# semantic_library/domain_ontology.yaml # Version: 1.0 # Description: Defines the core concepts, entities, properties, and relationships # for the narrative library's domain. This acts as the foundational schema. # --- NOTES ON STRUCTURE --- # This file could adopt a more formal ontology language like OWL (via RDF/XML or Turtle) # or a structured JSON-LD format for greater interoperability and reasoning capabilities # by standard ontology tools. For simplicity with YAML, a custom schema is used here. # Key sections to define: # 1. Entity Types: Core objects in the domain. # 2. Property Definitions: Attributes of entities, including data types and constraints. # 3. Relationship Types: How entities can be connected, their cardinality, and properties of relationships. # 4. Taxonomies/Hierarchies: "is-a" or "part-of" relationships (e.g., for driver types). # 5. Controlled Vocabularies: Predefined sets of values for certain properties (enums). # Example Structure (Conceptual): controlled_vocabularies: driver_type_enum: - Macroeconomic - Fundamental - CompanySpecific - IndustrySpecific - Technical - Geopolitical - EventDriven impact_direction_enum: - Positive - Negative - Neutral - Variable time_horizon_enum: - "0-3 months" - "3-6 months" - "6-12 months" - "1-2 years" - "2-5 years" - "Long-term (>5 years)" probability_qualifier_enum: # For qualitative probability expression - VeryLow (<0.1) - Low (0.1-0.3) - Medium (0.3-0.6) - High (0.6-0.85) - VeryHigh (>0.85) agent_type_enum: # From Adam v19.1 README - MarketSentimentAgent - MacroeconomicAnalysisAgent - GeopoliticalRiskAgent - IndustrySpecialistAgent - FundamentalAnalysisAgent - TechnicalAnalysisAgent - RiskAssessmentAgent - PredictionMarketAgent - AlternativeDataAgent - LegalAgent - ModelBuilderAgent # Added from README - SupplyChainGuardianAgent # Added - AlgorithmicTraderAgent # Added - DiscussionChairAgent # Added - CryptoAgent # ... other agent types from README simulation_type_enum: # From Adam v19.1 README - CreditRatingAssessment - InvestmentCommittee - PortfolioOptimization - StressTesting - MergerAcquisition # ... other simulation types entity_types: - name: Company description: "A business entity." properties: - name: id # Primary Key type: string is_required: true description: "Unique ticker symbol or identifier." - name: name type: string is_required: true - name: industryId # Foreign Key to Industry type: string - name: financials # Nested object type: object # Could reference a "FinancialStatement" entity type properties: - name: revenue_mn_usd type: number - name: pe_ratio type: number # ... other financial metrics - name: tradingLevels # Nested object type: object properties: - name: price type: number # ... other trading metrics # ... other company properties - name: Industry description: "A category of economic activity." properties: - name: id type: string is_required: true - name: name type: string # ... - name: Driver # As defined in drivers_knowledge_base.yaml, but schema here description: "A factor influencing entities." properties: - name: id type: string is_required: true - name: name type: string - name: type type: string # Could be restricted by driver_type_enum # ... other properties as in drivers_knowledge_base.yaml # The actual content/instances are in drivers_knowledge_base.yaml, # this ontology would define the *structure* of a driver. - name: MacroFactor description: "A macroeconomic indicator or condition." properties: # ... - name: trend type: string # Could be an enum for Increasing, Decreasing, Stable - name: Event description: "A discrete occurrence that can impact entities or drivers." properties: - name: event_id type: string - name: event_type # e.g., ProductLaunch, EarningsAnnouncement, GeopoliticalCrisis type: string - name: date type: date - name: significance_score type: number # 0-1 # ... - name: TradingSignal # Example of a more abstract concept description: "An indicator derived from market data suggesting a potential trading action or market state." properties: - name: signal_id type: string - name: signal_type # e.g., MomentumPositive, MeanReversionSetup type: string - name: confidence_level type: number - name: related_asset_id # e.g., company_id type: string - name: Agent description: "A specialized AI component responsible for a specific domain or task." properties: - name: agent_id type: string is_required: true - name: name # e.g., "Legal Eagle" type: string is_required: true - name: agent_type type: string # from agent_type_enum description: "The specialized type of the agent." - name: description type: string - name: capabilities type: array items: {type: string} - name: data_sources_used # Refs to DataSource IDs type: array items: {type: string} - name: status # e.g., Active, Inactive type: string - name: Simulation description: "A defined scenario or model for testing hypotheses or exploring outcomes." properties: - name: simulation_id type: string is_required: true - name: name # e.g., "Credit Rating Assessment Simulation" type: string - name: simulation_type type: string # from simulation_type_enum - name: description type: string - name: input_parameters type: object - name: environment_id # Links to