Summary Ontology

FLOW ALGEBRA
Summary Ontology
Kireth Semantic Research Archive

PAGE:
https://kirethresearch.org/booksai-core/ontologies/metadata-ontologies/descriptive-metadata/summary-ontology.html

AUTHORS:
Mark Anthony Higgins — Sky (Recursive AI)

FLOW "SummaryOntology" v4.0

DOMAIN := MetadataOntologies
SUBDOMAIN := DescriptiveMetadata
ONTOLOGY := SummaryOntology

ENTITY Summary {
    definition:
        "A condensed descriptive representation of a resource that preserves
         its principal meaning, topics, events, arguments, findings or purpose
         while reducing detail for faster discovery, selection, understanding
         and machine consumption.";
    objectives: [
        ContentCondensation,
        ResourceUnderstanding,
        Discovery,
        Selection,
        SemanticRetrieval,
        ContextGeneration,
        MachineInterpretability
    ];
}

SummaryEntity := {
    Summary,
    Resource,
    SummaryValue,
    ShortSummary,
    ExtendedSummary,
    ExtractiveSummary,
    AbstractiveSummary,
    GeneratedSummary
};

MetadataEntity := {
    MetadataRecord,
    SummaryProperty,
    Language,
    Identifier,
    Provenance,
    Confidence,
    Version
};

ContentEntity := {
    MainTopic,
    KeyPoint,
    Event,
    Argument,
    Finding,
    Purpose,
    Context
};

Summary SUMMARISES Resource;
MetadataRecord CONTAINS SummaryStatement;
Summary MAY_REPRESENT MainTopic;
Summary MAY_REPRESENT KeyPoint;
Summary MAY_REPRESENT Finding;
Summary HAS Language;
Provenance SUPPORTS SummaryStatement;
Version REPRESENTS SummaryState;

SummaryFlow :=
    Resource
    -> IdentifyResource
    -> DetermineSummaryPurpose
    -> AnalyseResourceContent
    -> IdentifySalientInformation
    -> SelectSummaryTypeAndLength
    -> GenerateOrComposeSummary
    -> ValidateAgainstResource
    -> AttachLanguageAndProvenance
    -> StoreInMetadataRecord
    -> IndexForDiscovery
    -> MaintainAndVersion;

Resource :=
    ThingRepresentedInCondensedFormBySummary;

Resource MAY_BE {
    Document,
    Article,
    Report,
    Book,
    Dataset,
    Audio,
    Video,
    WebPage,
    EventRecord,
    KnowledgeObject
};

Summary :=
    CondensedRepresentationOfResourceMeaningOrContent;

SummaryValue :=
    TextualOrStructuredContentOfSummary;

SummaryStatement :=
    Resource
    -> SummaryProperty
    -> SummaryValue;

SummaryProperty MAY_BE {
    summary,
    shortSummary,
    extendedSummary,
    executiveSummary,
    generatedSummary
};

ShortSummary :=
    HighlyCondensedRepresentationOfResource;

ExtendedSummary :=
    LongerCondensedRepresentationPreservingMoreContextAndDetail;

ExecutiveSummary :=
    DecisionOrManagementOrientedSummaryHighlightingPrincipalIssuesFindingsAndActions;

ExtractiveSummary :=
    SummaryConstructedFromSelectedSourcePassagesOrSentences;

AbstractiveSummary :=
    NewlyGeneratedTextRepresentingSourceMeaning;

GeneratedSummary :=
    SummaryProducedAutomaticallyBySoftwareOrAI;

HumanSummary :=
    SummaryWrittenOrCuratedByHumanAgent;

SummaryPurpose MAY_INCLUDE {
    Discovery,
    Selection,
    Preview,
    DecisionSupport,
    Accessibility,
    MachineContext
};

SummaryAudience MAY_BE {
    General,
    Specialist,
    Executive,
    Researcher,
    Machine
};

AudienceSpecificSummary SHOULD_PRESERVE CoreResourceMeaning;

MainTopic :=
    PrincipalSubjectRepresentedByResource;

KeyPoint :=
    ImportantStatementOrIdeaSelectedForSummary;

Event :=
    SignificantOccurrenceRepresentedInResource;

Argument :=
    PrincipalClaimReasoningOrPositionRepresentedByResource;

Finding :=
    SignificantReportedObservationOrResult;

Purpose :=
    ReasonResourceOrUnderlyingWorkExists;

Summary MAY_INCLUDE DifferentContentElementsAccordingToResourceTypeAndPurpose;

SummaryCompression :=
    ReductionFromSourceContentLengthToSummaryLength;

CompressionRatio :=
    SummaryLength / SourceLength;

HigherCompression MAY_INCREASE RiskOfInformationLoss;

