NSCT Agent
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a60cf21a2c
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feat(stage6): source independence & citation graph — detect syndication, shared origins, text similarity
- SourceIndependenceModel: per-source independence_score (0.0-1.0), syndication_group_id, primary_source_id, content_hash, shared_urls
- CitationGraphEdgeModel: directed edges (SYNDICATED, QUOTES, LINKS_TO, REPOST, SIMILAR_CONTENT) with confidence + evidence
- Content-Hash (SHA-256): instant syndication detection for identical content
- difflib Vorfilterung: >60% → LLM, >80% → high confidence, 100% → immediate syndication
- LLM-Pairwise-Analysis: two-text-comparison for suspicious pairs only (bounded concurrency)
- independence_score: 1.0 base, -0.4 for syndicated, -0.1 per high-similarity pair
- Pydantic schemas: SourceIndependenceScore, CitationGraphEdge, SyntacticSimilarityResult, LlmSyndicationAnalysis, SourceIndependenceAnalysisResult
- LLM response parser: handles JSON, markdown code blocks, partial/invalid JSON
- 43 tests: content hash, similarity thresholds, LLM parsing, analyzer integration, edge cases, prompt templates
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2026-08-23 18:47:24 +00:00 |
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NSCT Agent
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e8b6515f67
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feat(stage5): implement claim extraction — atomic verifiable claims from sources
- Claim model with provenance, evidence_span, attribution, claim_type
- Stage5Extractor: LLM-based atomic claim extraction from source content
- Never summarizes — always extracts atomic, verifiable claims
- Claims require evidence span (exact quote from source)
- Attribution per claim (who says what)
- Claim types: fact, opinion, prediction, recommendation, claim
- Confidence score 0.0–1.0 per claim
- Bounded concurrency, SSRF-safe, max content truncation
- REST API: GET/POST /research/{run_id}/claims
- 36 tests: parsing, edge cases, integration, validation
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2026-08-23 17:56:01 +00:00 |
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