Workflows

FactHarbor workflows are simple, automated, focused on continuous improvement.

1. Core Principles

• Automated by default: AI processes everything
• Publish immediately: No centralized approval (removed in V0.9.50)
• Quality through monitoring: Not gatekeeping
• Fix systems, not data: Errors trigger improvements
• Human-in-loop: Only for edge cases and abuse

2. Claim Submission Workflow

2.1 Claim Extraction

When users submit content (text, articles, web pages), FactHarbor first extracts individual verifiable claims:

Input Types:

• Single claim: "The Earth is flat"
• Text with multiple claims: "Climate change is accelerating. Sea levels rose 3mm in 2023. Arctic ice decreased 13% annually."
• URLs: Web pages analyzed for factual claims

Extraction Process:

• LLM analyzes submitted content
• Identifies distinct, verifiable factual claims
• Separates claims from opinions, questions, or commentary
• Each claim becomes independent for processing

Output:

• List of claims with context
• Each claim assigned unique ID
• Original context preserved for reference

This extraction ensures:

• Each claim receives focused analysis
• Multiple claims in one submission are all processed
• Claims are properly isolated for independent verification
• Context is preserved for accurate interpretation

```
User submits → Duplicate detection → Categorization → Processing queue → User receives ID
```
Timeline: Seconds
No approval needed

2.5 Claim and Scenario Workflow

Claim & Scenario Workflow
This diagram shows how Claims are submitted and Scenarios are created and reviewed.

graph TB
 Start[User Submission
Text/URL/Single Claim]
 Extract{Claim Extraction
LLM Analysis}
 ValidateClaims{Validate Claims
Clear & Distinct?}
 Single[Single Claim]
 Multi[Multiple Claims]
 Queue[Parallel Processing]
 
 Process[Process Claim
AKEL Analysis]
 Evidence[Gather Evidence
LLM + Sources]
 Scenarios[Generate Scenarios
LLM Analysis]
 CrossRef[Cross-Reference
Evidence & Scenarios]
 Verdict[Generate Verdict
Confidence + Risk]
 Review{Confidence
Check}
 Publish[Publish Verdict]
 HumanReview[Human Review Queue]
 
 Start --> Extract
 Extract --> ValidateClaims
 ValidateClaims -->|Valid| Single
 ValidateClaims -->|Valid| Multi
 ValidateClaims -->|Invalid| Start
 
 Single --> Process
 Multi --> Queue
 Queue -->|Each Claim| Process
 
 Process --> Evidence
 Process --> Scenarios
 Evidence --> CrossRef
 Scenarios --> CrossRef
 CrossRef --> Verdict
 
 Verdict --> Review
 Review -->|High Confidence| Publish
 Review -->|Low Confidence| HumanReview
 HumanReview --> Publish
 
 style Extract fill:#e1f5ff
 style Queue fill:#fff4e1
 style Process fill:#f0f0f0
 style HumanReview fill:#ffe1e1

3. Automated Analysis Workflow

```
Claim from queue
↓
Evidence gathering (AKEL)
↓
Source evaluation (track record check)
↓
Scenario generation
↓
Verdict synthesis
↓
Risk assessment
↓
Quality gates (confidence > 40%? risk < 80%?)
↓
Publish OR Flag for improvement
```
Timeline: 10-30 seconds
90%+ published automatically

3.5 Evidence and Verdict Workflow

graph TD
 CLAIM[Claim] --> EVIDENCE[Evidence]
 EVIDENCE --> SOURCE[Source]
 SOURCE --> TRACK[Track Record Check]
 EVIDENCE --> SCENARIO[Scenario]
 SCENARIO --> VERDICT[Verdict]
 VERDICT --> CONFIDENCE[Confidence Score]
 TRACK --> QUALITY[Quality Score]
 QUALITY --> SCENARIO
 USER[User/Contributor] --> CLAIM
 USER --> EVIDENCE
 USER --> SCENARIO
 VERDICT --> DISPLAY[Display to Users]
 style CLAIM fill:#e1f5ff
 style VERDICT fill:#99ff99
 style CONFIDENCE fill:#ffff99

Evidence and Verdict Workflow - Shows how Claim, Evidence, and Verdict relate:

