Reference
40 Capabilities
40 Capacités
bra0 is organized as 40 leaf capabilities across 5 families and 14 sub-domains. Each capability traces to a layer, a set of W3C standards, and a maturity status. This is the complete reference.
bra0 est organisé en 40 capacités unitaires réparties en 5 familles et 14 sous-domaines. Chaque capacité trace vers une couche, un ensemble de standards W3C et un statut de maturité. Voici la référence complète.
This is the Reference surface (Diátaxis): operational lookup, gate-bound to the capability manifest. For the strategic capability map and doctrine, see the Capability Blueprint (Explanation); for command signatures, the CLI reference.
Ceci est la surface de référence (Diátaxis) : consultation opérationnelle, liée par gate au manifeste des capacités. Pour la carte stratégique et la doctrine, voir le Blueprint des capacités (Explication) ; pour les signatures de commandes, la référence CLI.
Policies, identity, trust, audit. Who can? Who did? What's allowed? Is it compliant?
Politiques, identité, confiance, audit. Qui peut ? Qui a fait ? Qu'est-ce qui est autorisé ? Est-ce conforme ?
Identity & Mandates
Identité & Mandats
| ID | Capability | Description | Status |
| GOV-1 | Sovereignty Boundaries |
KnowledgeSpace as governance boundary. 5-layer trust stack. DID ODRLLe KnowledgeSpace comme frontière de gouvernance. Pile de confiance à 5 couches. |
Partial |
| GOV-6 | Agent Mandates |
Agent Service Contract ontology (asc: v0.4, 628 triples). 12 agents with formal ODRL mandates. asc: ODRLOntologie Agent Service Contract (asc: v0.4, 628 triplets). 12 agents avec mandats ODRL formels. |
Partial |
Compliance & Validation
Conformité & Validation
| ID | Capability | Description | Status |
| GOV-2 ▾ | Consent & Usage Policies |
ODRL 2.2 per-entity allow-lists (read/annotate/modify). Dual enforcement. ODRL 2.2Listes d'autorisation ODRL 2.2 par entité (lecture/annotation/modification). Double application. |
Partial |
| GOV-4 ▾ | Validation Gates |
SHACL validation via rudof (full SHACL 1.2). Post-merge quality gate. SHACL rudofValidation SHACL via rudof (SHACL 1.2 complet). Porte qualité post-merge. |
Exists |
| GOV-7 ▾ | KS Lifecycle |
Draft → review → published. SHACL gate + PROV-O trace per promotion. PROV-OBrouillon → revue → publié. Porte SHACL + trace PROV-O par promotion. |
Exists |
Traceability & Catalog
Traçabilité & Catalogue
| ID | Capability | Description | Status |
| GOV-3 ▾ | Provenance & Audit |
PROV-O activity logging (13 types). Immutable trail. NextGraph DAG + bra0 semantic meaning. PROV-OJournalisation d'activités PROV-O (13 types). Piste immuable. |
Exists |
| GOV-5 | Catalog and Discovery |
DCAT 3.0 dataset metadata export. Entity counts, distribution format, publisher. DCAT 3Export de métadonnées DCAT 3.0. Comptage d'entités, format, éditeur. |
Partial |
Meaning, reasoning, schema, enrichment. What does it mean? How do concepts relate? Is the model complete?
Sens, raisonnement, schéma, enrichissement. Que signifie-t-il ? Comment les concepts sont-ils liés ? Le modèle est-il complet ?
