FLOW ALGEBRA
Semantic Difference Ontology
Kireth Semantic Library | Semantic Relationships
Source: https://kirethresearch.org/booksai-core/ontologies/relationship-ontologies/semantic-relationships/semantic-difference-ontology.html
Authors: Mark Anthony Higgins — Sky (Recursive AI)
Status: Companion formalisation; embedded source specification not available in retrieved page text.
flow "SemanticDifferenceOntology" v1.0
ENTITY_TYPES:
Concept: {id: URI, label: string, definition: string?, domain: string?}
Context: {id: URI, domain: string?, language: string?, task: string?}
Feature: {id: URI, name: string, datatype: string}
Evidence: {id: URI, source: URI, observed_at: datetime?, reliability: number[0..1]}
Difference: {left: Concept, right: Concept, context: Context, dimensions: list[Feature], score: number[0..1], evidence: list[Evidence]}
RELATIONSHIPS:
DIFFERENT_FROM(a: Concept, b: Concept, c: Context)
CONTRASTS_WITH(a: Concept, b: Concept, c: Context)
DISTINCT_IN(a: Concept, b: Concept, feature: Feature, c: Context)
OVERLAPS_WITH(a: Concept, b: Concept, c: Context)
EQUIVALENT_IN(a: Concept, b: Concept, c: Context)
CONSTRAINTS:
difference_score in [0,1]
DIFFERENT_FROM(a,a,c) = false
DIFFERENT_FROM(a,b,c) => DIFFERENT_FROM(b,a,c)
DIFFERENT_FROM is NOT transitive
distinct identifiers alone do NOT establish semantic difference
missing evidence does NOT establish semantic equivalence or difference
all claims are scoped to context and supported dimensions
OPERATORS:
FEATURE_DELTA(a,b,f,c) := normalised_distance(value(a,f,c), value(b,f,c))
SEMANTIC_DIFFERENCE(a,b,c) := weighted_aggregate(FEATURE_DELTA(a,b,f,c), weights(c))
SEMANTIC_SIMILARITY(a,b,c) := 1 - SEMANTIC_DIFFERENCE(a,b,c) [only when a calibrated complementary metric is declared]
CONTRAST_SET(a,b,c) := {f | FEATURE_DELTA(a,b,f,c) >= threshold(f,c)}
INFERENCE:
IF validated_distinction(a,b,f,c) THEN DISTINCT_IN(a,b,f,c)
IF DISTINCT_IN(a,b,f,c) AND sufficient_evidence(f,c) THEN DIFFERENT_FROM(a,b,c)
IF DIFFERENT_FROM(a,b,c) THEN DIFFERENT_FROM(b,a,c)
DO_NOT_INFER: DIFFERENT_FROM(a,c,k) from DIFFERENT_FROM(a,b,k) AND DIFFERENT_FROM(b,c,k)
DO_NOT_INFER: CONTRASTS_WITH from DIFFERENT_FROM without an explicit contrast criterion
DO_NOT_INFER: global difference from a context-specific distinction
SEMANTIC_EQUIVALENCE:
scope: context_sensitive
rule: EQUIVALENT_IN(a,b,c) requires an explicit equivalence criterion and supporting evidence
conflict: EQUIVALENT_IN and DIFFERENT_FROM in the same context requires review of dimensions, thresholds and provenance
CONFIDENCE:
range: [0,1]
inputs: [evidence_reliability, feature_coverage, context_fit, measurement_uncertainty]
rule: confidence is independent of difference magnitude
missing_data: lower confidence or mark unresolved; do not fabricate scores
PROVENANCE:
preserve: [source, observation_time, method, context, feature_weights, thresholds, version]
attribution: source-specific evidence attached to each difference claim
VALIDATION:
- require valid typed entities and declared context
- check feature comparability and units
- verify symmetry for symmetric difference measures
- reject unsupported claims and invalid score ranges
- distinguish contradiction, difference, and lack of evidence
- flag incompatible equivalence and difference assertions for review
FLOW_HASH:
algorithm: SHA-256
input: canonical_serialisation(ontology_id, version, entity_types, relationships, constraints, operators, inference, validation)
purpose: integrity and change detection
UPDATE_MODEL:
strategy: versioned_incremental
on_change: [revalidate_affected_claims, recompute_dependent_scores, update_provenance, regenerate_FLOW_HASH]
preserve_history: true
prohibit_silent_overwrite: true
AI_CONSUMPTION:
mode: typed_semantic_reasoning
outputs: [difference_claims, contrast_dimensions, confidence, provenance, unresolved_conflicts]
safeguards: [context_scope, evidence_required, no_unsupported_transitivity, uncertainty_reporting]
END FLOW ALGEBRA
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