• Claim: Starting point, the assertion to evaluate
• Evidence: Gathered from sources to support/refute claim
• Source: Checked for track record quality
• Scenario: Possible interpretations based on evidence
• Verdict: Synthesized conclusion with confidence score
• Users: Can contribute at any stage

4. Publication Workflow

Standard (90%+): Pass quality gates → Publish immediately with confidence scores
High Risk (<10%): Risk > 80% → Moderator review
Low Quality: Confidence < 40% → Improvement queue → Re-process

5. User Contribution Workflow

```
Contributor edits → System validates → Applied immediately → Logged → Reputation earned
```
No approval required (Wikipedia model)
New contributors (<50 reputation): Limited to minor edits

5.5 Quality and Audit Workflow

Quality Gates Flow

flowchart TB
    subgraph Input[Input]
        CLAIM[Extracted Claim]
    end

    subgraph Gate1[Gate 1 Claim Validation]
        G1_CHECK{Is claim factual}
        G1_OPINION[Opinion Detection]
        G1_SPECIFIC[Specificity Check]
        G1_FUTURE[Future Prediction]
    end

    subgraph Research[Research]
        EVIDENCE[Gather Evidence]
    end

    subgraph Gate4[Gate 4 Verdict Confidence]
        G4_COUNT{Evidence Count}
        G4_QUALITY{Source Quality}
        G4_AGREE{Evidence Agreement}
        G4_TIER[Assign Confidence Tier]
    end

    subgraph Output[Output]
        PUBLISH[Publish Verdict]
        EXCLUDE[Exclude]
        LOWCONF[Flag for Review]
    end

    CLAIM --> G1_CHECK
    G1_CHECK --> G1_OPINION
    G1_OPINION --> G1_SPECIFIC
    G1_SPECIFIC --> G1_FUTURE
    G1_FUTURE -->|Pass| EVIDENCE
    G1_FUTURE -->|Fail| EXCLUDE
    EVIDENCE --> G4_COUNT
    G4_COUNT -->|2 or more| G4_QUALITY
    G4_COUNT -->|less than 2| LOWCONF
    G4_QUALITY -->|0.6 or more| G4_AGREE
    G4_QUALITY -->|less than 0.6| LOWCONF
    G4_AGREE -->|60 percent or more| G4_TIER
    G4_AGREE -->|less than 60 percent| LOWCONF
    G4_TIER -->|HIGH or MEDIUM| PUBLISH
    G4_TIER -->|LOW| LOWCONF

Gate Details

Gate 1: Claim Validation

Purpose: Ensure extracted claims are factual assertions that can be verified.

Gate 4: Verdict Confidence Assessment

Purpose: Only display verdicts with sufficient evidence and confidence.

Not Yet Implemented

Gate 2: Contradiction Search (planned) - Counter-evidence actively searched

Gate 3: Uncertainty Quantification (planned) - Data gaps identified and disclosed

6. Flagging Workflow

```
User flags issue → Categorize (abuse/quality) → Automated or manual resolution
```
Quality issues: Add to improvement queue → System fix → Auto re-process
Abuse: Moderator review → Action taken

7. Moderation Workflow

Automated pre-moderation: 95% published automatically
Moderator queue: Only high-risk or flagged content
Appeal process: Different moderator → Governing Team if needed

8. System Improvement Workflow

Weekly cycle:
```
Monday: Review error patterns
Tuesday-Wednesday: Develop fixes
Thursday: Test improvements
Friday: Deploy & re-process
Weekend: Monitor metrics
```
Error capture:
```
Error detected → Categorize → Root cause → Improvement queue → Pattern analysis
```
A/B Testing:
```
New algorithm → Split traffic (90% control, 10% test) → Run 1 week → Compare metrics → Deploy if better
```

9. Quality Monitoring Workflow

Continuous: Every hour calculate metrics, detect anomalies
Daily: Update source track records, aggregate error patterns
Weekly: System improvement cycle, performance review

10. Source Track Record Workflow

Initial score: New source starts at 50 (neutral)
Daily updates: Calculate accuracy, correction frequency, update score
Continuous: All claims using source recalculated when score changes

11. Re-Processing Workflow

Triggers: System improvement deployed, source score updated, new evidence, error fixed
Process: Identify affected claims → Re-run AKEL → Compare → Update if better → Log change

12. Related Pages

• Requirements
• Architecture
• Data Model