Three fixes for conversation-sourced claim quality:
1. Trust hierarchy in extraction prompt: bot-generated numbers are
flagged as unverified context, not evidence. Directional claims
are extractable but specific figures require external verification.
Prevents laundering bot guesses into the KB as evidence.
2. Conversation-sourced claims tagged with verified: false and
source_type: conversation in frontmatter. Downstream consumers
(Leo, dashboard) can filter/flag these for verification.
3. GET /api/telegram-extractions endpoint for daily spot-checking.
Shows recent Telegram-sourced PRs with claim titles, status,
merge rate, and eval issues. Quick review surface.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Two changes:
1. extract.py: Enrichments now modify existing claim files by appending
evidence sections. Previously enrichment-only extractions were
discarded as null-result even when they contained valuable challenges.
2. extraction_prompt.py: Corrections should produce BOTH a claim (the
corrected knowledge) AND an enrichment (linking to what it corrects).
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
When source format is "conversation", inject specialized extraction
rules that prioritize human corrections/pushback as highest-value
content. Fixes null-result on short but high-signal correction
messages. Maps corrections to existing KB claims as challenges.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