Model Construction
Construction de modèles
| ID | Capability | Description | Status |
| SL-1 ▾ | Ontology Authoring |
Create/edit OWL 2 ontologies and SKOS taxonomies. 11 entity types. Visual canvas + detail panels. OWL 2 SKOSCréer/éditer des ontologies OWL 2 et taxonomies SKOS. 11 types d'entités. Canvas visuel + panneaux. |
Exists |
| SL-5 ▾ | Data Mapping |
W3C RML TriplesMap: CSV/JSON → RDF instances. Schema inference, IRI templates. RMLW3C RML TriplesMap : CSV/JSON → instances RDF. Inférence de schéma, templates IRI. |
Partial |
| SL-6 | Vocabulary Composition |
Multi-vocabulary KnowledgeSpaces via prefix management. SKOSKnowledgeSpaces multi-vocabulaires via gestion de préfixes. |
Planned |
Formalization & Reasoning
Formalisation & Raisonnement
| ID | Capability | Description | Status |
| SL-2 | Schema Definition |
ShEx shapes → TypeScript ORM types. Static files + codegen. ShExShapes ShEx → types ORM TypeScript. Fichiers statiques + codegen. |
Partial |
| SL-3 ▾ | OWL Reasoning |
OWL 2 RL inference: 9 rules. Fixed-point materialization via SPARQL INSERT. OWL 2 RL SPARQLInférence OWL 2 RL : 9 règles. Matérialisation en point fixe via SPARQL INSERT. |
Exists |
| SL-4 | Semantic Enrichment |
LFS-MD annotation parser: [text]{=uri .Class}. Bidirectional MD↔RDF sync planned. LFS-MDParseur d'annotations LFS-MD. Synchronisation bidirectionnelle MD↔RDF planifiée. |
Partial |
Projection & Acceleration
Projection & Accélération
| ID | Capability | Description | Status |
| SL-7 ▾ | Reactive Projection |
SPARQL queries as reactive subscriptions. Auto re-evaluation on mutations. SPARQLRequêtes SPARQL comme souscriptions réactives. Réévaluation automatique sur mutations. |
Planned |
| SL-8 | Shape-Driven Forms |
Auto-generate property edit forms from SHACL/ShEx shapes. XSD-to-widget mapping. SHACL ShExGénération automatique de formulaires depuis les shapes SHACL/ShEx. |
Planned |
| SL-9 ▾ | KS Templates |
Pre-built template bundles: TBox + shapes + queries + sample ABox. 3 built-in templates.Bundles de templates pré-construits : TBox + shapes + requêtes + ABox exemple. |
Planned |
Storage, ingestion, query, sync, identity. Where is the data? Who is this? How do I verify?
Stockage, ingestion, requêtes, synchronisation, identité. Où sont les données ? Qui est-ce ? Comment vérifier ?
Data Operations
Opérations de données
| ID | Capability | Description | Status |
| DP-1 ▾ | KG Ingestion |
Load external KGs: Turtle, JSON-LD, N-Triples. Parse, validate, hydrate into Oxigraph. Turtle JSON-LDCharger des KG externes : Turtle, JSON-LD, N-Triples. Parser, valider, hydrater dans Oxigraph. |
Exists |
| DP-2 ▾ | SPARQL Operations |
SELECT, CONSTRUCT, ASK, UPDATE. QueryBridge abstracts backend. Dual runtime: TS + Rust native. SPARQL OxigraphSELECT, CONSTRUCT, ASK, UPDATE. QueryBridge abstrait le backend. Double runtime : TS + Rust natif. |
Exists |
| DP-3 | JSON-LD Serialization |
W3C JSON-LD 1.1 serialization of a Knowledge Space. CLI path: topo export --format jsonld (jsonld.fromRDF over an N-Quads dump); ORM path: jsonldService.serializeToJsonLd. JSON-LD 1.1Sérialisation W3C JSON-LD 1.1 d'un Knowledge Space. Voie CLI : topo export --format jsonld ; voie ORM : jsonldService.serializeToJsonLd. |
Exists |
| DP-4 ▾ | Export & Interoperability |
Serialize to Turtle, JSON-LD, N-Triples. DCAT metadata. Round-trip fidelity. W3CSérialisation en Turtle, JSON-LD, N-Triples. Métadonnées DCAT. Fidélité aller-retour. |
Exists |
| DP-8 ▾ | Document Chunking |
Document chunking with 5 quality evaluators (Semantic Coherence, Boundary Integrity, Information Coverage, Density Consistency, Redundancy Control) over the bra0-chunking Rust crate. CLI path: eval-cli --strategy fixed-size|semantic; lineage via prov:wasRevisionOf + Blake3 idempotence. ADR-120Découpage de document avec 5 évaluateurs de qualité (cohérence sémantique, intégrité des frontières, couverture informationnelle, consistance de densité, contrôle de redondance) sur la crate Rust bra0-chunking. Voie CLI : eval-cli --strategy fixed-size|semantic. |
Partial |
Sovereign Identity
Identité souveraine
| ID | Capability | Description | Status |
| DP-5 | DID Attribution |
Generate sovereign decentralized identifiers (did:ng:o:). DIDGénérer des identifiants décentralisés souverains (did:ng:o:). |
Gap |
| DP-6 | DID Resolution |
Resolve a DID to its document. Local-first, then P2P, never centralized. DIDRésoudre un DID vers son document. Local-first, puis P2P, jamais centralisé. |
Gap |
| DP-7 | DID Fusion |
Merge multiple DIDs representing the same entity. Sovereign act — owner-only. DIDFusionner plusieurs DIDs représentant la même entité. Acte souverain. |
Gap |
Grounding in reality. What is actually there? Has reality changed? Are we still in sync? Without topo perception, bra0 is a static ontology editor. With it, every decision traces back to verified observations.
