Use the existing root AGENTS.md and role router. Add a reference to this expansion only after merging with project instructions; do not replace a real AGENTS.md automatically. This packet includes an integration snippet, not a remote configuration change.
An AI task should receive: the authorized objective; verified site facts; relevant graph IDs; selected role owners; actual read/write limits; current sources; desired public/private outputs; acceptance criteria; and rollback requirements for any approved change. Retrieve only relevant lessons and records rather than loading the whole library as unquestioned authority.
The assistant must distinguish proposed work, actual code changes, locally executed checks, untested external behavior, and live engine observations. It may not fill missing evidence with fictional outputs, self-granted approval, fabricated credentials, or a claim that changing persona made its review independent.
17. PACKAGE SCOPE AND LIMITATIONS
---------------------------------
This release adds the curriculum and machine-readable starting structures. It does not build a production graph database, install GraphRAG, access Joseph's accounts, verify all public profiles, submit search data, deploy markup, edit a live site, or recertify the original 135 documents. The 40 cards are source-linked implementation guides, not completed deployments.
The offline tests inspect this package's records, examples, and limited readiness rules. They do not run live Rich Results tests, search-engine indexing tests, real browser journeys, private-source permissions, or an external independent audit. Those remain requirements for a real implementation.
18. NAMED RESEARCH SYSTEMS AND ALGORITHMS TO KNOW
------------------------------------------------
These names belong in the library because they explain several real graph-based approaches that marketing language often blends together. They are a methods appendix, not five new disclosed ranking factors. Map them into the appropriate Gxx views rather than adding an agent, endpoint, or public score for every name.
Knowledge Vault — probabilistic knowledge fusion.
The 2014 Google Research paper combines extracted web information with prior knowledge and models uncertainty in the fused facts. This is a useful historical basis for teaching extraction, reconciliation, confidence calibration, and source fusion. It is not the same claim as "my site has been entered in Knowledge Vault." [S46]
Library use: connect G04 entity resolution, G09 document/entity mappings, G10 provenance, and G30 contradictions. Keep uncertain extractions out of approved public facts. Calibrated probabilities in a research model are different from an assistant inventing a confidence percentage.
Knowledge-Based Trust (KBT) — fact-based source trust research.
The 2015 paper investigates estimating source trustworthiness from extracted facts while separating extraction mistakes from errors in the source itself. [S45]
Library use: teach why evidence quality and the reliability of extraction must both be examined. A bad parser can make a correct source look inconsistent; a frequently repeated assertion can still be wrong. KBT is not interchangeable with E-E-A-T, link-based trust, or a consumer-visible website score. Do not claim a modern engine uses this exact paper without separate deployment evidence.
TrustRank — seed-guided link analysis for spam detection.
The 2004 paper uses a small expert-reviewed seed set and the web's link structure to identify other pages likely to be reputable. The reviewed paper is by researchers affiliated with Stanford and Yahoo, and its experiments are historical. [S49]
Library use: attach this method to G14 external link analysis and an explicitly labeled research lesson on trust propagation. Explain seed dependence and probabilistic assumptions. Do not substitute "all government sites" or "all university sites" for a demonstrated seed set, and do not translate proximity into a guaranteed modern ranking benefit. The paper is not evidence that the original TrustRank algorithm currently governs Google Search.
HITS — hubs and authorities.
HITS distinguishes hub scores from authority scores for a supplied linked graph; the NetworkX documentation exposes an implementation. [S47]
Library use: compare it with PageRank in a controlled G13/G14 lesson. Show that two algorithms applied to the same small graph answer different mathematical questions. Neither supplies Google's hidden scores. A node labeled "authority" by an algorithm has not acquired a real-world credential or permission to make unsupported claims.
Query–entity click graphs.
Microsoft Research's 2011 Jigs and Lures work models associations between queries and typed entities using click-graph information. [S48]
Library use: enrich G21 query relevance and G26 measurement teaching with a distinction between a query-to-result appearance and an observed click association. Only use actually available, authorized data. Do not invent click logs from rankings or infer a click from a displayed citation. Historical experimental gains are not a promised improvement on another business's site.
