Random Fictional Language Contact Map Generator

Description

Assign supplied invented languages to regions with minimum coverage quotas, then label caller contact edges; constructed nonuniform allocation, not real sociolinguistic inference.

Worldbuilding fixtures describe an invented setting through supplied entities and explicit relations. A reproducible arrangement can support games or writing exercises while keeping constructed history and geography separate from factual claims about the real world.

Assign supplied invented languages to regions with minimum coverage quotas, then label caller contact edges; constructed nonuniform allocation, not real sociolinguistic inference.

When to use this tool

Use this generator to create reproducible fictional language contact map cases from the supplied model or bank. Inspect the returned evidence before using cases in a test or exercise.

How to use the tool and how it works

Supply regionIds, languageIds, contacts, minimumRegionsPerLanguage in the field shapes below. Set seed when you need an explicit replay.
Run the tool and correct any input error. For generated controls, distinguish a successful fixture containing an invalid case from failure to generate the fixture.
Read regions, contacts, languageCounts, componentCount, fictional. Use the conventions below. Keep answer-bearing fields separate when presenting an exercise.

Reserve the requested minimum number of regions per language, randomly fill remaining assignments, shuffle them across regions, and annotate supplied contact links with whether their endpoint languages match.^[1]

Input field	Meaning and units	Accepted input
regionIds	Region Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
languageIds	Language Ids	Required. Array of Text; minimum UTF-16 length 1; maximum UTF-16 length 64.; minimum items 1; maximum items 16.
contacts	Contacts	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 64.
contacts[].from	From	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
contacts[].to	To	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
minimumRegionsPerLanguage	Minimum Regions Per Language	Required. Safe integer; minimum 0; maximum 16.
seed	Optional numeric seed; takes precedence over context randomness. Without either, use the fixed tool.io default seed.	Optional. Safe integer.

Output field	Interpretation	Returned shape
regions	Regions	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
regions[].id	Literal identifier used independently of display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
regions[].languageId	Language Id	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
contacts	Contacts	Required. Array of Object; no unknown keys.; minimum items 0; maximum items 64.
contacts[].from	From	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
contacts[].to	To	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
contacts[].sameLanguage	Same Language	Required. Boolean.
languageCounts	Language Counts	Required. Array of Object; no unknown keys.; minimum items 1; maximum items 16.
languageCounts[].id	Literal identifier used independently of display labels.	Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 64.
languageCounts[].count	Count	Required. Safe integer; minimum 0; maximum 16.
componentCount	Component Count	Required. Safe integer; minimum 1; maximum 16.
fictional	Fictional	Required. Boolean; exactly true.
randomness	Replay source and normalized 32-bit seed, or null seed for an advancing context source.	Required. Object; no unknown keys.
randomness.seed	Optional safe-integer replay seed; normalization and precedence are explained below.	Required. Safe integer. or Null.
randomness.source	Source	Required. Text; one of "context", "seed".

An explicit safe-integer seed takes precedence over injected context randomness and is normalized to an unsigned 32-bit integer. With no seed and no context source, replay uses the fixed tool.io default seed. A context source must return finite values from zero inclusive to one exclusive; its advancing state must be retained separately. randomness records the source and normalized seed, or null for context. These generators are not cryptographic random sources.

json

{
  "input": {
    "regionIds": [
      "a",
      "b",
      "c"
    ],
    "languageIds": [
      "cairn",
      "tidal"
    ],
    "contacts": [
      {
        "from": "a",
        "to": "b"
      },
      {
        "from": "b",
        "to": "c"
      }
    ],
    "minimumRegionsPerLanguage": 1,
    "seed": 42
  },
  "output": {
    "regions": [
      {
        "id": "a",
        "languageId": "cairn"
      },
      {
        "id": "b",
        "languageId": "tidal"
      },
      {
        "id": "c",
        "languageId": "tidal"
      }
    ],
    "contacts": [
      {
        "from": "a",
        "to": "b",
        "sameLanguage": false
      },
      {
        "from": "b",
        "to": "c",
        "sameLanguage": true
      }
    ],
    "languageCounts": [
      {
        "id": "cairn",
        "count": 1
      },
      {
        "id": "tidal",
        "count": 2
      }
    ],
    "componentCount": 1,
    "fictional": true,
    "randomness": {
      "seed": 42,
      "source": "seed"
    }
  }
}

Limitations and assumptions

Every region gets one language label and the minimum quotas must fit. This is fictional labeling rather than multilingual population, linguistic similarity, historical contact, or language inference.
A replay requires the same complete input and implementation. The stated sampling convention applies within its eligible space. A finite draw does not exhaust all possible outputs; repeats remain possible unless a distinct-selection rule is explicit.
The field tables state structural bounds; cross-field constraints and bounded search or output budgets also apply. Unknown keys are rejected where the object contract disallows them. Input errors are distinct from null fields and deliberate invalid controls in a successful output.

Alternative or Complementary methods

For a supplied example, inspect the returned construction or delegated check directly. To evaluate a consumer, also test cases chosen for its own boundaries; a generated finite corpus does not establish exhaustive coverage.

References

Tool behavior and example: Random Fictional Language Contact Map Generator — tool.io

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