feat(example): add per-entity LLM evaluations for 985 WoN entities (S3.3)

Batch evaluation of all 988 entities via OpenRouter. 984 succeeded on
first pass; 3 failed (network errors). eval-summary --update-metrics
written with per_entity_mean=3.9556.

Viability dashboard: 6/6 PASS
  redundancy_ratio   0.0061  (max 0.10)
  coverage_ratio     0.6190  (min 0.40)
  coherence_comps    0.0000  (max 3)
  consistency_cycles 0.0000  (max 0)
  granularity_entropy 2.6748 (min 1.0)
  per_entity_mean    3.9556  (min 3.5)

Dimension breakdown (mean across 985 entities):
  definition_precision  3.62
  source_grounding      4.36
  domain_placement      4.56
  vsm_relevance         3.31
  explanatory_value     3.94

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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---
entity_slug: bank_economic_efficiency_metrics
evaluator: null
evaluated_at: '2026-02-23T00:39:10.441212'
overall_score: 3.6
scores:
- name: definition_precision
value: 4.0
max_value: 5.0
rationale: The definition is quite precise, clearly specifying concrete metrics
(cost-income ratios, return on assets, capital adequacy ratios) rather than vague
concepts. It distinctly captures the idea of quantitative measures for banking
assessment, though it could be slightly more specific about what constitutes "efficiency"
versus other performance aspects.
- name: source_grounding
value: 2.0
max_value: 5.0
rationale: This entity appears to introduce modern banking terminology and metrics
that would not have existed in Smith's 18th-century context. While Smith discusses
banking operations and their effects, he would not have used contemporary financial
ratio analysis or formal efficiency metrics as described here.
- name: domain_placement
value: 4.0
max_value: 5.0
rationale: The "Accumulation" domain placement is appropriate since banking efficiency
directly relates to capital formation and the productive use of accumulated wealth.
Banking metrics fundamentally concern how well financial institutions facilitate
the accumulation and deployment of capital in the economy.
- name: vsm_relevance
value: 5.0
max_value: 5.0
rationale: This entity maps excellently to VSM System 3 (internal regulation/audit),
as these metrics are precisely the kind of performance monitoring and control
measures that S3 uses to ensure operational units meet standards. The metrics
also support S4 intelligence functions by providing data for strategic decision-making.
- name: explanatory_value
value: 3.0
max_value: 5.0
rationale: While the entity identifies important measurement tools, it primarily
names metrics rather than explaining underlying mechanisms of how banking efficiency
affects economic outcomes. It has moderate explanatory value for understanding
banking performance but doesn't illuminate deeper structural relationships in
Smith's economic framework.
---
# Evaluation: Bank Economic Efficiency Metrics
## definition_precision — 4.0 / 5.0
The definition is quite precise, clearly specifying concrete metrics (cost-income ratios, return on assets, capital adequacy ratios) rather than vague concepts. It distinctly captures the idea of quantitative measures for banking assessment, though it could be slightly more specific about what constitutes "efficiency" versus other performance aspects.
## source_grounding — 2.0 / 5.0
This entity appears to introduce modern banking terminology and metrics that would not have existed in Smith's 18th-century context. While Smith discusses banking operations and their effects, he would not have used contemporary financial ratio analysis or formal efficiency metrics as described here.
## domain_placement — 4.0 / 5.0
The "Accumulation" domain placement is appropriate since banking efficiency directly relates to capital formation and the productive use of accumulated wealth. Banking metrics fundamentally concern how well financial institutions facilitate the accumulation and deployment of capital in the economy.
## vsm_relevance — 5.0 / 5.0
This entity maps excellently to VSM System 3 (internal regulation/audit), as these metrics are precisely the kind of performance monitoring and control measures that S3 uses to ensure operational units meet standards. The metrics also support S4 intelligence functions by providing data for strategic decision-making.
## explanatory_value — 3.0 / 5.0
While the entity identifies important measurement tools, it primarily names metrics rather than explaining underlying mechanisms of how banking efficiency affects economic outcomes. It has moderate explanatory value for understanding banking performance but doesn't illuminate deeper structural relationships in Smith's economic framework.