Evidence Ingestion is the system layer that captures raw retrieval outputs and transforms them into structured, normalized evidence units ready for classification, scoring, and validation.
Context Block
Page Type: Evidence System Layer
Function: Data Intake & Structuring Engine
Position: First stage in Evidence pipeline
Role: Converts retrieval output into structured evidence objects
This layer is the entry point of the Evidence system. Anything coming from retrieval cannot be used directly until it is standardized into a consistent evidence format.
Core Objective
- Convert raw retrieval outputs into structured evidence
- Normalize heterogeneous data formats
- Prepare evidence for classification and scoring
- Ensure traceability from retrieval to evidence layer
- Remove unstructured or invalid inputs early
Ingestion Pipeline
1. Raw Data Capture
Collects outputs from retrieval engine (documents, snippets, datasets, logs).
2. Format Normalization
Standardizes structure into unified evidence schema.
3. Noise Filtering
Removes irrelevant, duplicate, or corrupted data entries.
4. Metadata Enrichment
Adds source, timestamp, and contextual tags.
5. Evidence Object Creation
Transforms cleaned data into structured evidence units.
Evidence Object Schema
Each ingested evidence must contain:
- evidence_id
- source_reference
- raw_content
- structured_content
- retrieval_query_link
- timestamp
- initial_confidence (pre-scoring)
Input Types
- Text documents
- Structured datasets
- Web retrieval snippets
- API outputs
- System logs / signals
Normalization Rules
- Unify format into structured JSON-like schema
- Remove redundant or duplicated content
- Standardize encoding and metadata fields
- Preserve original source traceability
Integration in GEO Pipeline
Evidence Ingestion is the gateway between raw retrieval output and structured epistemic processing inside the GEO system.
Failure Modes
- Loss of source traceability during ingestion
- Incomplete normalization of heterogeneous data
- Duplicate evidence generation
- Incorrect metadata assignment
Structured Output Model
Each ingestion cycle produces:
- Structured Evidence Objects
- Normalized Metadata Set
- Traceability Map
- Noise Filter Report
- Ingestion Confidence Score
Relationship Block
Parent Layer: /evidence/
Upstream: Retrieval System
Downstream: Evidence Classification, Evidence Scoring
Connected Systems: Ontology Layer, Knowledge Graph, Answer Engine
Structured Summary
Evidence Ingestion is the foundational entry layer of the Evidence system. It transforms raw retrieval outputs into structured, traceable, and machine-readable evidence units.
This layer ensures that no unstructured or unreliable data enters the validation and scoring pipeline, preserving system integrity from the first step.