Taxonomy Distribution Report

Overview

• Total Concepts: 130
• Number of Taxonomies: 9
• Average Concepts per Taxonomy: 14.4

Distribution Summary

Category	TaxonomyID	Count	Percentage	Status
DIM	DIM	26	20.0%	✅
ACCUM	ACCUM	22	16.9%	✅
EXPR	EXPR	20	15.4%	✅
LATT	LATT	14	10.8%	✅
RESULT	RESULT	13	10.0%	✅
Foundation Concepts - Prerequisites	FOUND	10	7.7%	✅
POLICY	POLICY	10	7.7%	✅
BATCH	BATCH	8	6.2%	✅
SUPP	SUPP	7	5.4%	✅

Visual Distribution

DIM                       ██████████  26 ( 20.0%)
ACCUM                     ████████  22 ( 16.9%)
EXPR                      ███████  20 ( 15.4%)
LATT                      █████  14 ( 10.8%)
RESULT                    █████  13 ( 10.0%)
Foundation Concepts - Pre ███  10 (  7.7%)
POLICY                    ███  10 (  7.7%)
BATCH                     ███   8 (  6.2%)
SUPP                      ██   7 (  5.4%)

Balance Analysis

✅ No Over-Represented Categories

All categories are under the 30% threshold. Good balance!

Category Details

DIM (DIM)

Count: 26 concepts (20.0%)

Concepts:

• 1. MatchStrategy Enum
• 1. EXACT Strategy
• 1. NOT_EQUAL Strategy
• 1. RANGE Strategy
• 1. GREATER_THAN Strategy
• 1. LESS_THAN Strategy
• 1. PREFIX Strategy
• 1. SUFFIX Strategy
• 1. CONTAINS Strategy
• 1. REGEX Strategy
• 1. SET_MEMBERSHIP Strategy
• 1. SET_EXCLUSION Strategy
• 1. DimensionRole Enum
• 1. CONSTRAINT Role
• 1. CONTEXT_KEY Role
• ...and 11 more

ACCUM (ACCUM)

Count: 22 concepts (16.9%)

Concepts:

• 1. AccumulatorCompiler
• 1. Compatible Expression
• 1. Coalesce Expression
• 1. Coalesce NA Flag
• 1. Compatible Exact
• 1. Compatible Range
• 1. Coalesce Exact
• 1. Coalesce Range
• 1. Coalesce Threshold
• 1. AccumulatorEngine
• 1. Prime Number Encoding
• 1. Prime Table Sieve
• 1. Get Prime Function
• 1. Checked Multiply
• 1. Anchor Creation
• ...and 7 more

EXPR (EXPR)

Count: 20 concepts (15.4%)

Concepts:

• 1. DimensionCompiler
• 1. Compile Exact Expression
• 1. Compile Range Expression
• 1. Compile String Match
• 1. Compile Regex Expression
• 1. Compile Set Expression
• 1. Compile Threshold Expression
• 1. Sentinel-Aware Ternary
• 1. Context Value Extraction
• 1. ExpressionRulesEngine
• 1. Engine Construction
• 1. Convenience vs Advanced Path
• 1. Single-Pass Evaluation
• 1. Context Binding Phase
• 1. Dimension Expression Phase
• ...and 5 more

LATT (LATT)

Count: 14 concepts (10.8%)

Concepts:

• 1. Lattice Class
• 1. Lattice Combinations
• 1. Lattice Partition Key
• 1. Coalesced Columns
• 1. NA Flag Columns
• 1. Combination Depth
• 1. AccumulatorResult Class
• 1. Accumulated Aggregates
• 1. Provenance Accessor
• 1. Depths Accessor
• 1. Lattice Save Method
• 1. Lattice Load Method
• 1. Lattice Is Composed
• 1. Aggregate Min Max Product

RESULT (RESULT)

Count: 13 concepts (10.0%)

Concepts:

• 1. RuleResult Class
• 1. Survivors Accessor
• 1. Best Match Accessor
• 1. Count Accessor
• 1. Active Dimensions
• 1. RuleResult Explain Method
• 1. At Least Filter
• 1. Top N Filtering
• 1. Min Specificity Filter
• 1. Observability Columns
• 1. ExplainResult Class
• 1. Engine-Level Explain
• 1. RuleResult Select Method

Foundation Concepts - Prerequisites (FOUND)

Count: 10 concepts (7.7%)

Concepts:

• 1. Ternary Logic
• 1. Sentinel Values
• 1. Match Strategy Patterns
• 1. Pydantic Model Validation
• 1. Vectorized Evaluation
• 1. Backend-Agnostic Design
• 1. DataFrame as Rule Store
• 1. Mountainash Expressions
• 1. Mountainash Relations
• 1. Context Object

POLICY (POLICY)

Count: 10 concepts (7.7%)

Concepts:

• 1. Table-Level Hit Policy Fields
• 1. HitPolicy Enum
• 1. Collect Policy
• 1. Unique Policy
• 1. First And Priority Policy
• 1. Any Policy
• 1. Rule Order Policy
• 1. SelectionInfo Dataclass
• 1. HitPolicyViolationError
• 1. Cardinality Application

BATCH (BATCH)

Count: 8 concepts (6.2%)

Concepts:

• 1. BatchRuleResult Class
• 1. Evaluate Batch Method
• 1. Batch Context Preparation
• 1. Cross-Join Evaluation
• 1. Per-Context Ranking
• 1. Backend Conforming
• 1. Chunked Batch Evaluation
• 1. For Context Accessor

SUPP (SUPP)

Count: 7 concepts (5.4%)

Concepts:

• 1. Aggregate Model
• 1. Partition Key Filtering
• 1. Build All Partitions
• 1. Apply Auto Selection
• 1. LatticeIndex Router
• 1. AmbiguousPartitionError
• 1. EXACT_KEY Partition Routing

Recommendations

• ✅ Excellent balance: Categories are evenly distributed (spread: 14.6%)
• ✅ MISC category minimal: Good categorization specificity

Educational Use Recommendations

• Use taxonomy categories for color-coding in graph visualizations
• Design curriculum modules based on taxonomy groupings
• Create filtered views for focused learning paths
• Use categories for assessment organization
• Enable navigation by topic area in interactive tools

---

Report generated by learning-graph-reports/taxonomy_distribution.py