Normalisation
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 matching methods.
How two records are compared and how the comparison is made cheap enough to run. Blocking, deterministic rules, probabilistic scoring, string distance.
every figure, with its population →What normalisation means
Normalisation is the rewriting step that puts two records into the same form so they can be compared at all. It lower-cases, strips or standardises punctuation, expands or removes legal form suffixes, collapses whitespace, folds accents, canonicalises ampersands and the word 'and', handles the article at the front of a name, and rewrites identifiers into the shape their register actually uses.
It is unglamorous and it dominates the results. A pipeline with an excellent scorer and naive normalisation will miss 'The Acme Group Ltd.' against 'Acme Group Limited'; a pipeline with careful normalisation and a mediocre scorer will catch it. The same asymmetry runs through identifiers: a Companies House number is eight characters behind an optional letter prefix, and knowing that is what stops a stripped six-digit number colliding with a charity reference.
Normalisation is also where over-eagerness becomes dangerous. Stripping every legal form makes two genuinely different companies with the same stem look identical, and folding numbers to words makes 'Group 4' and 'Group Four' one thing when the register says they are two. The right instinct is to normalise for retrieval and keep the raw value for scoring, so that a difference which was deliberately ignored to find a candidate can still count as evidence when the candidate is judged.
Normalisation is the first stage of Entity Bind's cascade, covering legal forms, punctuation, transliteration and register-specific number shapes, and the raw submitted value is retained beside the normalised one.
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.
- 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 accuracy methodEvery published rate with the population it was measured over, its interval and its fixture — including the input shapes that fail.Open
- Register coverageThe registers the resolver reads, the licence each one publishes under, and how often a live entity's name is unique once it is tidied to a common form.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.
Transliteration
Transliteration maps text from one writing system into another — Cyrillic or Greek or Han into Latin script — so that names recorded in different alphabets can be compared at all.
Blocking
Blocking is the technique that makes entity resolution affordable by comparing each record only against a small set of plausible candidates instead of against every other record.
Fuzzy matching
Fuzzy matching compares strings by similarity rather than equality, returning a score between zero and one — a useful retrieval signal and, on its own, not a calibrated basis for a merge.
Edit distance
Edit distance counts the minimum number of single-character insertions, deletions or substitutions needed to turn one string into another; Levenshtein distance is the standard form.
Company number
A company number is the identifier a register assigns to a company at incorporation, and it is unique only within the register that issued it — never within a country and never globally.
Candidate generation
Candidate generation is the retrieval step that proposes the small set of entities a record might be, and its recall is the hard ceiling on everything the rest of the pipeline can achieve.
- GuideBlocking and candidate generationYou cannot compare every pair. How blocking keys work, why rarity weighting matters, how to measure retrieval with recall@k, and the silent failure mode that mints duplicates.
- JurisdictionFranceSIRENE under Licence Ouverte 2.0, storable and resellable, and the only register that links a site to the legal entity running it. Bare names meet a ceiling.
The other 12 terms on this shelf
How two records are compared and how the comparison is made cheap enough to run. Blocking, deterministic rules, probabilistic scoring, string distance.
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.
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