V.01 · Visibility & Coverage

Map what AI systems anchor their answers on.

Named entities — people, organisations, places, dates, statistics — are the anchors AI systems use to connect content to queries. This tool identifies every entity in your content, shows where they appear, and visualises their prominence and density.

ToolV.01 · v1.5
Built forContent creators and SEO professionals
Time to use~ 2 minutes
OutputEntity map + prominence visualisation
GEO

Entity Prominence Map

See where your key entities appear across your document — and where they go missing.

What is an Entity Prominence Map?
An entity prominence map shows how consistently your key named entities — people, organisations, products, concepts — appear across the sections of your document. Entity salience is grounded in published NLP research: mention frequency, first-mention position, and distribution across document sections predict how dominant an entity is in a text (Dunietz & Gillick, EACL 2014; GUM-SAGE, ACL 2025). This tool computes a composite salience score from these three signals and maps each entity's coverage across paragraphs. User-specified terms are tracked directly. When fewer than five terms are provided, the tool supplements with the most frequently recurring multi-word phrases in the text.
How to use the entity prominence map

The heat map shows which paragraphs contain each of your tracked entities. A filled cell means the entity appears in that paragraph; an empty cell is a gap. The goal is not 100% coverage — not every paragraph needs to mention every entity — but the final third of your document should reinforce your key terms, not abandon them. That is where coverage gaps matter most.

The bar chart shows what percentage of paragraphs contain each entity. An entity appearing in under 30% of paragraphs is effectively a one-off mention regardless of how many times it appears in total — it is not distributed across the document.

If the auto-detected entities are not the terms you care about — for example, if your key phrases are lowercase or not capitalised mid-sentence — use the "Track specific entities" field to specify them directly.

Why this matters for AI & SEO
Entity salience — the degree to which a named entity dominates a document — is an established concept in NLP research and is used by information retrieval systems to assess topical focus. Content where key entities appear consistently across sections is more likely to be treated as authoritative on those entities than content that mentions them only once. This tool applies that principle to estimate entity prominence. The direct link between document-level prominence and AI citation frequency is a reasonable extrapolation from entity salience research, not a directly measured outcome.
Your entity prominence map will appear here after you click Analyse.
What the research shows

Why entity density matters for AI answer construction.

R.01

Entities are how AI systems identify what content is about

Named entities — researchers, organisations, studies, statistics, dates, and places — are the primary anchors AI systems use to match content to queries. High entity density gives AI more to anchor on, more to reference, and more to cite with specificity.

R.02

Entity prominence in the opening section matters

AI systems weight content earlier in a document more heavily. Entities that appear in the first 20% of a document carry more prominence signal than those appearing later. The map shows you where your entities are concentrated — front-loading entities is a structural strategy.

R.03

Researcher and study citations are high-value entities

Named researchers (Aggarwal et al., Zhang et al.) and specific studies are some of the highest-value entities for AI citation matching. Content that names the sources of its claims is more likely to be cited by AI when those sources are queried. Source attribution is both an evidence signal and an entity strategy.

R.04

Generic content is entity-sparse by definition

Content that makes general claims without naming sources, organisations, people, or specific studies tends to be entity-sparse. Entity-sparse content gives AI systems fewer anchor points — making it harder to retrieve, cite, and absorb. The map makes this visible.

Map your entity coverage.

See where your named entities are concentrated, which sections are entity-sparse, and how your overall entity density compares to content optimised for AI citation.