# Extract Trading-Literature Relations

Profile: {{ macros.profile }}

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

{{ input.content }}