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Evaluation Label Separator Ambiguity

Flag supplied evaluation labels containing the exact nonempty separator before delimiter-based serialization.

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Description

Find supplied labels containing a chosen separator.

Model and prompt records distinguish token indices, offset units, reserved capacity, code scales and numeric representations. A common softmax shift is mathematically invariant but can alter rounded inputs. Literal brace doubling and citation tokens are format conventions rather than universal template or evidence validation.

Find supplied labels containing a chosen separator.

When to use this tool

Use Evaluation Label Separator Ambiguity when you already have labels, separator and need to find supplied labels containing a chosen separator.

How to use the tool and how it works

  1. Enter labels, separator. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read containsSeparatorIndices, ambiguous. Inspect ambiguous before interpreting the associated values.

Require separator nonempty; return indices with literal substring membership and an ambiguous flag when any exist.1

Input fieldMeaning and unitsAccepted input
labelsLabelsRequired. Array of text; maximum UTF-16 length 8192; maximum items 256.
separatorNonempty literal substring, not a regex or automatically escaped delimiter.Required. Text; minimum UTF-16 length 1; maximum UTF-16 length 8192.
Output fieldInterpretationReturned shape
containsSeparatorIndicesContains Separator IndicesRequired. Array of safe integer; maximum items 256.
ambiguousAmbiguousRequired. Boolean.
json
{
  "input": {
    "labels": [
      "cat",
      "red|blue"
    ],
    "separator": "|"
  },
  "output": {
    "containsSeparatorIndices": [
      1
    ],
    "ambiguous": true
  }
}

Limitations and assumptions

  • Multi-character separators are literal. This is one delimiter-collision check, not complete serialization, escaping, unique-label validation or evaluation correctness.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.

Alternative or Complementary methods

Use the complete tokenizer, template, model contract and evaluation method. Verify actual capacity, vocabulary and numerical behavior when supplied budgets, local masks or representation checks cannot establish correct model operation.

References

  1. Calculation and input contract: artificial-intelligence/evaluation-label-separator-ambiguity — tool.io

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