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Last modified by Robert Schaub on 2025/12/24 09:59
From version 2.1
edited by Robert Schaub
on 2025/12/23 22:20
Change comment: Imported from XAR
To version 1.1
edited by Robert Schaub
on 2025/12/23 18:19
Change comment: Imported from XAR

Summary

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15 15  
16 16  * AKEL can reliably extract factual claims from articles
17 17  * AKEL can generate credible verdicts with proper evidence
18 -* **AKEL can assess article credibility beyond simple claim averaging** (context-aware analysis)
19 19  * Quality gates prevent hallucinations and low-confidence outputs
20 20  * Fully automated approach is viable
21 21  
... ... @@ -41,31 +41,6 @@
41 41  * A/B testing
42 42  * Gates 2 & 3 (Evidence relevance, Scenario coherence)
43 43  
44 -
45 -=== Experimental Features (POC1) ===
46 -
47 -**Context-Aware Analysis** (Approach 1: Single-Pass Holistic)
48 -
49 -**Goal:** Test if AI can detect when an article's overall credibility differs from the average of its claim verdicts (e.g., accurate facts but misleading conclusion).
50 -
51 -**Implementation:**
52 -* Enhanced AI prompt to evaluate logical structure
53 -* AI identifies article's main argument
54 -* AI assesses if conclusion follows from evidence
55 -* Article verdict may differ from claim average
56 -
57 -**Testing:**
58 -* 30-article test set (10 straightforward, 10 misleading, 10 complex)
59 -* Success criteria: ≥70% accuracy on misleading articles
60 -* Marked as experimental - doesn't block POC1 success
61 -
62 -**See:** [[Article Verdict Problem>>Test.FactHarbor.Specification.POC.Article-Verdict-Problem]] for complete analysis
63 -
64 -**Decision:**
65 -* If ≥70% accuracy → ship in POC2
66 -* If 50-70% → try weighted aggregation approach
67 -* If <50% → defer to POC2 with different approach
68 -
69 69  == 3. Requirements ==
70 70  
71 71  === 3.1 NFR11: Quality Assurance Framework (POC1 Lite Version) ===