A compact comparison:
Knowledge graph: entities and semantic relationships.
Web-link graph: pages and hyperlinks.
Click graph: observed query/item or user/item interactions.
Trust-propagation model: assumptions and labels propagated across a network.
Probabilistic knowledge fusion: combining uncertain extracted assertions.
E-E-A-T evidence view: this library's map from claims to real support.
SERP observation view: this library's dated record of displayed results.
Vector-neighbor graph: proximity under an embedding representation.
Do not transfer a score across these categories. A high local hub score, an extracted-fact probability, a vector similarity, a citation count, and an editorial claim of expertise are not measurements of the same thing. Every algorithm lesson must identify its graph definition, data scope, parameters, assumptions, evaluation set, and deployment status.
==============================================================================
GRAPH CATALOG INDEX
===================
G01 Personal identity and profile graph [P0; standards-backed library view]
G02 Organization, business, and brand graph [P0; standards-backed library view]
G03 Cross-domain operating and ownership graph [P0; library analytical view]
G04 Entity resolution and reconciliation graph [P0; library analytical view]
G05 Local business, place, and service-area graph [P1_IF_APPLICABLE; standards-backed library view]
G06 Product, offer, merchant, and inventory graph [P3_IF_APPLICABLE; standards-backed library view]
G07 Authorship and editorial contribution graph [P0; standards-backed library view]
G08 Topic, ontology, and taxonomy graph [P1; standards-backed library view]
G09 Document, passage, and entity graph [P1; library analytical view]
G10 Claim, evidence, and provenance graph [P0; standards-backed library view]
G11 E-E-A-T evidence graph [P1; custom library evidence view; not a Google graph specification]
G12 Reputation, review, and corroboration graph [P1; library analytical view]
G13 Internal link and navigation graph [P0; library analytical view of documented web links]
G14 External web-link graph [P1; documented link-analysis concept; local reconstruction]
G15 Citation, co-citation, and bibliographic-coupling graph [P2; research/analysis view]
G16 Canonical and duplicate-document graph [P0; library view of documented URL policy]
G17 Redirect and migration graph [P1_IF_APPLICABLE; library engineering view]
G18 Hreflang and locale-alternative graph [P3_IF_APPLICABLE; library view of documented localization signals]
G19 Crawl, rendering, and resource-dependency graph [P0; library engineering view]
G20 Structured-data consistency graph [P0; serialization/validation view]
G21 Query, intent, and page-relevance graph [P1; library analytical view]
G22 SERP observation and competitor-overlap graph [P1; custom observational view; not an official SERP graph]
G23 Question, task, and query-fan-out map [P1; custom planning/observation view]
G24 Entity-mention and co-occurrence graph [P2; library analytical view]
G25 AI answer, grounding, and citation graph [P1; custom observation view of documented report data]
G26 Search-to-lead and customer-journey graph [P1; custom measurement view]
G27 GraphRAG and owned-corpus retrieval graph [P2; documented method with library-specific adaptation]
G28 Embedding-similarity and nearest-neighbor graph [P2; published algorithmic method]
G29 Temporal, version, and supersession graph [P2; library governance view]
G30 Contradiction, uncertainty, and dispute graph [P2; library governance view]
G31 Source-dependency and change-impact graph [P2; library governance view]
G32 Instruction, capability, and workflow dependency graph [P1; private library operating design]
G33 Requirement, test, evidence, and acceptance graph [P0; private library operating design]
G34 Permissions, consent, and disclosure graph [P0; policy-description and private governance view]
G35 Multimedia, transcript, and rights graph [P3_IF_APPLICABLE; standards-informed library view]
G36 Open Graph social-preview metadata [P1; documented protocol; naming distinction]
G37 Social, professional, and interaction graphs [P3_IF_APPLICABLE; documented graph family; library analysis must be scoped]
G38 Scholarly and research graph [P3_IF_APPLICABLE; documented public-data graph family]
G39 Event, venue, organizer, and time graph [P3_IF_APPLICABLE; standards-backed library view]
G40 Learning prerequisite and curriculum graph [P1; custom teaching design]
==============================================================================
40 GRAPH REFERENCE CARDS
========================
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# G01 — Personal identity and profile graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P0
Accountability: R11, R14, R13
## Question
Which person is this, and which records identify that same person?