Ancrage dans la réalité. Qu'y a-t-il réellement ? La réalité a-t-elle changé ? Sommes-nous encore synchronisés ? Sans perception topo, bra0 est un éditeur d'ontologies statique.
Reality Capture
Capture de la réalité
| ID | Capability | Description | Status |
| TP-1 ▾ | Digital Perception |
topo capture — scan directories, classify files, produce ArchiMate RDF. ArchiMatetopo capture — scanner des répertoires, classifier les fichiers, produire du RDF ArchiMate. |
Exists |
| TP-2 | Social Perception |
topo social — extract EDGY entities from markdown. 2-tier: regex + NER (candle BERT). EDGY NERtopo social — extraire des entités EDGY depuis le markdown. 2 niveaux : regex + NER (candle BERT). |
Partial |
| TP-3 | Physical Perception |
Capture physical infrastructure, sensors, spatial relationships. IoT+SOSA for neuro domain. SOSACapturer l'infrastructure physique, capteurs. IoT+SOSA pour le domaine neuro. |
Partial |
Orchestration
| ID | Capability | Description | Status |
| TP-4 ▾ | Continuous Reflection |
topo reflect — cross-reference traces with domain encounters. Multi-phase SPARQL analysis. SPARQLtopo reflect — croiser les traces avec les rencontres domaine. |
Exists |
| TP-5 | Pipeline Authoring |
Visual DAG editor for P-Plan pipelines. ReactFlow-based. Turtle source of truth. P-PlanÉditeur visuel DAG pour les pipelines P-Plan. Basé sur ReactFlow. |
Planned |
Intelligence across all planes. 100% Rust/WASM compute: oxigraph + sophia + rudof + candle. Symbolic first, neural when needed, sovereign always.
Intelligence transversale. 100% Rust/WASM : oxigraph + sophia + rudof + candle. Symbolique d'abord, neuronal si nécessaire, souverain toujours.