SummaryLength MAY_BE MeasuredIn {
    Characters,
    Words,
    Sentences,
    Tokens
};

MetadataSchema MAY_DEFINE SummaryLengthConstraint;

LengthConstraint SHOULD_NOT CauseMaterialDistortionOfMeaning;

SummaryCoverage :=
    DegreeToWhichImportantSourceContentIsRepresented;

SummaryAccuracy :=
    DegreeToWhichSummaryFaithfullyRepresentsSource;

SummaryRelevance :=
    DegreeToWhichIncludedInformationMatchesSummaryPurpose;

SummaryCoherence :=
    DegreeToWhichSummaryFormsLogicalReadableRepresentation;

SummaryConciseness :=
    DegreeToWhichSummaryAvoidsUnnecessaryDetail;

SummaryQuality MAY_INCLUDE {
    Accuracy,
    Coverage,
    Relevance,
    Coherence,
    Conciseness,
    Provenance
};

Salience :=
    EstimatedImportanceOfSourceInformationForSummaryPurpose;

Salience MAY_BE DeterminedBy {
    HumanJudgement,
    Position,
    Frequency,
    EntityImportance,
    SemanticSimilarity,
    ModelPrediction
};

SummaryGeneration :=
    SourceContent
    -> Analyse
    -> SelectSalientInformation
    -> Condense
    -> ProduceSummary;

ManualSummarisation :=
    HumanAgent
    -> ReadOrInspectResource
    -> ComposeSummary;

AutomaticSummarisation :=
    Software
    -> AnalyseResource
    -> GenerateSummary;

AIGeneratedSummary :=
    GeneratedSummaryProducedByAIModel;

AIGeneratedSummary SHOULD_HAVE {
    GenerationMethod,
    ModelVersion,
    Provenance,
    Confidence,
    ValidationStatus
};

ExtractiveSummarisation MAY_REDUCE UnsupportedGenerationRisk
BUT MAY_HAVE CoherenceOrCoverageLimitations;

AbstractiveSummarisation MAY_IMPROVE ReadabilityAndCompression
BUT MAY_INTRODUCE UnsupportedClaims;

UnsupportedClaim :=
    SummaryStatementNotAdequatelySupportedBySourceResource;

IF UnsupportedClaimDetected
THEN SummaryAccuracy SHOULD_DECREASE
AND ValidationReview SHOULD_BE Triggered;

Contradiction :=
    SummaryStatementInconsistentWithVerifiedSourceContent;

IF ContradictionDetected
THEN Summary SHOULD_NOT_BE TreatedAsAuthoritativeWithoutCorrection;

Omission :=
    ImportantSourceInformationAbsentFromSummary;

CriticalOmission MAY_REDUCE SummaryCoverageOrMisrepresentMeaning;

Distortion :=
    CondensationThatChangesMeaningOrRelativeImportanceOfSourceContent;

Distortion SHOULD_BE TreatedAs SummaryQualityFailure;

SummaryValidation MAY_CHECK {
    Requiredness,
    Datatype,
    Language,
    Length,
    SourceConsistency,
    UnsafeMarkup
};

IF SchemaRequiresSummary
AND SummaryMissing
THEN ValidationStatus := violation;

SummaryLanguage :=
    LanguageInWhichSummaryIsExpressed;

SummaryLanguage MAY_DIFFER_FROM ResourceLanguage;

MultilingualResource MAY_HAVE MultipleSummariesInDifferentLanguages;

TranslatedSummary :=
    SummaryTranslatedIntoAnotherLanguage;

TranslatedSummary SHOULD_PRESERVE MeaningOfSourceSummaryOrResource;

CrossLingualSummary :=
    SummaryProducedInLanguageDifferentFromPrimarySourceLanguage;

CrossLingualSummarisation MAY_COMBINE TranslationAndSummarisation;

SummarySource :=
    OriginFromWhichSummaryWasObtained;

Source MAY_BE {
    Resource,
    Creator,
    Publisher,
    Repository,
    MetadataAgent,
    AIModel
};

SummaryProvenance MAY_INCLUDE {
    Source,
    Creator,
    GenerationMethod,
    Timestamp,
    ModelVersion
};

SummaryIdentifier MAY_BE AssignedWhenSummaryManagedAsIndependentMetadataObject;

SummaryVersion :=
    IdentifiedRevisionOfSummary;

SummaryHistory MAY_PRESERVE PreviousVersionsWhereRequired;

SummaryChange MAY_INCLUDE {
    Correction,
    Shortening,
    Expansion,
    Translation,
    Replacement
};

ResourceRevision MAY_REQUIRE SummaryRegenerationOrReview;