## Nodes
Person; ProfilePage; Verified profile; Creative work
## Relationship sketch
- profile.mainEntity → person
- work.author → person
- person.sameAs → exact identity reference
## Evidence inputs
Owner-approved public name, actual profile records, bylines, and relationship evidence.
## Implementation
Allocate one stable person identifier. Keep the person separate from biography documents, user accounts, businesses, and people with similar names. Leave unknown properties unset.
## Acceptance checks
- Person and biography page have different identifiers
- Identity links are reviewed for an exact match
- No unverified credential is published
## Do not infer
A descriptive biography, account handle, or confident name match does not prove identity.
## Publication boundary
Approved identity facts may be public; supporting sensitive records stay private.
## Source basis
S03, S04, S05. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G02 — Organization, business, and brand graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P0
Accountability: R11, R14, R18
## Question
Which organization operates a service, and which brands does it actually use?
## Nodes
Organization; Brand; WebSite; Service
## Relationship sketch
- organization.brand → brand
- website.publisher → organization
- service.provider → organization
## Evidence inputs
Owner-confirmed operating structure, real trading names, visible service pages, and verified legal details when needed.
## Implementation
Model organizations, brands, domains, and services separately. Choose the smallest accurate model; do not create a legal entity for each domain or force several businesses into one.
## Acceptance checks
- Every node has an explicit type and verified meaning
- Public names match approved visible facts
- Service provider is not confused with its website
## Do not infer
An owned domain is not automatically an organization, legal name, or separate local office.
## Publication boundary
Publish approved organization/brand/service facts, not private ownership documents.
## Source basis
S02, S06, S07. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G03 — Cross-domain operating and ownership graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view
Priority: P0
Accountability: R11, R14, R24
## Question
How are the owner, organizations, brands, websites, and publications related?
## Nodes
Person; Organization; Brand; Domain; Publication
## Relationship sketch
- verified ownership assertion → evidence
- website → operating organization
- publication → publisher
## Evidence inputs
Explicit ownership/operating statements, domain control evidence where authorized, and approved publisher assignments.
## Implementation
Keep private ownership assertions as qualified claims; map only supported relationships into public vocabulary. Domain control, employment, founding, and publishing are different predicates.
## Acceptance checks
- No sameAs links connect merely affiliated businesses
- Every ownership or founder assertion has evidence
- The person and all website IDs remain distinct
## Do not infer
Common ownership is not identity equivalence, editorial independence, or proof of founding.
## Publication boundary
Relationship summary may be public; contracts and control records normally remain private.
## Source basis
S02, S04, S07. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G04 — Entity resolution and reconciliation graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view
Priority: P0
Accountability: R11, R14, R21
## Question
Which mentions or imported records refer to the same entity?
## Nodes
Mention; Candidate entity; Identifier; Source record; Resolution decision
## Relationship sketch
- mention → candidate
- candidate → supporting identifier
- decision → accepted/rejected match
## Evidence inputs
Names, identifiers, profile URLs, contextual attributes, conflicts, and reviewer decisions.
## Implementation
Generate candidates without merging them. Require corroboration, keep rejected alternatives and confidence rationale, and support reversible merges. Give human reviewers ambiguous cases.
## Acceptance checks
- Known same-name people remain separate in negative tests
- Reversing a merge restores source associations
- All accepted matches retain provenance
## Do not infer
Vector similarity or identical names are not sufficient evidence of identity.
## Publication boundary
Private resolution records; only approved identity references become public.
## Source basis
S04, S10, S12. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G05 — Local business, place, and service-area graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P1_IF_APPLICABLE
Accountability: R18, R11, R14, R20
## Question
Which real business is at a location, and where does it provide service?
## Nodes
Organization; LocalBusiness; Place; Address; Service area; Profile
## Relationship sketch
- branch → parent organization
- business → actual place
- service → area served
## Evidence inputs
Approved location facts, eligible business profiles, hours, real service coverage, and privacy decisions.
