POC Requirements

 Status: ✅ Approved for Development Version: 3.0 (Aligned with Main Requirements) Goal: Prove that AI can extract claims and determine verdicts automatically without human intervention InformationCore Philosophy: POC validates the Main Requirements through simplified implementation. All POC features map to formal FR/NFR requirements. == 1. POC Overview == === 1.1 What POC Tests === Core Question:

 Can AI automatically extract factual claims from articles and evaluate them with reasonable verdicts? What we're proving:

• AI can identify factual claims from text
• AI can evaluate those claims with structured evidence
• Quality gates can filter unreliable outputs
• The core workflow is technically feasible What we're NOT proving:
• Production-ready reliability (that's POC2)
• User-facing features (that's Beta 0)
• Full IFCN compliance (that's V1.0) === 1.2 Requirements Mapping === POC1 implements a subset of the full system requirements defined in Main Requirements. Scope Summary:
• In Scope: 8 requirements (7 FRs + 1 NFR)
• Partial: 3 NFRs (simplified versions)
• Out of Scope: 19 requirements (deferred to later phases) == 2. Requirements Scope Matrix == SuccessRequirements Traceability: This matrix shows which Main Requirements are implemented in POC1, providing full traceability between POC and system requirements. |=Requirement|=POC1 Status|=Implementation Level|=Notes