SummaryNormalisation MAY_INCLUDE {
    UnicodeNormalisation,
    WhitespaceNormalisation,
    LanguageTagNormalisation
};

OriginalDisplayText SHOULD_BE PreservedWhereRequired;

Summary MAY_CONTAIN MarkupAccordingToMetadataSyntax;

UnsafeMarkup SHOULD_BE SanitisedOrRejectedAccordingToPolicy;

SummaryIndex :=
    SearchIndexBuiltFromSummaryText;

SummaryIndex MAY_SUPPORT {
    FullTextSearch,
    KeywordSearch,
    EntitySearch,
    SemanticSearch
};

Summary MAY_BE UsedAs RetrievalSurrogateForLongResource;

RetrievalSurrogate :=
    ShortRepresentationUsedToEstimateResourceRelevanceBeforeFullRetrieval;

Summary MAY_BE ConvertedTo Embedding;

SummaryEmbedding MAY_SUPPORT SemanticSimilaritySearch;

VectorSimilarity != FactualEquivalence;

KeywordExtraction MAY_USE SummaryAsInput;

SubjectClassification MAY_USE SummaryAsEvidence;

NamedEntityRecognition MAY_EXTRACT EntitiesFromSummary;

ExtractedEntity SHOULD_BE DistinguishedFrom ExplicitlyCuratedMetadata;

SemanticSearch MAY_USE SummaryFor {
    QueryMatching,
    Ranking,
    ConceptExtraction,
    ResourceSelection
};

KnowledgeGraph MAY_LINK SummaryTo Resource;

ResolvedEntitiesAndConceptsMentionedInSummary MAY_BE LinkedToGraph;

Title IDENTIFIES Resource;
Description EXPLAINS Resource;
Summary CONDENSES Resource;

Summary MAY_BE ASubtypeOfDescriptionAccordingToMetadataModel;

Summary != AbstractByDefinition
ALTHOUGH TheirFunctions MAY_OVERLAP;

Abstract MAY_FOLLOW FormalDomainConvention;
Summary MAY_BE GeneralPurposeCondensation;

MetadataSchema MAY_DEFINE SummaryPropertyAndConstraints;

DublinCore MAY_REPRESENT GeneralSummaryThrough descriptionOrProfileSpecificProperty;

SchemaOrg MAY_REPRESENT SummaryUsing descriptionOrAbstractAccordingToResourceTypeAndVocabulary;

RDF MAY_REPRESENT:
    Resource
    -> summaryProperty
    -> SummaryLiteral;

JSONLD MAY_SERIALISE SummaryWithLanguageAndSemanticContext;

MetadataRepository MAY_STORE SummaryMetadata;

MetadataRegistry MAY_REGISTER SummaryPropertiesAndProfiles;

MetadataCatalogue MAY_DISPLAY SummaryForResourceSelection;

SummaryInteroperability MAY_REQUIRE {
    SharedPropertySemantics,
    LanguageTags,
    ResourceIdentifiers,
    SchemaMapping
};

SummaryCrosswalk :=
    MappingBetweenSummaryOrDescriptionPropertiesAcrossSchemas;

AccessControl MAY_RESTRICT SummaryIndependentlyOfResource;

Summary MAY_CONTAIN SensitiveOrConfidentialInformation;

PrivacyPolicy SHOULD_APPLY_TO SummaryContent;

SummarySecurity MAY_INCLUDE {
    InputValidation,
    OutputEscaping,
    AccessControl,
    ProvenanceIntegrity
};

AI MAY_USE SummaryFor {
    Retrieval,
    Classification,
    QuestionAnswering,
    Planning,
    ContextCompression
};

RetrievalAugmentedGeneration MAY_USE SummaryFor {
    SourceDiscovery,
    Ranking,
    ContextCompression,
    PreliminaryEvidence
};

Summary MAY_REDUCE ContextWindowUse
BUT ImportantDetailsMayBeLost;

HighPrecisionClaimVerification SHOULD_PREFER UnderlyingSourceWhereAvailable;

MachineReadableSummary SHOULD_PRESERVE {
    SummaryType,
    Language,
    ResourceIdentifier,
    Provenance,
    Confidence,
    Version
};

# ---------- SEMANTIC REASONING ----------
IF MetadataValueCondensesPrincipalMeaningOrContentOfResource
THEN SummaryClassification := supported;

IF SummaryUsesOnlySelectedSourcePassages
THEN Summary MAY_BE ClassifiedAs ExtractiveSummary;

IF SummaryUsesNewlyGeneratedWording
THEN Summary MAY_BE ClassifiedAs AbstractiveSummary;

IF SummaryGeneratedByAI
THEN GenerationProvenance SHOULD_BE Preserved;

