Transcription Name Match

Compare a transcribed name with a reference using edit distance.

Description

Transcribed names can differ through insertions, deletions or substitutions.

Transcribed names can differ through insertions, deletions or substitutions. Edit distance measures character changes, while normalized similarity expresses their proportion.^[1]

Compare a transcribed name with a reference using edit distance.

When to use Transcription Name Match

Use this tool to compare a transcribed name with a reference using edit distance.

Prepare the text, recorded observations, aligned figures or editorial criteria requested. Confirm what each label, count, timestamp or supplied flag represents before interpreting the result.

How to use Transcription Name Match and understand its results

Prepare the text, recorded observations, aligned figures or editorial criteria requested. Confirm what each label, count, timestamp or supplied flag represents before interpreting the result.
Enter transcribedName, referenceName, maximumEditDistance using the field table and calculation rules, then run the tool.
Read editDistance, similarityPercent, withinTolerance. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
transcribedName	Transcribed name	string	Required
referenceName	Reference name	string	Required
maximumEditDistance	Maximum edit distance	integer; minimum: 0	Required

Trim and lowercase both nonblank names, then compare Unicode code points using Levenshtein distance. Enter a nonnegative integer maximum distance. Return distance, similarity and inclusive gate.

similarity%=100(1−distance/max(nameLengths)); acceptable=distance≤maximum

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
editDistance	Levenshtein edit distance	integer; minimum: 0
similarityPercent	Name similarity (%)	number; minimum: 0; maximum: 100
withinTolerance	Within supplied distance	boolean

json

{
  "input": {
    "transcribedName": "Jon Smyth",
    "referenceName": "John Smith",
    "maximumEditDistance": 2
  },
  "output": {
    "editDistance": 2,
    "similarityPercent": 80,
    "withinTolerance": true
  }
}

Limitations and assumptions

No transposition rule, accent removal, Unicode normalization or identity verification is supplied. Runtime grows with the product of name lengths; use short names.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Extremely large text inputs are rejected. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.

Alternative or Complementary methods

Use Fuzzy Name Match: Fuzzy-match two names with a caller-supplied similarity threshold. For a complementary task, use Back-Translation Similarity: Compare token sets in a source rendering and back-translation without claiming semantic equivalence.

References

Transcription Name Match — tool.io

Similar or alternative tools

Fuzzy Name Match
Fuzzy-match two names with a caller-supplied similarity threshold.
Back-Translation Similarity
Compare token sets in a source rendering and back-translation without claiming semantic equivalence.