• ✅ AKEL extracts claims using LLM
• ✅ Each claim includes original text reference
• ✅ Claims are identified as factual/non-factual
• ❌ No advanced claim parsing (added in POC2) Acceptance Criteria:
• Extracts 3-5 claims from typical article
• Identifies factual vs non-factual claims
• Quality Gate 1 validates extraction === 3.2 FR3: Multiple Scenarios (Full Implementation) === Main Requirement: Generate multiple interpretation scenarios for ambiguous claims POC Implementation:
• ✅ AKEL generates 2-3 scenarios per claim
• ✅ Scenarios capture different interpretations
• ✅ Each scenario is evaluated separately
• ✅ Verdict considers all scenarios Acceptance Criteria:
• Generates 2+ scenarios for ambiguous claims
• Scenarios are meaningfully different
• All scenarios are evaluated === 3.3 FR4: Analysis Summary (Basic Implementation) === Main Requirement: Provide user-friendly summary of analysis POC Implementation:
• ✅ Simple text summary generated
• ❌ No rich formatting (added in Beta 0)
• ❌ No visual elements (added in Beta 0)
• ❌ No interactive features (added in Beta 0) POC Format:
  ```
  Claim: [extracted claim]
  Scenarios: [list of scenarios]
  Evidence: [supporting/opposing evidence]
  Verdict: [probability with uncertainty]
  ``` === 3.4 FR5-FR6: Evidence Collection & Evaluation (Full Implementation) === Main Requirements:
• FR5: Collect supporting and opposing evidence
• FR6: Evaluate evidence source reliability POC Implementation:
• ✅ AKEL searches for evidence (web/knowledge base)
• ✅ Mandatory contradiction search (finds opposing evidence)
• ✅ Source reliability scoring
• ❌ No evidence deduplication (added in POC2)
• ❌ No advanced source verification (added in POC2) Acceptance Criteria:
• Finds 2+ supporting evidence items
• Finds 1+ opposing evidence (if exists)
• Sources scored for reliability === 3.5 FR7: Automated Verdicts (Full Implementation) === Main Requirement: AI computes verdicts with uncertainty quantification POC Implementation:
• ✅ Probabilistic verdicts (0-100% confidence)
• ✅ Uncertainty explicitly stated
• ✅ Reasoning chain provided
• ✅ Quality Gate 4 validates verdict confidence POC Output:
  ```
  Verdict: 70% likely true
  Uncertainty: ±15% (moderate confidence)
  Reasoning: Based on 3 high-quality sources...
  Confidence Level: MEDIUM
  ``` Acceptance Criteria:
• Verdicts include probability (0-100%)
• Uncertainty explicitly quantified
• Reasoning chain explains verdict === 3.6 NFR11: Quality Assurance Framework (LITE VERSION) === Main Requirement: Complete quality assurance with 7 quality gates POC Implementation: 2 gates only Quality Gate 1: Claim Validation
• ✅ Validates claim is factual and verifiable
• ✅ Blocks non-factual claims (opinion/prediction/ambiguous)
• ✅ Provides clear rejection reason Quality Gate 4: Verdict Confidence Assessment
• ✅ Validates ≥2 sources found
• ✅ Validates quality score ≥0.6
• ✅ Blocks low-confidence verdicts
• ✅ Provides clear rejection reason Out of Scope (POC2+):
• ❌ Gate 2: Evidence Relevance
• ❌ Gate 3: Scenario Coherence
• ❌ Gate 5: Source Diversity
• ❌ Gate 6: Reasoning Validity
• ❌ Gate 7: Output Completeness Rationale: Prove gate concept works. Add remaining gates in POC2 after validating approach. === 3.7 NFR1-3: Performance, Scalability, Reliability (Basic) === Main Requirements:
• NFR1: Response time < 30 seconds
• NFR2: Handle 1000+ concurrent users
• NFR3: 99.9% uptime POC Implementation:
• ⚠️ Response time monitored (not optimized)
• ⚠️ Single-threaded processing (no concurrency)
• ⚠️ Basic error handling (no advanced retry logic) Rationale: POC proves functionality. Performance optimization happens in POC2. POC Acceptance:
• Analysis completes (no timeout requirement)
• Errors don't crash system
• Basic logging in place == 4. What's NOT in POC Scope == === 4.1 User-Facing Features (Beta 0+) === WarningDeferred to Beta 0: Out of Scope:
• ❌ User accounts and authentication (FR8)
• ❌ User corrections system (FR9, FR45-46)
• ❌ Public publishing interface (FR10)
• ❌ Social sharing (FR11)
• ❌ Email notifications (FR12)
• ❌ API access (FR13) Rationale: POC validates AI capabilities. User features added in Beta 0. === 4.2 Advanced Features (V1.0+) === Out of Scope:
• ❌ IFCN compliance (FR47)
• ❌ ClaimReview schema (FR48)
• ❌ Archive.org integration (FR49)
• ❌ OSINT toolkit (FR50)
• ❌ Video verification (FR51)
• ❌ Deepfake detection (FR52)
• ❌ Cross-org sharing (FR53) Rationale: Advanced features require proven platform. Added post-V1.0. === 4.3 Production Requirements (POC2, Beta 0) === Out of Scope:
• ❌ Security controls (NFR4, NFR12)
• ❌ Code maintainability (NFR5)
• ❌ System monitoring (NFR13)
• ❌ Evidence deduplication
• ❌ Advanced source verification
• ❌ Full 7-gate quality framework Rationale: POC proves concept. Production hardening happens in POC2 and Beta 0. == 5. POC Output Specification == === 5.1 Required Output Elements === For each analyzed claim, POC must produce: 1. Claim
• Original text
• Classification (factual/non-factual/ambiguous)
• If non-factual: Clear reason why 2. Scenarios (if factual)
• 2-3 interpretation scenarios
• Each scenario clearly described 3. Evidence (if factual)
• Supporting evidence (2+ items)
• Opposing evidence (if exists)
• Source URLs and reliability scores 4. Verdict (if factual)
• Probability (0-100%)
• Uncertainty quantification
• Confidence level (LOW/MEDIUM/HIGH)
• Reasoning chain 5. Quality Status
• Which gates passed/failed
• If failed: Clear explanation why === 5.2 Example POC Output === { "claim": { "text": "Switzerland has the highest life expectancy in Europe", "type": "factual", "gate1_status": "PASS" }, "scenarios": [ "Switzerland's overall life expectancy is highest", "Switzerland ranks highest for specific age groups" ], "evidence": { "supporting": [ { "source": "WHO Report 2023", "reliability": 0.95, "excerpt": "Switzerland: 83.4 years average..." } ], "opposing": [ { "source": "Eurostat 2024", "reliability": 0.90, "excerpt": "Spain leads at 83.5 years..." } ] }, "verdict": { "probability": 0.65, "uncertainty": 0.15, "confidence": "MEDIUM", "reasoning": "WHO and Eurostat show similar but conflicting data...", "gate4_status": "PASS" }
  } == 6. Success Criteria == SuccessPOC Success Definition: POC validates that AI can extract claims, find balanced evidence, and compute reasonable verdicts with quality gates improving output quality. === 6.1 Functional Success === POC is successful if: ✅ FR1-FR7 Requirements Met:

1. Extracts 3-5 factual claims from test articles
   2. Generates 2-3 scenarios per ambiguous claim
   3. Finds supporting AND opposing evidence
   4. Computes probabilistic verdicts with uncertainty
   5. Provides clear reasoning chains ✅ Quality Gates Work:
2. Gate 1 blocks non-factual claims (100% block rate)
   2. Gate 4 blocks low-quality verdicts (blocks if <2 sources or quality <0.6)
   3. Clear rejection reasons provided ✅ NFR11 Met:
3. Quality gates reduce hallucination rate
   2. Blocked outputs have clear explanations
   3. Quality metrics are logged === 6.2 Quality Thresholds === Minimum Acceptable:

• ≥70% of test claims correctly classified (factual/non-factual)
• ≥60% of verdicts are reasonable (human evaluation)
• Gate 1 blocks 100% of non-factual claims
• Gate 4 blocks verdicts with <2 sources Target:
• ≥80% claims correctly classified
• ≥75% verdicts are reasonable
• <10% false positives (blocking good claims) === 6.3 POC Decision Gate === After POC1, we decide: ✅ PROCEED to POC2 if:
• Success criteria met
• Quality gates demonstrably improve output
• Core workflow is technically sound
• Clear path to production quality ⚠️ ITERATE POC1 if:
• Success criteria partially met
• Gates work but need tuning
• Core issues identified but fixable ❌ PIVOT APPROACH if:
• Success criteria not met
• Fundamental AI limitations discovered
• Quality gates insufficient
• Alternative approach needed == 7. Test Cases == === 7.1 Happy Path === Test 1: Simple Factual Claim
• Input: "Paris is the capital of France"
• Expected: Factual, 1 scenario, verdict 95% true Test 2: Ambiguous Claim
• Input: "Switzerland has the highest income in Europe"
• Expected: Factual, 2-3 scenarios, verdict with uncertainty Test 3: Statistical Claim
• Input: "10% of people have condition X"
• Expected: Factual, evidence with numbers, probabilistic verdict === 7.2 Edge Cases === Test 4: Opinion
• Input: "Paris is the best city"
• Expected: Non-factual (opinion), blocked by Gate 1 Test 5: Prediction
• Input: "Bitcoin will reach $100,000 next year"
• Expected: Non-factual (prediction), blocked by Gate 1 Test 6: Insufficient Evidence
• Input: Obscure factual claim with no sources
• Expected: Blocked by Gate 4 (<2 sources) === 7.3 Quality Gate Tests === Test 7: Gate 1 Effectiveness
• Input: Mix of 10 factual + 10 non-factual claims
• Expected: Gate 1 blocks all 10 non-factual (100% precision) Test 8: Gate 4 Effectiveness
• Input: Claims with varying evidence availability
• Expected: Gate 4 blocks low-confidence verdicts == 8. Technical Architecture (POC) == === 8.1 Simplified Architecture === POC Tech Stack:
• Frontend: Simple web interface (Next.js + TypeScript)
• Backend: Single API endpoint
• AI: Claude API (Sonnet 4.5)
• Database: Local JSON files (no database)
• Deployment: Single server Architecture Diagram: See POC1 Specification === 8.2 AKEL Implementation === POC AKEL:
• Single-threaded processing
• Synchronous API calls
• No caching
• Basic error handling
• Console logging Full AKEL (POC2+):
• Multi-threaded processing
• Async API calls
• Evidence caching
• Advanced error handling with retry
• Structured logging + monitoring == 9. POC Philosophy == InformationImportant: POC validates concept, not production readiness. Focus is on proving AI can do the job, with production quality coming in later phases. === 9.1 Core Principles === 1. Prove Concept, Not Production
• POC validates AI can do the job
• Production quality comes in POC2 and Beta 0
• Focus on "does it work?" not "is it perfect?" 2. Implement Subset of Requirements
• POC covers FR1-7, NFR11 (lite)
• All other requirements deferred
• Clear mapping to Main Requirements 3. Quality Gates Validate Approach
• 2 gates prove the concept
• Remaining 5 gates added in POC2
• Gates must demonstrably improve quality 4. Iterate Based on Results
• POC results determine next steps
• Decision gate after POC1
• Flexibility to pivot if needed === 9.2 Success = Clear Path Forward === POC succeeds if we can confidently answer: ✅ Technical Feasibility:
• Can AI extract claims reliably?
• Can AI find balanced evidence?
• Can AI compute reasonable verdicts? ✅ Quality Approach:
• Do quality gates improve output?
• Can we measure and track quality?
• Is the gate approach scalable? ✅ Production Path:
• Is the core architecture sound?
• What needs improvement for production?
• Is POC2 the right next step? == 10. Related Pages == * Main Requirements - Full system requirements (this POC implements a subset)
• POC1 Specification (Detailed) - Detailed POC1 technical specs
• POC Summary - High-level POC overview
• Implementation Roadmap - POC1, POC2, Beta 0, V1.0 phases
• User Needs - What users need (drives requirements) Document Owner: Technical Team Review Frequency: After each POC iteration Version History:
• v1.0 - Initial POC requirements
• v2.0 - Updated after specification cross-check
• v3.0 - Aligned with Main Requirements (FR/NFR IDs added)