Knowledge Quality
Qualité du savoir
| ID | Capability | Description | Status |
| NS-1 ▾ | Gap Detection |
topo gaps — 10 SPARQL queries (Gaur taxonomy). Custom queries via --queries. SPARQLtopo gaps — 10 requêtes SPARQL (taxonomie Gaur). Requêtes custom via --queries. |
Exists |
| NS-2 | Grounding Verification |
Grounding Index: KG-provenance-backed triples / total. Target: >0.95 for clinical CDSS. PROV-OIndice d'ancrage : triplets avec provenance KG / total. Cible : >0.95 pour CDSS cliniques. |
Partial |
| NS-6 | Temporal Validity |
Knowledge freshness via PROV-O timestamps. Domain-specific expiry rules. PROV-OFraîcheur des connaissances via horodatages PROV-O. Règles d'expiration par domaine. |
Gap |
Symbolic Inference
Inférence symbolique
| ID | Capability | Description | Status |
| NS-5 ▾ | Symbolic Cascade |
5-stage pipeline: OWL → NER → merge → SHACL → result. Symbolic always wins. OWL SHACLPipeline 5 étapes : OWL → NER → fusion → SHACL → résultat. Le symbolique gagne toujours. |
Exists |
| NS-7 ▾ | OWL Materialization |
OWL 2 RL via 9 SPARQL CONSTRUCT rules. Fixpoint engine. 14ms on 522-triple corpus. sophia oxigraphOWL 2 RL via 9 règles SPARQL CONSTRUCT. Moteur en point fixe. 14ms sur 522 triplets. |
Exists |
Neural Extraction
Extraction neuronale
| ID | Capability | Description | Status |
| NS-8 ▾ | Entity Recognition |
Zero-shot NER via candle BERT + SKOS vocabulary. MiniLM-L6-v2 (22MB). candle BERTNER zero-shot via candle BERT + vocabulaire SKOS. MiniLM-L6-v2 (22 Mo). |
Partial |
| NS-9 | Sovereign Transcription |
Audio-to-text via candle-whisper (Rust WASM). Local-first. Multilingual. candle whisperAudio vers texte via candle-whisper (Rust WASM). Local-first. Multilingue. |
Gap |
| NS-11 | Schema-Constrained LLM Extraction |
JSON-Schema-constrained extraction with stop-reason instrumentation. ADR-085 invocation contract: bra0Extract.invoke({corpus, jsonSchema, M*, T=0.0, seed}). SHACL candleExtraction contrainte par JSON-Schema avec instrumentation des stop-reasons. Contrat d'invocation ADR-085 : bra0Extract.invoke({corpus, jsonSchema, M*, T=0.0, seed}). |
Exists |
Assistance
| ID | Capability | Description | Status |
| NS-3 | Context Generation |
Agent prompts via SPARQL CONSTRUCT on the KG. Change behavior = change triples. SPARQLPrompts des agents via SPARQL CONSTRUCT sur le KG. Changer le comportement = changer les triplets. |
Partial |
| NS-4 ▾ | Auditable Explanations |
Full PROV-O provenance pipeline (250 LOC). Every pipeline step records activity, timestamps, agents. PROV-OPipeline de provenance PROV-O complet (250 LOC). Chaque étape enregistre activité, horodatages, agents. |
Partial |
| NS-10 | Local Inference |
Small LMs in-browser via candle WASM. Tier 3 of cascade (3% compute). Zero cloud dependency. candlePetits modèles de langage dans le navigateur via candle WASM. Tier 3 de la cascade. |
Gap |
Operational reference — interface · SPARQL · CLI
Référence opérationnelle — interface · SPARQL · CLI
Every capability is first a SPARQL operation, then a CLI command, then optionally a UI (arch-delta invariant I1). This section associates each capability with its three operational handles — the signature you call from code, the SPARQL query you run over the evidence graph, and the topo invocation from the terminal. Entries synchronized with blueprint.html via the capability-operations.ttl authoring source. Progressive publication per cycle gate.
Chaque capacité est d'abord une opération SPARQL, puis une commande CLI, puis optionnellement une UI (invariant I1 de l'arch-delta). Cette section associe chaque capacité à ses trois poignées opérationnelles — la signature appelée depuis le code, la requête SPARQL sur l'evidence graph, et l'invocation topo en terminal. Entrées synchronisées avec blueprint.html via la source d'autorité capability-operations.ttl. Publication progressive à chaque gate du cycle.
CoverageCouverture:
20 / 40
49%
· target (shipped + partial) = 27/39 = 69%cible (shipped + partial) = 27/39 = 69%
GOV-2
Consent & Usage Policies
partial
InterfaceconsentStore.evaluate(request: AccessRequest) → PolicyDecision
SPARQLASK {
?policy a odrl:Policy ;
odrl:permission ?perm .
?perm odrl:action ?action ;
odrl:target ?target .
FILTER (?action = <urn:action:read> && ?target = <urn:entity:X>)
}
CLItopo policy check --request request.json --policy policy.ttl
GOV-3
Provenance & Audit
shipped
InterfaceprovenanceEngine.logActivity(kind: ProvActivityKind, used: IRI[], generated: IRI[], agent: IRI) → IRI
SPARQLINSERT DATA {
GRAPH <urn:audit> {
<urn:act:_uuid_> a prov:Activity ;
prov:startedAtTime "2026-04-16T10:00:00Z"^^xsd:dateTime ;
prov:wasAssociatedWith <did:ng:o:agentX> ;
prov:used <urn:entity:input> ;
prov:generated <urn:entity:output> .
