Entity disambiguation
Updated 2026-09-15
Entity disambiguation is the work of making a brand distinguishable from similarly named entities so that AI answers describe the right thing. It matters most for short, generic or near-homonym brand names, where a model can blend two products into one description.
How to detect and fix it
Detection is direct: sample "what is <brand>" and "what does <brand> do" across engines and read the answers rather than counting mentions. Confusion shows up as attributes that belong to another product. The fix has three parts: an entity page that states plainly what the product is, who built it and what it does not do; consistent identifiers across the site and any external profiles; and category-level contrast — saying what the product is not, without naming a competitor.
Illustrative finding (example, not a customer measurement)
Across a "what is <brand>" prompt, two engines describe the brand as workforce-scheduling software. None of the sampled answers cite the brand's own site. The gap is not visibility — mention rate is high — it is identity, and the fix is an entity page plus consistent external profiles.
Common mistakes
- Naming the confusable competitor in the correction, which strengthens the association you are trying to break.
- Fixing the homepage only. Confusion is resolved across every page that repeats the entity, not one.
- Measuring disambiguation as a rate. It is read, not scored: the finding is what the answer says.
Frequently asked questions
- How long does disambiguation take to show up?
- Grounded answers can pick up a clear new entity page within weeks; memory answers lag by however long the model waits for retraining, which is why the grounded and ungrounded cases are read separately.
- Should the entity page mention the confusion explicitly?
- At category level, yes — stating what the product is not is a legitimate, quotable fact. Naming the other company is neither necessary nor wise.
