infospace-bench/infospaces/lefevre-reminiscences-of-a-stock-operator/workflows/templates/trading-literature/extract-relations.md

Extract Trading-Literature Relations

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Extract a small set of important relations from the source chunk. Return one Markdown relation artifact per relation. Each artifact uses sections ## Subject, ## Predicate, ## Object, and ## Relation Type. Add ## Evidence whenever the chunk supplies a concrete supporting phrase.

Use exactly one of these relation types per relation:

• cause_effect — one entity drives a measurable market or operator outcome (e.g. a strategy causing a loss; a market event causing a policy change)
• lesson_evidence — an evidence_bearing_claim is supported (or undercut) by a concrete trade, event, or quote in the source
• risk_mitigation — a strategy, rule, or habit reduces a named risk
• actor_venue — a trader operates in a market, institution, or pit
• strategy_outcome — a named strategy is applied to a specific trade or campaign and produces a labelled outcome (win, loss, scratch)

Subject and object values should match entity titles you would (or did) extract in the entities stage. Skip relations whose subject or object would be a one-off fictional flourish. Skip implicit moralising; prefer relations the chunk actually evidences.

Source title: {{ input.title }} Source artifact: {{ input.artifact_id }}

Source

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