Cluster
The definition as the field writes it comes first, weaknesses and all. What Entity Bind does about it comes last, in its own paragraph, so you can take one without the other. Filed under foundations.
What the problem is called, and what the objects in it are. Entity, record, cluster, and the four industry names for the same job.
every figure, with its population →What cluster means
A cluster is the group of records a resolver has decided are one company. Building those groups is a separate step from judging pairs, because pairwise decisions do not compose into groups on their own. If A matches B and B matches C, transitivity implies A matches C — but the scorer may never have compared A and C, and may have rejected them if it had. Clustering is the step that turns a set of pairwise verdicts into disjoint groups, usually with union–find, and it is where the errors of the pairwise stage compound.
Compounding is the reason cluster metrics exist. A resolver with excellent pairwise precision can still produce a badly wrong cluster, because one bad edge merges two otherwise clean families into one. A single false edge between two ten-record clusters produces a twenty-record cluster in which every record is now wrong about ten of its neighbours. This is why publishing pairwise precision alone is misleading, and why Entity Bind's accuracy rule forbids it.
Entity Bind's clustering carries a contradiction guard: conflicting strong identifiers block a transitive merge and flag it rather than letting the chain close. Two records carrying different registration numbers for the same register cannot be pulled into one cluster by a third record that merely resembles both.
Cluster quality is scored from each record's point of view — what share of the cluster it landed in genuinely belongs with it — which is B-cubed precision. On the live-adjudicated recording of 2026-08-29 that figure is 1.0000, and Cluster F1 0.9646 on the same 317-company representative recording of 2026-08-29. Pairwise numbers are never published without these.
Where this shows up in Entity Bind
Three pages where this term stops being vocabulary and starts changing an answer, a payload or a price.
- What is entity resolution?Entity resolution decides which records in one or more datasets refer to the same real-world entity, and joins them under a single stable identifier.Open
- The accuracy methodEvery published rate with the population it was measured over, its interval and its fixture — including the input shapes that fail.Open
- How it worksThe seven-stage cascade in order, what each stage can settle on its own, and what it hands to the next.Open
The fastest way past a definition is a file: which of your rows are the same company, which of your existing matches we would not have made, and what we could not decide.
Start freeThe terms next to this one
Each with its own sentence, because the next question is usually about the word beside this one.
B-cubed (B³)
B-cubed is a cluster-level evaluation metric that scores precision and recall from the point of view of each individual record, asking what share of its assigned cluster genuinely belongs with it and what share of its true family it was placed with.
Cluster metrics
Cluster metrics evaluate the groups a resolver produced rather than the pairs it judged, which is the only way to see errors that only appear once pairwise decisions are chained into entities.
Pairwise metrics
Pairwise metrics evaluate a resolver one candidate pair at a time — did it correctly decide that these two records are or are not the same entity — and they systematically flatter systems whose errors chain together.
Over-merge
An over-merge is a cluster containing records from more than one real entity — the failure that turns two customers, two suppliers or two counterparties into one.
Fragmentation
Fragmentation is the opposite failure to over-merging: one real entity split across several clusters, so the same company is counted, contracted with or invoiced more than once.
Entity
An entity is the real-world thing a set of records is asserted to describe — in Entity Bind, one company or organisation, holding a stable identifier that survives the records attaching to it.
- GuideSurvivorship and golden recordsMerging records is only half the job. Field-level survivorship, source precedence, temporal facts, per-field provenance, and why last-confirmed beats first-seen.
- GuideHow to measure entity resolution accuracyPrecision, recall, abstention, pairwise versus B-cubed cluster metrics, Wilson intervals and out-of-fold evaluation. Why a single accuracy number for entity resolution is always meaningless, with worked arithmetic.
The other 9 terms on this shelf
What the problem is called, and what the objects in it are. Entity, record, cluster, and the four industry names for the same job.
Internal fixtures only. The historical 2026-08-29 per-tier recording covers 317 GB companies with identifier-rich arrivals seeding the catalogue first; the context tier includes country and registered-town prose. Its legacy replay has no full-prompt-verified calls and cannot certify current calibration. The September 5 CI reports cover 1,176 labelled pairs and 705 records over 250 companies using offline stubs. These are not independent customer holdouts or live production validation; the 99% minimum-input product target remains unmet. Scope is company and organisation identity only — not people, vessels, bank-account ownership, sanctions or emissions. Results may not be used for eligibility decisions about individuals, including employment, credit and tenancy.
Start with your own company records.
Create your workspace, verify your email and run your first company file. The Free plan needs no card. Create API keys in your workspace when you need an integration.
300 credits. No card.
For a guided review of your file, explore the Merge Safety Sprint →