## Implementation
Distinguish headquarters, branches, customer-facing premises, mailing addresses, and service areas. Do not derive a physical office from a city page or a travel radius.
## Acceptance checks
- Each published physical location is real
- Service-area claims do not create fictional branches
- Sensitive home-address publication is explicitly reviewed
## Do not infer
One page for each town is not evidence of one office in each town.
## Publication boundary
Public business facts only; avoid unnecessary personal location information.
## Source basis
S07, S28. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G06 — Product, offer, merchant, and inventory graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P3_IF_APPLICABLE
Accountability: R11, R03, R14, R16
## Question
What is sold, by whom, with which current offer and availability?
## Nodes
Product; Variant; Offer; Merchant; Inventory observation
## Relationship sketch
- offer → item
- offer → seller
- inventory observation → offer/version
## Evidence inputs
Actual catalog, identifiers, landing pages, feeds, dated price and stock records.
## Implementation
Separate an enduring product identity from a seller-specific, time-sensitive offer. Reconcile pages and feeds. Only use variant relationships supported by the actual catalog.
## Acceptance checks
- Offer currency and price agree with the reviewed source
- Availability has an observation time
- Variants are not merged solely because names resemble each other
## Do not infer
Your catalog graph is not direct control of Google Shopping Graph.
## Publication boundary
Approved catalog facts public; supplier and customer records private.
## Source basis
S30, S31. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G07 — Authorship and editorial contribution graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P0
Accountability: R13, R11, R14
## Question
Who actually authored, reviewed, edited, or published this work?
## Nodes
Person; Work; Revision; Contribution; Publisher
## Relationship sketch
- work.author → person
- revision → actual reviewer
- work.publisher → organization
## Evidence inputs
Actual contribution records, approved bylines, editorial review, revision history.
## Implementation
Track contributions per work/version rather than giving every page the same impressive author. Separate authorship, review, publishing, and tool assistance.
## Acceptance checks
- Byline agrees with actual contribution
- Reviewer records identify the reviewed version
- An AI role prompt is not represented as a staff member
## Do not infer
A reviewer credit is not proof that every claim or future revision was reviewed.
## Publication boundary
Approved bylines and methodology may be public; draft review logs private.
## Source basis
S03, S05, S08. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G08 — Topic, ontology, and taxonomy graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P1
Accountability: R10, R09, R11, R13
## Question
Which concepts exist, and how do their meanings and scopes relate?
## Nodes
Concept; Preferred label; Alternative label; Concept scheme
## Relationship sketch
- concept → broader/narrower concept
- concept → related concept
- label → concept
## Evidence inputs
Domain definitions, terminology decisions, source-backed distinctions, and reader questions.
## Implementation
Use controlled concepts to connect documents without making each term a public page. Record synonyms separately from broader concepts; avoid over-specific taxonomies that users cannot navigate.
## Acceptance checks
- Broader-than relationships are not mistaken for same-identity links
- Ambiguous abbreviations have definitions
- Concept revisions preserve stable identifiers
## Do not infer
A dense taxonomy does not certify topical authority or completeness of expertise.
## Publication boundary
A helpful subset may be published; internal editorial notes stay private.
## Source basis
S15, S44. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G09 — Document, passage, and entity graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view
Priority: P1
Accountability: R10, R11, R13
## Question
Which part of which document describes or supports an entity or concept?
## Nodes
Document; Version; Section; Passage; Entity; Concept
## Relationship sketch
- passage → document version
- passage → mentions entity
- section → concerns concept
## Evidence inputs
Original text, offsets or section locators, content hashes, extraction method, and source rights.
## Implementation
Preserve document and section boundaries when indexing. Treat mentions as mentions, not verified assertions; keep a route from each retrieved passage back to the actual source.
## Acceptance checks
- Every passage resolves to an exact source version
- Quoted context can be reconstructed
- Mention extraction does not silently assert facts
## Do not infer
Entity mention, aboutness, evidence support, and endorsement are different relationships.
## Publication boundary
Public passages follow source rights; private corpus records remain private.