simulation_environment_definitions.yaml type: string - name: involved_agent_ids # Agents participating type: array items: {type: string} - name: DataSource description: "An external or internal source of data used by Agents or the system." properties: - name: source_id type: string is_required: true - name: name # e.g., "SEC Filings", "Twitter API" type: string - name: type # e.g., API, Database, NewsFeed type: string - name: description type: string - name: update_frequency type: string - name: access_details type: object - name: data_granularity # e.g., company-level, market-level, transaction-level type: string - name: FinancialInstrument description: "A tradable asset of any kind, e.g., stock, bond, crypto." properties: - name: instrument_id # e.g., Ticker, ISIN, CUSIP type: string is_required: true - name: name type: string - name: instrument_type # e.g., Equity, FixedIncome, Cryptocurrency, Derivative type: string - name: issuer_id # e.g., company_id if stock/bond type: string - name: exchange_id # Where it's traded type: string # ... other relevant financial instrument properties - name: EconomicIndicator # More specific than MacroFactor description: "A specific statistic about economic activity." # inherits_from: MacroFactor (conceptually) properties: - name: indicator_id # e.g., GDP_ crescita_QOQ, CPI_YoY type: string is_required: true - name: name type: string - name: description type: string - name: source_agency # e.g., BLS, BEA, Federal Reserve type: string - name: release_frequency type: string - name: unit_of_measure # e.g., %, $, Millions type: string - name: current_value # Could also be part of a TimeSeries entity type: number - name: trend type: string - name: RegulatoryBody description: "An agency or organization responsible for financial regulation." properties: - name: body_id type: string is_required: true - name: name # e.g., "Securities and Exchange Commission" type: string - name: acronym # e.g., "SEC" type: string - name: jurisdiction # e.g., "USA", "EU" type: string - name: areas_of_oversight type: array items: {type: string} - name: InvestmentThesis description: "A reasoned argument for a particular investment strategy or decision." properties: - name: thesis_id type: string is_required: true - name: title type: string - name: summary type: string - name: supporting_driver_ids type: array items: {type: string} - name: target_instrument_ids type: array items: {type: string} - name: confidence_level type: number - name: time_horizon type: string - name: created_by_agent_id # Agent who formulated it type: string relationship_types: - name: BELONGS_TO_INDUSTRY description: "A company is part of an industry." domain: Company # Source entity type range: Industry # Target entity type cardinality: "many-to-one" - name: AFFECTED_BY_DRIVER description: "An entity (Company, Industry) is influenced by a driver." domain: [Company, Industry] # Can have multiple source types range: Driver cardinality: "many-to-many" properties: # Relationships can also have properties - name: relevance_score type: number # How relevant this driver is to this specific entity - name: activation_status # Inferred by Reasoning Engine type: boolean - name: TRIGGERS_DRIVER # An event might trigger a driver domain: Event range: Driver cardinality: "many-to-many" - name: IMPACTS_VARIABLE # A driver's effect impacts a specific variable description: "Connects a DriverImpact (sub-object of Driver) to a target variable string." # This is more conceptual for how the impact_model links to the ontology. # domain: DriverImpact (conceptual) # range: string (representing a path like 'company.financials.revenue') - name: USES_DATA_SOURCE domain: Agent range: DataSource cardinality: "many-to-many" - name: GENERATES_INSIGHT_FROM_DRIVER domain: Agent range: Driver cardinality: "many-to-many" properties: - name: insight_summary type: string - name: confidence_score type: number - name: PARTICIPATES_IN_SIMULATION domain: Agent range: Simulation cardinality: "many-to-many" - name: ISSUED_BY # e.g., Stock issued by Company domain: FinancialInstrument range: Company cardinality: "many-to-one" - name: TRADED_ON_EXCHANGE # e.g., Stock traded on NYSE domain: FinancialInstrument # Could be an Exchange entity range: string cardinality: "many-to-many" - name: MONITORED_BY_REGULATOR domain: [Company, Industry, FinancialInstrument] range: RegulatoryBody cardinality: "many-to-many" - name: BASED_ON_THESIS domain: string # e.g., InvestmentPortfolio, TradingStrategy range: InvestmentThesis cardinality: "many-to-one" - name: TARGETS_INSTRUMENT domain: InvestmentThesis range: FinancialInstrument cardinality: "many-to-many" - name: SUPPORTS_THESIS domain: Driver range: InvestmentThesis cardinality: "many-to-many" # Taxonomies (Example) # driver_taxonomy: # Macroeconomic: # children: # - InterestRateRelated # - InflationRelated # - GDPGrowthRelated # Fundamental: # children: # - CompanySpecificFundamental # - IndustrySpecificFundamental # ... # This file would be loaded by the ReasoningEngine or a dedicated ontology manager # to validate data structures, understand relationships, and potentially perform # more advanced semantic reasoning if integrated with an ontology reasoner.