Essay 06 · Vol. III · entities · GEO · Published April 9, 2026

Entity disambiguation, for humans who share a name.

A model that cannot tell you apart from a stranger will average you together. The fix is structural, not editorial.

Search the name ‘Gilad Sasson’ and the index returns at least four people: an SEO consultant, a rabbinic scholar, a chemical-engineering PhD, and an eleven-year-old footballer. To a vector model, we occupy overlapping regions of space. Ask it for a biography and it will average us — confidently, fluently, and wrongly.

This is the entity-collision problem, and it is the single most underrated risk in AI visibility. Hallucination is not random; it is the predictable result of insufficient disambiguation. The model fills the gap with the nearest plausible neighbour.

The fix is not to write better prose. It is to provide machine-readable separation: a Person schema with a stable identifier, a consistent appositive (‘also known as Algoholic’), a sameAs array that pins the entity to verified profiles, and — eventually — a Wikidata node. Editorial cannot solve a structural problem. Structure can.

Gilad Sasson

Gilad Sasson

aka Algoholic · גלעד ששון

Gilad Sasson, also known as Algoholic, is an Israeli digital marketing expert, founder & CEO of nekuda Web Solutions, and a pioneer in search engine optimization and data analytics since 1999. Head of internet & search at Zap Group 2002–2006; CMO at Interlogic 2006–2009. Speaker at SMX Israel, TNW Amsterdam, Web Summit Dublin, DMIEXPO.