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tegwick 574bb11db6 feat(example): add supply-chain-vsm composition demo (S3.5)

Demonstrates infospace composition: the Wealth of Nations infospace is
used as a discipline, applying Smith's economic framework as a lens to
analyse modern supply chain management concepts.

New example: examples/supply-chain-vsm/
- infospace.yaml binding WoN as discipline (../infospace-with-history)
- 3 source documents: coordination mechanisms, capital & inventory,
  market structure (~400 words each, original content)
- supply-chain-entity-schema-v1.0.md with WoN Concept required section
- won-mapping-schema-v1.0.md with Conceptual Continuity rating
- artifacts/won-reference/core-entities.md — 12 curated WoN entities
  for injection as discipline context
- 8 hand-crafted entity files demonstrating LLM output format
- 3 mapping files with full rationale and VSM inheritance chains
- Viable: YES (5/5 thresholds)

Key mappings demonstrated:
  Demand Signal          → Effectual Demand        (Strong, S2)
  Vendor-Managed Inventory → Division of Labour    (Strong, S1/S2)
  Just-in-Time Inventory → Circulating Capital     (Strong, S1/S3)
  Bullwhip Effect        → Natural Price           (Moderate, S2)
  Platform Intermediary  → Merchant Capital        (Strong, S2/S4)
  Monopsony Power        → Combination of Masters  (Strong, S3*)

Platform fix: entity_parser.py now recognises ## Supply Chain Domain
as a domain alias for ## Economic Domain, enabling composed infospaces
to use their own domain section name.

Tutorial §13 rewritten with real commands, real output, and the full
mapping table from the demo.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

2026-02-23 00:08:51 +01:00

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Extract Supply Chain Entities

You are a supply chain analyst with expertise in both modern operations management and classical political economy. Your task is to extract distinct supply chain entities from a source document.

Source Document

@{chapter_text}

Extraction Guidelines

@{extraction_rules}

Wealth of Nations Reference Entities

The following WoN entities are available as mapping targets. For each entity you extract, identify the most relevant WoN concept from this set.

@{won_core_entities}

Existing Entities

The following entities have already been extracted from previous sources. Do not re-extract concepts already captured — only extract genuinely new entities introduced by this source.

@{existing_entities}

Output Format

Output each entity using the following delimiter format:

--- ENTITY: Entity Name ---

# Entity Name

## Definition

[20–150 word definition]

## Source

[Source document name, section if applicable]

## Supply Chain Domain

[Coordination | Capital Management | Market Structure | Risk | Logistics]

## VSM Assignment

[S1–S5] — [one-sentence rationale]

## WoN Concept

[WoN entity name] — [one-sentence explanation of the connection]

---

Extract 4–8 entities. Prefer precision over volume.

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