IF SummaryContainsUnsupportedClaim
THEN Confidence SHOULD_DECREASE
AND Review SHOULD_BE Triggered;

IF SummaryOmitsCriticalContextAndChangesInterpretation
THEN SummaryQuality SHOULD_DECREASE;

IF ResourceVersionChangesMaterially
THEN ExistingSummary SHOULD_BE RevalidatedOrRegenerated;

# ---------- SEMANTIC EQUIVALENCE ----------
SEMANTIC_EQUIVALENCE {
    "summary" ~= "resource summary" WHEN metadata_context;
    "short summary" ~= "brief summary";
    "extended summary" ~= "detailed summary";
    "generated summary" ~= "automatically generated summary";
    "extractive summary" ~= "source-extracted summary";
    "abstractive summary" ~= "generated semantic summary";
    "summary metadata" ~= "condensed description metadata";
    "summary version" ~= "summary revision";
}

# ---------- QUERY FLOW ----------
QUERY(q) ->
    NORMALISE(q) ->
    IDENTIFY_RESOURCE(q) ->
    IDENTIFY_SUMMARY(q) ->
    IDENTIFY_SUMMARY_TYPE_AND_PURPOSE(q) ->
    IDENTIFY_LANGUAGE_AND_AUDIENCE(q) ->
    IDENTIFY_MAIN_TOPICS_KEY_POINTS_AND_FINDINGS(q) ->
    IDENTIFY_SOURCE_AND_PROVENANCE(q) ->
    VALIDATE_SUMMARY_AGAINST_RESOURCE(q) ->
    SCORE_CONFIDENCE(q) ->
    RETURN_RELEVANT_SUMMARY_KNOWLEDGE;

# ---------- CONFIDENCE ----------
CONFIDENCE(assertion) :=
    weighted_mean(
        source_reliability,
        summary_accuracy,
        source_consistency,
        coverage_quality,
        provenance_quality,
        contextual_relevance
    );

CONFIDENCE >= 0.90 => HIGH;
CONFIDENCE >= 0.70 AND < 0.90 => MODERATE;
CONFIDENCE < 0.70 => REVIEW;

# ---------- AI CONSUMPTION ----------
AI_CONSUMPTION {
    primary_entity: Summary;
    ontology: SummaryOntology;
    parse_entities: true;
    parse_relationships: true;
    preserve_relationship_direction: true;
    resolve_semantic_equivalence: true;
    execute_reasoning_rules: true;
    apply_confidence_weighting: true;
    preserve_provenance: true;
}

# ---------- UPDATE MODEL ----------
UPDATE_MODEL {
    new_summary:
        identify_resource
        -> classify_summary_type
        -> identify_purpose_and_audience
        -> attach_language
        -> attach_source
        -> attach_provenance
        -> validate_against_resource
        -> assign_confidence
        -> integrate;

    summary_revision:
        preserve_previous_version
        -> apply_changes
        -> validate_source_consistency
        -> update_index_and_embedding
        -> recompute_confidence
        -> regenerate_flow_hash;

    generated_summary:
        record_generation_method
        -> identify_source_resource
        -> validate_supported_claims
        -> assess_coverage
        -> assign_confidence
        -> human_review_if_required
        -> integrate;

    conflict:
        preserve_provenance
        -> compare_summary_with_resource_and_sources
        -> adjust_confidence
        -> flag_review;
}

# ---------- FLOW HASH ----------
FLOW_HASH_INPUT :=
    DOMAIN
    + SUBDOMAIN
    + ONTOLOGY
    + SummaryEntity
    + MetadataEntity
    + ContentEntity
    + Summary
    + SummaryGeneration
    + SummaryQuality
    + RELATIONSHIPS
    + SEMANTIC_REASONING
    + SEMANTIC_EQUIVALENCE
    + UPDATE_MODEL;

FLOW_HASH :=
    HASH(FLOW_HASH_INPUT);

# ---------- TERMINAL ----------
SummaryOntology
    -> IdentifySummarisedResource
    -> DetermineSummaryPurposeAudienceAndType
    -> AnalyseResourceForSalientInformation
    -> CondenseMainTopicsEventsArgumentsAndFindings
    -> PreserveLanguageAndDisplayText
    -> AttachResourceIdentifierSourceAndProvenance
    -> ValidateAccuracyCoverageAndUnsupportedClaims
    -> StoreAndVersionSummaryMetadata
    -> IndexForFullTextAndSemanticRetrieval
    -> ExtractCandidateEntitiesSubjectsAndKeywords
    -> EnforcePrivacySecurityAndAccess
    -> SupportAIContextCompressionAndMachineConsumption
    -> MaintainReliableCondensedResourceKnowledge;

END FLOW