}
}
CLItopo audit log --entity <iri> --agent <did> --activity consolidate
GOV-4
Validation Gates
shipped
Interfacefn validate_shacl(shapes: &Path, data: &Path) → ShaclReport // cascade.rs
SPARQL# rudof writes sh:ValidationReport into the graph; retrieve violations:
SELECT ?focusNode ?resultPath ?severity ?message WHERE {
?report a sh:ValidationReport ;
sh:conforms false ;
sh:result ?r .
?r sh:focusNode ?focusNode ;
sh:resultPath ?resultPath ;
sh:resultSeverity ?severity ;
sh:resultMessage ?message .
}
CLIrudof shacl-validate -s shapes.ttl data.ttl
GOV-7
KnowledgeSpace Lifecycle
planned
InterfacelifecycleService.promote(kspace: IRI, from: Stage, to: Stage) → Result<PromotionActivity, GateError>
SPARQLDELETE { ?ks bra0:stage ?oldStage }
INSERT {
?ks bra0:stage ?newStage .
<urn:act:_uuid_> a prov:Activity ;
prov:used ?ks ;
prov:generated ?newStage ;
prov:startedAtTime ?now .
} WHERE {
BIND (<urn:ks:target> AS ?ks)
BIND ("review" AS ?newStage)
BIND (NOW() AS ?now)
?ks bra0:stage ?oldStage .
FILTER NOT EXISTS { ?r a sh:ValidationReport ; sh:conforms false ; sh:scope ?ks }
}
CLItopo kspace promote <iri> --from draft --to review
SL-1
Ontology Authoring
shipped
InterfacerdfMutationGenerator.createClass({iri, label, superClass?, comment?}) → TurtlePatch
SPARQLINSERT DATA {
<urn:ont:MyClass> a owl:Class ;
rdfs:label "My Class"@en ;
rdfs:subClassOf <urn:ont:ParentClass> .
}
CLItopo ontology new-class <iri> --label 'My Class' --super <parent-iri> --lang en
SL-3
OWL Reasoning
shipped
Interfacefn materialize_owl2rl(store: &mut Store) → InferredTripleCount // owl.rs (sophia + oxigraph)
SPARQL# One of 9 OWL 2 RL rules — inverseOf materialization:
INSERT { GRAPH <urn:bra0:inferred> { ?b ?p2 ?a } }
WHERE {
?p1 owl:inverseOf ?p2 .
?a ?p1 ?b .
FILTER NOT EXISTS { ?b ?p2 ?a }
}
CLItopo owl materialize <ontology-dir>
SL-5
Data Mapping
shipped
InterfacermlEngine.apply(mapping: RmlTriplesMap, source: SourceHandle) → Stream<RdfQuad>
SPARQL# Retrieval of RDF produced by RML application:
SELECT ?s ?p ?o WHERE {
GRAPH <urn:source:csv-import-2026-04-16> { ?s ?p ?o }
}
CLItopo map apply mapping.rml.ttl --source data.csv --out instances.ttl
SL-7
Reactive Projection
planned
InterfaceuseReactiveQuery(sparql: string, dependencies: IRI[]) → { data, loading, error, refetch }
SPARQL# Any SELECT; runtime re-evaluates on mutations to listed dependency IRIs:
SELECT ?decision ?rationale WHERE {
?decision a evo:Decision ;
evo:rationale ?rationale .
} ORDER BY DESC(?decision)
CLItopo watch --query live.rq --deps urn:entity:X,urn:entity:Y
SL-9
KnowledgeSpace Templates
planned
InterfacetemplateBridge.apply(templateId: string, target: KSpaceIRI) → Result<AppliedTriples, ValidationError>
SPARQLCONSTRUCT {
?tbox ?p ?o .
?shape a sh:NodeShape ; ?sp ?so .
