feat(infospace): add L3 relation graph with VSM-aware triplets (S2.8)
Implements the L3 relation graph layer — a directed graph of (Subject,
Predicate, Object) triplets annotated with VSM channel codes and feedback
roles. Triplets are authored as markdown files under output/relations/,
parsed into RelationMeta dataclasses, and analysed with networkx.
New modules:
- markitect/infospace/relation_models.py — RelationMeta dataclass +
RELATION_TYPES controlled vocabulary (15 relation classes → VSM codes)
- markitect/infospace/relation_parser.py — parse_relation_file() and
parse_relations_directory()
New schema: examples/infospace-with-history/schemas/relation-schema-v1.0.md
— file naming convention, required sections, controlled vocabulary table
15 seed relation files covering the three core WoN feedback loops:
- Capital Accumulation loop (positive reinforcement, S1/S3)
- Market Price Balancing loop (negative feedback, S2/S3)
- Market Extent mutual dependency (S1/S2)
Plus structural relations: wages regulation, rent residual, price
decomposition, invisible hand coordination
CLI: markitect infospace relations [--entity SLUG] [--vsm FILTER]
[--loops] [--stats]
- Builds directed graph from parsed files
- Detects feedback loops via nx.simple_cycles()
- 6 loops found from 15 seed relations (3 intended + 3 emergent)
- --stats aggregates by VSM system code (strips parentheticals)
Config: InfospaceConfig gains relations_dir (default output/relations)
infospace.yaml: schemas.relation references relation-schema-v1.0.md
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
tegwick
2d45425b25