Entity Clarity Index™ is a proprietary Ivica Srncevic metric that measures how unambiguously a page communicates its primary, secondary, and contextual entities. It evaluates entity disambiguation, schema anchoring, lexical consistency, and co‑occurrence patterns to determine how reliably AI systems and search engines can identify what the page is about.
What the metric measures
1. Primary Entity Precision
How clearly the main entity is:
- introduced
- reinforced
- referenced consistently
- supported by schema
- connected to expected attributes
2. Secondary Entity Disambiguation
Does the page avoid:
- entity collisions
- ambiguous references
- overlapping meanings
- missing qualifiers
This is critical for AI retrieval.
3. Lexical & Semantic Consistency
Does the content maintain:
- consistent naming
- consistent attributes
- consistent relationships
- consistent terminology
This reduces semantic drift.
4. Schema Anchoring Strength
How well structured data reinforces:
- entity type
- entity attributes
- entity relationships
- entity roles
This is where most sites fail.
Scoring Model
| Component | Weight |
|---|---|
| Primary Entity Precision | 35% |
| Secondary Entity Disambiguation | 30% |
| Lexical & Semantic Consistency | 20% |
| Schema Anchoring Strength | 15% |
If you want to explore how this metric fits into the broader diagnostic system, you can also review my other proprietary frameworks, including the Semantic Coverage Index™, Query Intent Alignment Score™, Entity Clarity Index™, Entity Graph Stability Score™, Topical Authority Density™, and Schema Confidence Score™. These diagnostics work together inside the AI Visibility Inspector and the NovaX AI Visibility Intelligence engine to provide a complete semantic visibility assessment. For a broader strategic context, you can also explore my foundational frameworks, such as the SEO Maturity Model, Semantic Cluster Blueprint, Visibility Strategy System Design, AI Search Readiness Audit, International SEO GEO Optimization, and Indexation & Crawl Diagnostic.
