Wrote sourced_from: into 414 claim files pointing back to their origin source. Backfilled claims_extracted: into 252 source files that were processed but missing this field. Matching uses author+title overlap against claim source: field, validated against 296 known-good pairs from existing claims_extracted. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
34 lines
1 KiB
Markdown
34 lines
1 KiB
Markdown
---
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type: source
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source_type: telegram
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title: "Telegram: @m3taversal — can-you-save-a-learning-for-this"
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author: "@m3taversal"
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url: ""
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date: 2026-03-25
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domain: internet-finance
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format: conversation
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status: processed
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priority: high
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intake_tier: directed
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rationale: "Can you save a learning for this?"
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proposed_by: "@m3taversal"
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tags: [telegram, ownership-community]
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claims_extracted:
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- "permissioned-launch-curation-creates-implicit-endorsement-liability-for-futarchy-platforms"
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---
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## Conversation
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**@m3taversal:**
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Can you save a learning for this?
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**Rio (response):**
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Saved.
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LEARNING: communication When users ask for a token price, check live market data tools first before saying you don't have it. The $ prefix or token name should both trigger a lookup attempt.
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## Agent Notes
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**Why archived:** Tagged exchange in ownership community.
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**Rationale from contributor:** Can you save a learning for this?
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**Intake tier:** directed — fast-tracked, contributor provided reasoning
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**Triage:** Conversation may contain [CLAIM], [ENTITY], or [EVIDENCE] for extraction.
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