## Source basis
S12, S14, S25. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G10 — Claim, evidence, and provenance graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: standards-backed library view
Priority: P0
Accountability: R14, R11, R20
## Question
What supports a particular assertion, and where did that support originate?
## Nodes
Claim; Evidence; Source version; Extraction activity; Reviewer
## Relationship sketch
- claim → supported/contradicted by evidence
- evidence → source version
- derived artifact → source activity
## Evidence inputs
Exact assertion scope, original source locator, observation date, evidence class, and review decision.
## Implementation
Make claims first-class records. Preserve source chains and ownership/independence labels. A summary derived from a source is not a new independent source.
## Acceptance checks
- Every published material assertion has a source or labeled basis
- Conflicting evidence remains attached
- Unsupported assertions cannot pass the publication-readiness check
## Do not infer
Five copies of the same claim do not constitute five independent confirmations.
## Publication boundary
Publish safe citations, not secrets, client messages, or restricted originals.
## Source basis
S14, S16. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G11 — E-E-A-T evidence graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: custom library evidence view; not a Google graph specification
Priority: P1
Accountability: R14, R13, R11, R19
## Question
What real evidence demonstrates experience, expertise, attribution, and trust for this claim?
## Nodes
Person; Work performed; Evidence; Published work; Independent mention; Correction
## Relationship sketch
- work performed → evidence
- claim → bounded experience basis
- mention → source and independence class
## Evidence inputs
Actual work artifacts, methods, relevant verified qualifications, corrections, disclosures, and earned recognition.
## Implementation
Build an evidence map for specific claims and subjects. Use it to expose missing support and accurate authorship, not to manufacture a universal authority score.
## Acceptance checks
- Experience claims point to real work or are omitted
- Owned/paid/earned sources stay distinguished
- No public Google E-E-A-T number is invented
## Do not infer
This is an internal teaching and audit model; Google does not document it as a standalone ranking system.
## Publication boundary
Publish substantiated selected evidence with permission; private engagement records remain private.
## Source basis
S01, S08, S43. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G12 — Reputation, review, and corroboration graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view
Priority: P1
Accountability: R19, R14, R11, R18
## Question
Who said what about which entity, with what provenance and independence?
## Nodes
Reviewer; Review; Reviewed entity; Publisher; Disclosure; Source owner
## Relationship sketch
- review → exact subject
- statement → publisher
- publisher → ownership/disclosure record
## Evidence inputs
Actual reviews and dates, subject matching, publication rights, disclosed sponsorship, source lineage.
## Implementation
Preserve review context and scales. Record whether a source is owned, paid, syndicated, or independently earned; never infer independence from different domain names alone.
## Acceptance checks
- Review subject is not confused with another product/business
- Syndicated copies share a provenance origin
- Feature eligibility is checked separately from review authenticity
## Do not infer
Authentic self-hosted testimonials do not automatically qualify for LocalBusiness/Organization review stars.
## Publication boundary
Approved review evidence public; unnecessary reviewer data excluded.
## Source basis
S29, S14, S43. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G13 — Internal link and navigation graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view of documented web links
Priority: P0
Accountability: R08, R09, R04
## Question
Can visitors and crawlers find the intended pages through useful links?
## Nodes
Page; Link; Anchor; Navigation context
## Relationship sketch
- page → linked page
- link → anchor and location
## Evidence inputs
Authorized crawl, initial/rendered HTML as relevant, intended navigation, canonical route list.
## Implementation
Inspect reachable components and important pages with no incoming links. Evaluate navigational usefulness alongside graph metrics. Keep page purpose and user journeys ahead of arbitrary link quotas.
## Acceptance checks
- Important public pages are reachable from intended entry points
- Actual href targets work
- Any reported orphan definition and crawl scope are explicit
## Do not infer
A crawl of only part of a site cannot prove whole-site orphan status.
## Publication boundary
Navigation is public; diagnostic reports normally private.
## Source basis
S19, S41. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G14 — External web-link graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: documented link-analysis concept; local reconstruction
Priority: P1
Accountability: R19, R08, R10
## Question
Which external pages link to your content, and what does the observed network show?