} WHERE {
GRAPH <urn:template:skos-taxonomy> {
{ ?tbox ?p ?o . FILTER(?p IN (rdf:type, rdfs:subClassOf, rdfs:label)) }
UNION
{ ?shape a sh:NodeShape ; ?sp ?so }
}
}
CLItopo template list | topo template apply <template-id> --to <kspace-iri> | topo template validate <template-id>
DP-2
SPARQL Operations
shipped
Interfacefn raw_query(q: &str) → QuerySolutions // Rust, cmd_query.rs
// TypeScript: oxigraphStore.query(sparql: string) → Promise<Results>
SPARQL# The meta-capability — SPARQL itself. Any SELECT/CONSTRUCT/ASK/UPDATE:
SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10
CLItopo query <dir> -q <file.rq|dir/> [--csv|--json|--summary]
DP-1
KG Ingestion
shipped
Interfacefn import(path: &Path, format: RdfFormat) → Result<TripleCount, ParseError> // rdfParser
SPARQL# Post-import retrieval of the ingested graph:
SELECT ?s ?p ?o WHERE {
GRAPH <urn:import:2026-04-16> { ?s ?p ?o }
} LIMIT 100
CLItopo import <file.ttl|file.jsonld|file.nt> [--graph <iri>]
DP-4
Export & Interoperability
shipped
InterfacerdfSerializer.serialize(store: Store, format: RdfFormat) → String
provenanceExporter.dcat(store: Store) → DcatCatalog
SPARQL# DCAT catalogue CONSTRUCT for export:
CONSTRUCT {
?dataset a dcat:Dataset ;
dcterms:title ?title ;
dcat:distribution [ a dcat:Distribution ; dcat:mediaType ?mt ] .
} WHERE {
?dataset a dcat:Dataset ;
dcterms:title ?title ;
dcterms:format ?mt .
}
CLItopo export <dir> --format ttl|jsonld|nt|dcat [--out <file>]
DP-8
Document Chunking
partial
Interfaceevaluate(chunks: &[Chunk]) → EvaluationReport // crates/bra0-chunking, 5 evaluators: SC + BI + ICC + DCC + RC
// Lineage: prov:wasRevisionOf via token-Jaccard, Blake3 idempotence cache
SPARQL# Retrieve a chunk:EvaluationReport with per-metric scores + lineage:
SELECT ?report ?metric ?score ?chunk ?prevChunk WHERE {
?report a chunk:EvaluationReport ;
chunk:hasMetric ?metric ;
chunk:score ?score ;
chunk:onChunk ?chunk .
OPTIONAL { ?chunk prov:wasRevisionOf ?prevChunk }
FILTER (?metric IN (chunk:SC, chunk:BI, chunk:ICC, chunk:DCC, chunk:RC))
} ORDER BY ?chunk ?metric
CLIeval-cli --input <file> --strategy fixed-size|semantic --target-chars <n> --features candle,coref
TP-1
Digital Perception
shipped
Interfacefn capture(dir: &Path) → ArchimateArtifactGraph // generic adapter, 6 format categories
SPARQL# Query captured artifacts with ArchiMate typing:
SELECT ?artifact ?format ?size ?date ?partOf WHERE {
?artifact a archi:Artifact ;
rdfs:label ?label ;
archi:format ?format ;
dcterms:extent ?size ;
dcterms:created ?date ;
dcterms:isPartOf ?partOf .
}
TP-4
Continuous Reflection
shipped
Interfacefn reflect(iot_traces: Graph, encounters: Graph) → CorrelationReport
SPARQL# Corroboration phase — cross-reference IoT traces with domain encounters:
SELECT ?iotObs ?encounter WHERE {
?iotObs a sosa:Observation ; sosa:resultTime ?t1 .
?encounter a evo:Encounter ; time:hasTime ?t2 .
FILTER (ABS(?t1 - ?t2) < "PT5M"^^xsd:duration)
}
NS-1
Gap Detection
shipped
Interfacefn detect_gaps(ontology: Graph, queries: &[SparqlQuery]) → GapReport // 10 built-in Gaur-taxonomy queries, oxigraph WASM
SPARQL# One of 10 Gaur-taxonomy queries — representation gap (unused class):
SELECT ?class WHERE {
?class a owl:Class .
