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d1f57272a4
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feat(example): add L2 classifications for 823/988 WoN entities (S3.4)
Batch classification via OpenRouter (claude-sonnet-4). 165 entities
remain unclassified due to credit exhaustion; incremental skip means
a follow-up run will complete them automatically.
Type × VSM matrix (823 entities):
S1 S2 S3 S3* S4 S5
Element 86 75 58 21 43 32 (315 total, 38%)
Process 39 42 37 17 67 24 (226 total, 28%)
Institution 4 12 30 24 . 52 (122 total, 15%)
Principle 3 7 15 2 43 32 (102 total, 12%)
Relation 2 14 5 5 22 10 (58 total, 7%)
Matrix fill: 29/30 cells (Institution/S4 empty — expected)
Metrics updated: type_entropy=2.0936, vsm_type_matrix_cells=29
Also:
- BatchEvaluator gains delay_seconds param for rate-limited providers
- classify CLI gains --rpm option (--rpm 10 for Gemini free tier)
- history.write_metrics_file now handles non-float metric values
(type_distribution is a dict, was crashing round())
- run_entity_classification forwards delay_seconds to BatchEvaluator
- classify-links and graph commands added by user (entities --by-type,
graph --format mermaid/dot, classify-links for Relation enrichment)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-02-23 12:49:11 +01:00 |
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81a4c8796a
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feat(infospace): add L2 entity classification with type × VSM matrix (S2.9)
Implements the L2 typed-entities layer — each entity is assigned an
Entity Type (Element, Process, Relation, Principle, Institution) and a
VSM System (S1–S5) by an LLM, with one-sentence rationales for each.
New modules:
- markitect/infospace/classification.py — EntityClassification dataclass
+ ENTITY_TYPES / VSM_SYSTEMS controlled vocabularies
- markitect/infospace/classification_io.py — write/read classification
files (YAML frontmatter + markdown body, mirrors evaluation_io)
- markitect/infospace/classifier.py — build_classification_prompt(),
parse_classification_response(), run_entity_classification(); batch
runner writes files incrementally (same resumable pattern as evaluate)
CLI: markitect infospace classify [--entity SLUG] [--provider P] [--model M]
- Incremental skip: checks output/classifications/ for existing files
- Defaults to openrouter provider; 2000 max_tokens (Gemini 2.5 Flash
uses ~787 thinking tokens, so 800 was too low)
CLI: markitect infospace classify-summary [--update-metrics]
- Entity type counts + VSM system counts with percentages
- 5 × 6 type × VSM matrix (spots structural blind spots at a glance)
- --update-metrics writes type_distribution, type_entropy,
vsm_type_matrix_cells to metrics.yaml
Config: InfospaceConfig gains classifications_dir (default output/classifications)
Schema: schemas/typed-entity-schema-v1.0.md — type/VSM vocabulary tables,
rationale format rules, validation rules, metrics enabled at L2
infospace.yaml: schemas.typed_entity references typed-entity-schema-v1.0.md
Seed classifications (3): division_of_labour (Process/S1),
natural_price_as_central_price (Principle/S2),
invisible_hand_mechanism (Principle/S4)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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2026-02-23 09:35:58 +01:00 |
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