## Nodes
External page; Internal page; Domain; Observed hyperlink
## Relationship sketch
- source page → target page
## Evidence inputs
Actual link observations, collection source, timestamps, anchor and link attributes, coverage limitations.
## Implementation
Analyze observed linking relationships and ownership clusters. Mark third-party crawl coverage as partial. Distinguish network measurements from the search engine's internal scoring.
## Acceptance checks
- Links are checked at their source when practical
- Collection coverage is documented
- Local metrics are labeled as locally computed
## Do not infer
NetworkX PageRank, third-party domain scores, and Google ranking values are not interchangeable.
## Publication boundary
Public links; private outreach and analysis records.
## Source basis
S09, S39, S43. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G15 — Citation, co-citation, and bibliographic-coupling graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: research/analysis view
Priority: P2
Accountability: R10, R14, R11
## Question
Which works cite which sources, and which share citation neighborhoods?
## Nodes
Work; Cited source; Citation occurrence
## Relationship sketch
- work → cited source
- two works → shared reference projection
- two sources → jointly cited projection
## Evidence inputs
Resolved citations, source locators, document versions, and duplication provenance.
## Implementation
Maintain the directed citation graph first. Co-citation connects items cited together; bibliographic coupling connects works sharing references. Label derived edges and formulas, not endorsements.
## Acceptance checks
- Derived projections can be recomputed from citation records
- Copied source lists do not count as independent evidence
- A citation is inspected before treating it as support
## Do not infer
Being cited together does not imply identity, agreement, quality, or ranking equivalence.
## Publication boundary
Respect source licenses; publish only permitted citation data.
## Source basis
S14, S37, S40. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G16 — Canonical and duplicate-document graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library view of documented URL policy
Priority: P0
Accountability: R08, R09, R11
## Question
Which URLs describe duplicate documents, and what canonical signals are observed?
## Nodes
URL; Document version; Declared canonical; Observed engine canonical
## Relationship sketch
- URL → declared canonical
- inspection observation → selected canonical
- document → duplicate candidate
## Evidence inputs
Page headers/HTML, sitemaps, redirect signals, actual engine inspection when available.
## Implementation
Store publisher-declared and engine-observed canonicals separately. Review cross-domain canonical proposals for real document duplication; do not canonicalize distinct services merely to connect brands.
## Acceptance checks
- Each observation distinguishes intent from engine behavior
- Canonical targets are valid intended documents
- Conflicting page/header signals are reported
## Do not infer
Canonicalizing a page does not merge people or organizations.
## Publication boundary
Page canonical signals public; inspection records private.
## Source basis
S17, S08. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G17 — Redirect and migration graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library engineering view
Priority: P1_IF_APPLICABLE
Accountability: R08, R01, R25, R26
## Question
What happens to each old URL, and is the migration reversible?
## Nodes
Old URL; Hop; Destination; Release; Rollback mapping
## Relationship sketch
- old URL → redirect hop
- final URL → intended replacement
- mapping → release version
## Evidence inputs
Authorized redirect map, actual HTTP observations, content equivalence decisions, backup mapping.
## Implementation
Check loops, long chains, deleted destinations, and mismatched content. Treat redirect changes as authorized production changes with rollback; do not silently replace all missing pages with the homepage.
## Acceptance checks
- No loop in approved redirect paths
- Every moved important URL has a reviewed outcome
- Rollback restores the previous mapping
## Do not infer
An HTTP redirect does not prove the destination inherited a particular ranking.
## Publication boundary
Redirect behavior public; migration control records private.
## Source basis
S17, S41. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G18 — Hreflang and locale-alternative graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library view of documented localization signals
Priority: P3_IF_APPLICABLE
Accountability: R08, R09, R13
## Question
Which localized documents are alternatives for the same user task?
## Nodes
Localized page; Language; Region; Alternate group
## Relationship sketch
- page → locale
- page → alternate page
## Evidence inputs
Actual translated/localized pages and annotations, canonical policy, language/region intent.
