False-Friend Pair Examples Lookup

Independently verified cross-language senses for false-friend pair; cognacy/translation not inferred from spelling. Exact independently verified context/edition key, not live or embedded reference data. Caller establishes language, dialect, method and reference context; no automatic identity or universal language-wide claim.

Description

False friends are similar-looking expressions with potentially misleading meanings across languages.

False friends are similar-looking expressions with potentially misleading meanings across languages.1

A useful pair record specifies senses and contexts rather than promising universal non-equivalence. The tool retrieves your supplied source-specific notice for one exact key; it contains no built-in or live reference database.

When to use False-Friend Pair Examples Lookup

Use this tool to calculate or review the supplied observations under the stated rules. Specify the language variety, analysis, source edition and population or inventory definition.

How to use False-Friend Pair Examples Lookup and understand its results

  1. Specify the language variety, analysis, source edition and population or inventory definition.
  2. Enter callerVerifiedFalseFriendPairKeys, callerVerifiedFalseFriendPairNotices, queryFalseFriendPairKey, using the field meanings and rules below, then run the tool.
  3. Read matchedCallerNotice, using the output meanings and calculation rules below. Confirm that the exact matched record is the one whose source and context apply.
  4. Correct any reported input issue and run again. Before using a successful result, check the stated units, signs, reference scope and observation coverage.
Input fieldMeaningValue typeRequirement
callerVerifiedFalseFriendPairKeysCaller verified false friend pair keyslist of stringRequired
callerVerifiedFalseFriendPairNoticesCaller verified false friend pair noticeslist of stringRequired
queryFalseFriendPairKeyQuery false friend pair key; use the exact reference token or coordinate domain stated belowstringRequired

Supply nonempty aligned unique nonblank context keys and nonblank notices, then query one exact existing key. Matching is case-sensitive without trimming or normalization. Return its original notice unchanged; unknown keys fail. No data is fetched or independently verified.

notice=notices[indexOf(keys,exactQuery)]

Use the matching field units and the exact boundary, ordering and reference rules above.

Output fieldMeaningValue type
matchedCallerNoticeMatched caller noticestring
json
{
  "input": {
    "callerVerifiedFalseFriendPairKeys": [
      "context-a/edition-a",
      "context-a/edition-b"
    ],
    "callerVerifiedFalseFriendPairNotices": [
      "independent reference a",
      "independent reference b"
    ],
    "queryFalseFriendPairKey": "context-a/edition-b"
  },
  "output": {
    "matchedCallerNotice": "independent reference b"
  }
}

Limitations and assumptions

The language variety, analytical definitions and reference scope are supplied by the caller. No corpus, speech or complete/current linguistic registry is analyzed automatically. Reference records and their claimed verification are supplied by the caller; the tool does not retrieve or verify them.

Missing required fields, unknown fields, wrong types and violated rules return input issues. Numeric values and outputs must be finite. Lists and matrices must be dense, without missing cells. Numeric lists allow at most 10000 entries; ordinary string lists allow at most 128 strings of 128 UTF-16 units each; numeric matrices allow at most 128 rows and 128 columns, subject to narrower requirements above.

Alternative or Complementary methods

For a related step, use Cognate vs Loanword Classifier: Cognates and loans involve different historical relationships between forms. For a complementary comparison, use Calque Example Pair Lookup: A calque translates the components or structure of an expression rather than borrowing its entire form.

References

  1. False-Friend Pair Examples Lookup — tool.io

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