--- title: "Precision" summary: "Precision is the share of the matches a system asserted that were correct — and it is meaningless without the share of records the system was willing to decide at all." canonical_url: https://entitybind.com/glossary/precision last_updated: 2026-10-15 copy: full --- # Precision > Precision is the share of the matches a system asserted that were correct — and it is meaningless without the share of records the system was willing to decide at all. Canonical page: https://entitybind.com/glossary/precision Last updated: 2026-10-15 Glossary · Measurement ## How to read this 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 measurement](https://entitybind.com/glossary#measurement). By [James Rooney](https://entitybind.com/about), founder of Entity Bind · Last revised 15 October 2026 ## What precision means Precision is true positives divided by all positives asserted. If a resolver proposes a hundred merges and ninety-seven are right, precision is 0.97. It is the metric a merge-safety buyer cares about most, because the three wrong merges are the ones that corrupt a customer master. It is also the easiest metric in the field to game, and the gaming needs no dishonesty: a system that decides almost nothing and abstains on everything else can report perfect precision forever. This is why precision may never be published without the automation rate beside it — the share of pairs the system actually decided — and why a vendor quoting one without the other is quoting half of a ratio. The second requirement is an interval. Precision measured on a few hundred pairs has a wide confidence interval, and the point estimate of 1.0 on a small sample is compatible with a true rate well below it. The lower bound is the number that means something. Entity Bind's continuous-integration gate of 2026-09-05 measured automated merge precision of 1.0000 (357/357) at an automation rate of 63.10%. 742 of 1,176 pairs were decided automatically in the September 5 saved gate report. This measures automation, separately from accepted-merge precision. The published figure is the worst rate those observations are still consistent with at 95% — the Wilson lower bound — rather than the point estimate: 98.94%. The 95% Wilson lower bound of 357 error-free automated merges. Proving a 99% lower bound needs at least 381 consecutive clean merges, so this is 24 short of it — and we publish the bound rather than the point estimate. ## 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. - [Precision, recall and abstention](https://entitybind.com/guides/precision-recall-and-abstention): The precision-recall trade-off is usually described as a two-way choice, and in entity resolution that description is wrong. There is a third output — declining… - [The accuracy method](https://entitybind.com/accuracy): Every published rate with the population it was measured over, its interval and its fixture — including the input shapes that fail. - [The audit pack](https://entitybind.com/audit-pack): The fixtures, the verdict logs and the replay path: what an evaluator needs to re-run a published rate for themselves. 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 free →](https://app.entitybind.com/app?signup=1) ## The terms next to this one Each with its own sentence, because the next question is usually about the word beside this one. - [Recall](https://entitybind.com/glossary/recall): Recall is the share of the true matches present in the data that a system actually found, and it is the metric that abstention costs you. - [F1 score](https://entitybind.com/glossary/f1): F1 is the harmonic mean of precision and recall, reported as a single number that is only interpretable once you know which of its two components is doing the work. - [Wilson interval](https://entitybind.com/glossary/wilson-interval): The Wilson score interval is a confidence interval for a proportion that stays sensible at the extremes, which is why it is the right interval to publish when a system has made no observed errors at all. - [False positive](https://entitybind.com/glossary/false-positive): A false positive in entity resolution is a pair of records asserted to be the same entity when they are not — the error class that corrupts data rather than merely leaving it untidy. - [Pairwise metrics](https://entitybind.com/glossary/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. - [Abstention](https://entitybind.com/glossary/abstention): An abstention is a first-class 'we do not know' returned instead of a match: the record comes back unresolved, with a ranked shortlist, a typed reason and the column that would have decided it. ### Answered at length elsewhere - [How to measure entity resolution accuracy](https://entitybind.com/guides/how-to-measure-entity-resolution-accuracy) (Guide): Precision, 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 13 terms on this shelf How you tell whether any of it worked, and which numbers may not be quoted without which other numbers. - [Recall](https://entitybind.com/glossary/recall) - [F1 score](https://entitybind.com/glossary/f1) - [B-cubed (B³)](https://entitybind.com/glossary/b-cubed) - [Pairwise metrics](https://entitybind.com/glossary/pairwise-metrics) - [Cluster metrics](https://entitybind.com/glossary/cluster-metrics) - [Recall@k](https://entitybind.com/glossary/recall-at-k) - [Calibration](https://entitybind.com/glossary/calibration) - [Expected calibration error (ECE)](https://entitybind.com/glossary/expected-calibration-error) - [Wilson interval](https://entitybind.com/glossary/wilson-interval) - [False positive](https://entitybind.com/glossary/false-positive) - [False bind](https://entitybind.com/glossary/false-bind) - [Over-merge](https://entitybind.com/glossary/over-merge) - [Fragmentation](https://entitybind.com/glossary/fragmentation) Previous, alphabetically: [Pass-through data](https://entitybind.com/glossary/pass-through-data) · Next, alphabetically: [Probabilistic matching](https://entitybind.com/glossary/probabilistic-matching) ## Evidence basis 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. [Start free](https://app.entitybind.com/app?signup=1) · [All 64 terms](https://entitybind.com/glossary) 300 credits. No card. For a guided review of your file, explore [the Merge Safety Sprint](https://entitybind.com/audit-pack). --- Entity Bind resolves companies and organisations only. It does not resolve people, vessels, bank-account ownership, sanctions exposure, emissions or geolocation, and its results may not be used for eligibility decisions about individuals, including employment, credit and tenancy. This is the Markdown copy of https://entitybind.com/glossary/precision, assembled from the same data the page renders and carrying every sentence, table row, figure and question the page's main content carries. The HTML page is canonical; it adds the layout, the navigation and the interactive parts (the ask panel, the forms), which a copy can name but not run. Every page on the site, with a line on each: https://entitybind.com/llms.txt.