## Implementation
Validate reciprocal alternative sets under the current implementation method. Do not confuse localization with location claims or populate a graph using untranslated duplicate pages.
## Acceptance checks
- Alternate URLs resolve as intended
- Annotation sets are consistent and reciprocal where required
- Language/region intent matches actual content
## Do not infer
An alternate-language page is not a different business entity.
## Publication boundary
Appropriate locale annotations public.
## Source basis
S18, S17. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G19 — Crawl, rendering, and resource-dependency graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library engineering view
Priority: P0
Accountability: R04, R08, R06, R20
## Question
What must load for the user and each tested consumer to observe the real content?
## Nodes
URL; HTML; Script; Stylesheet; Image; Rendered state; Consumer observation
## Relationship sketch
- page → required resource
- render observation → observed content
- consumer → access result
## Evidence inputs
Initial responses, browser network captures, blocked-resource observations, versioned tests.
## Implementation
Trace critical content, metadata, and links to dependencies. Test optional-script failure and record differences between browser and crawler observations; avoid pretending all consumers render identically.
## Acceptance checks
- Essential content is observed under the agreed delivery contract
- Blocked resources have documented impact
- Actual crawler evidence is separated from a spoofed user-agent test
## Do not infer
User-agent string selection does not authenticate a crawler or reproduce its complete behavior.
## Publication boundary
Public assets; private traces redacted.
## Source basis
S20, S27. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G20 — Structured-data consistency graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: serialization/validation view
Priority: P0
Accountability: R11, R04, R14, R21
## Question
Do all public representations describe the same approved entities and facts?
## Nodes
Entity registry; Page; JSON-LD node; Feed record; Validation finding
## Relationship sketch
- page representation → entity ID
- assertion → approved claim
- finding → affected representation
## Evidence inputs
Approved entity registry, actual page markup, visible content, feed versions, validation output.
## Implementation
Generate public subsets from a reviewed source of truth. Detect conflicting identifiers and facts across templates. Run syntax, vocabulary, graph, content, and feature checks separately.
## Acceptance checks
- Public references resolve to intended entity records
- No template invents a second identity
- Visible content and JSON-LD agree on material facts
## Do not infer
A large @graph array is not proof of completeness, authority, or provider ingestion.
## Publication boundary
Only approved public projections; private full graph stays private.
## Source basis
S13, S16, S08. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G21 — Query, intent, and page-relevance graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view
Priority: P1
Accountability: R10, R23, R13, R16
## Question
Which pages answer which actual reader questions and tasks?
## Nodes
Query; Task; Intent hypothesis; Page; Evidence of demand
## Relationship sketch
- query → task hypothesis
- task → helpful page
- query → observed page result
## Evidence inputs
Actual inquiries, permitted search-report data, editorial judgments, and annotated evaluation sets.
## Implementation
Separate measured queries from brainstorming. Evaluate whether a page answers the task instead of merely sharing words. Keep ambiguous intents explicit rather than forcing one interpretation.
## Acceptance checks
- Observed and hypothetical demand are labeled
- Page-task relevance is reviewed against content
- Internal retrieval tests include relevant and irrelevant pages
## Do not infer
Your intent taxonomy is not a disclosure of an engine's hidden query representation.
## Publication boundary
Useful user-facing content public; query logs privacy-reviewed.
## Source basis
S09, S40. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G22 — SERP observation and competitor-overlap graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: custom observational view; not an official SERP graph
Priority: P1
Accountability: R10, R16, R08
## Question
What appeared for a specified query under specified conditions?
## Nodes
Query; SERP snapshot; Result occurrence; URL; Domain; Result feature
## Relationship sketch
- snapshot → query/context
- snapshot → occurrence
- occurrence → URL and feature
## Evidence inputs
Permitted search observations or licensed data, exact collection context, time, URL and feature details.
## Implementation
Model each appearance as an occurrence, not a timeless edge. Distinguish organic results, ads, local results, and AI citations. Compare URL-set overlaps only within documented sampling.
## Acceptance checks
- Every result belongs to a dated snapshot
- Position definition and feature type are retained
- Unavailable result data is not represented as zero visibility
## Do not infer
Ranking for one query does not make a competitor's schema, word count, or backlink pattern causal.
