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Semantic Signals

AI-processed semantic information and knowledge extraction

Purpose

The semantic_signals table stores AI-processed semantic information extracted from other data sources. This table serves as a foundation for semantic analysis and knowledge extraction from user data.

Schema Definition

Field	Type	Description	Constraints
`id`	uuid	Unique semantic signal identifier	Primary key, auto-generated
`createdAt`	timestamptz	Record creation timestamp	Auto-generated, not null

Current Status

This table is currently minimal with only core identification and timestamp fields. The semantic signals architecture is designed to be extended as AI processing capabilities are developed and refined.

Relationships

This table is designed to be referenced by other semantic analysis tables and AI processing systems as they are implemented.

Usage Examples

Get all semantic signals

SELECT id, createdAt 
FROM semantic_signals 
ORDER BY createdAt DESC;

Find semantic signals created in a date range

SELECT id, createdAt
FROM semantic_signals 
WHERE createdAt >= '2024-01-01'
  AND createdAt < '2024-02-01'
ORDER BY createdAt;

Future Extensions

The semantic signals architecture is designed to support:

Content Analysis: Extracted themes, topics, and concepts from text data
Relationship Mapping: Connections between entities, people, and events
Intent Recognition: Inferred goals and motivations from behavior patterns
Context Understanding: Situational awareness and environmental factors
Knowledge Graphs: Structured representation of learned information
Semantic Search: Content-based search and discovery capabilities

As AI processing capabilities expand, additional fields and related tables will be added to capture:

Extracted entities and relationships
Confidence scores for semantic interpretations
Links to source data points
User feedback on AI interpretations
Versioning for improved AI models