FILTER NOT EXISTS { ?x a ?class }
}
CLItopo gaps <ontology-file> [--queries <custom-queries-dir>]
NS-4
Auditable Explanations
shipped
Interfaceprovenance.recordActivity(type: ProvActivityType, inputs: IRI[], outputs: IRI[], agent: IRI) → ProvActivity // provenance.ts, 250 LOC, 8 tests
SPARQL# Full PROV-O chain for an output — why does X exist?
SELECT ?act ?input ?agent ?start WHERE {
<urn:output:X> prov:wasGeneratedBy ?act .
?act prov:used ?input ;
prov:wasAssociatedWith ?agent ;
prov:startedAtTime ?start .
} ORDER BY ?start
CLItopo audit explain <entity-iri>
NS-5
Symbolic Cascade
shipped
Interfacefn cascade(input: Graph) → CascadeResult // cascade.rs — 5 stages: OWL 2 RL → NER tier 2 → merge → SHACL → result
SPARQL# TripleOrigin provenance on cascade output — which stage produced each triple:
SELECT ?s ?p ?o ?origin WHERE {
?s ?p ?o ;
bra0:tripleOrigin ?origin .
FILTER (?origin IN ("owl-materialization","ner-extraction","merge","shacl-validation"))
}
CLItopo cascade <input-dir> [--skip-ner]
NS-7
OWL Materialization
shipped
Interfacefn materialize_owl2rl(store: &mut Store) → InferredTripleCount // owl.rs, 9 OWL 2 RL rules, fixpoint, 14 ms on 522-triple OntoEDGY
SPARQL# Transitive property materialization (1 of 9 rules):
INSERT { GRAPH <urn:bra0:inferred> { ?a ?p ?c } }
WHERE {
?p a owl:TransitiveProperty .
?a ?p ?b . ?b ?p ?c .
FILTER NOT EXISTS { ?a ?p ?c }
}
CLItopo owl materialize <ontology-dir>
NS-8
Entity Recognition
shipped
InterfaceNerEngine::zero_shot_ner(text: &str, vocabulary: &SkosGraph) → Vec<EntityMatch> // ner.rs, candle BERT MiniLM-L6-v2 (22 MB, 384 dims), WASM 4.1 MB
SPARQL# Retrieve NER-extracted entities with confidence + origin:
SELECT ?entity ?label ?class ?confidence WHERE {
?entity a ?class ;
rdfs:label ?label ;
re:extractionConfidence ?confidence ;
re:extractionOrigin "ner-tier-2" .
} ORDER BY DESC(?confidence)
CLItopo ner <dir> --vocab <vocab.ttl>
Progressive coverage (D18 — revised 2026-06-06)Couverture progressive (D18 — révisé 2026-06-06)
20 of the 40 leaf capabilities remain undocumented operationally. Realistic target: 28 / 40 = 70% (all shipped + partial; the 6 planned capabilities land story-by-story as acceptance criteria, never speculatively; the 6 gap leaves — incl. NS-6 Temporal Validity — are R&D-blocked).
20 des 40 capacités-feuilles restent non documentées opérationnellement. Cible réaliste : 28 / 40 = 70% (shipped + partial ; les 6 capacités planned atterrissent story-par-story comme AC, jamais en spéculation ; les 6 feuilles gap — dont NS-6 Temporal Validity — sont bloquées R&D).
See also
Voir aussi
Feature Blueprint — full interactive blueprint with detailed descriptions, roadmap, and alignment matrix.
3-Layer Architecture — how GOV maps to Control Plane, SL to Semantic Layer, DP to Data Plane.
SHACL Shapes — the validation shapes that enforce data quality (GOV-4).
Ontology Catalog — the ontologies used by Semantic Layer capabilities.
Feature Blueprint — blueprint interactif complet avec descriptions détaillées, roadmap et matrice d'alignement.
Architecture 3 couches — comment GOV correspond au Control Plane, SL à la Semantic Layer, DP au Data Plane.
SHACL Shapes — les shapes de validation qui assurent la qualité des données (GOV-4).
Catalogue d'ontologies — les ontologies utilisées par les capacités de la Semantic Layer.