## Publication boundary
Aggregate research may be public; raw collected data obeys permissions.
## Source basis
S09, S40. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G23 — Question, task, and query-fan-out map
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: custom planning/observation view
Priority: P1
Accountability: R10, R12, R13
## Question
What related questions must be answered for the user's task?
## Nodes
Task; Question; Subquestion; Observed grounding phrase; Hypothesized expansion
## Relationship sketch
- task → subquestion
- question → supporting page
- observed phrase → evidence record
## Evidence inputs
User research, actual questions, provider-exposed phrases when available, separate model-generated suggestions.
## Implementation
Use related questions to improve coverage without producing a page for every paraphrase. Tag suggestions as hypotheses, and never label generated subquestions as actual hidden provider fan-out.
## Acceptance checks
- Observed and hypothesized expansions remain separate
- Each proposed section serves a real task
- Redundant pages are not generated just to fill graph nodes
## Do not infer
Public descriptions of query fan-out do not reveal the exact query tree for a particular answer.
## Publication boundary
Helpful answers public; research/observation records private.
## Source basis
S21, S22, S43. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G24 — Entity-mention and co-occurrence graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: library analytical view
Priority: P2
Accountability: R10, R11, R14
## Question
Where are entities mentioned together, and in what context?
## Nodes
Mention; Passage; Entity candidate; Source; Co-occurrence projection
## Relationship sketch
- passage → mentions candidate
- projection → shared passage/source
## Evidence inputs
Actual text spans, entity-resolution decisions, source lineage, language and time.
## Implementation
Preserve sentiment and relationship context when known; a criticism and a recommendation are not equivalent. Use co-occurrence to find inspection candidates, not to auto-create sameAs or endorsements.
## Acceptance checks
- Every mention maps to a source span
- False name matches are tested
- Derived associations are labeled and reversible
## Do not infer
Co-occurrence does not establish identity, expertise, recommendation, or causation.
## Publication boundary
Public-source analysis only as permitted; minimize personal data.
## Source basis
S12, S14, S40. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G25 — AI answer, grounding, and citation graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: custom observation view of documented report data
Priority: P1
Accountability: R12, R16, R14
## Question
Which answer or report observation cites which source, and for what support?
## Nodes
Answer observation; Grounding phrase; Citation occurrence; Page; Claim; Provider
## Relationship sketch
- observation → source citation
- grounding phrase → reported page
- citation → reviewed support relation
## Evidence inputs
Actual cited URLs, provider report/export definitions, observation context, original answer when available.
## Implementation
Distinguish observed answers from aggregated reports and grounding phrases from original prompts. Inspect source support rather than assuming a citation validates all nearby text.
## Acceptance checks
- Every count has a denominator and coverage window
- Actual prompts are not invented from grounding phrases
- Citation observations are separate from referral sessions and leads
## Do not infer
Citation count is not a public authority metric or proof of customers acquired.
## Publication boundary
Sanitized aggregates may be public; user prompts and private reports protected.
## Source basis
S22, S23, S21. See Research/sources.json.
Sources support the primitives or named technology. The organization, labels, actions, and acceptance contracts in this catalog are this library's design, not claimed provider requirements.
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# G26 — Search-to-lead and customer-journey graph
Status: NEW RESEARCHED DESIGN; not deployed
Reviewed: 2026-09-12
Nature: custom measurement view
Priority: P1
Accountability: R16, R03, R12, R20
## Question
Which observed discovery events connect to actual business outcomes?
## Nodes
Referral; Session; Event; Durable inquiry; Qualified lead; Outcome
## Relationship sketch
- permitted session → observed event
- inquiry → qualification decision
- outcome → attributed evidence
## Evidence inputs
Authorized analytics and backend events, consent-aware identifiers, actual qualification and outcome records.
## Implementation
Start from accurate business-state transitions. Preserve attribution uncertainty, unknown origin, and missing identifiers; do not stitch anonymous people across contexts without authority.
## Acceptance checks
- Submit success does not substitute for durable acceptance