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How to re-check low-confidence labels with a stronger model with Classifier Dev

Use the smart tier so answers under 0.7 confidence get a second opinion.

Who it is forA data or ops person whose batch of labels includes some ambiguous items that a fast answer may get wrong.

The problemFast single-label answers are less reliable when the model is unsure, and it is hard to tell which ones to recheck by hand.

The outcomeUncertain single-label answers are replaced by a reasoning model's answer and marked escalated, while confident answers stay as they were.

What you need first

  • A terminal with curl or another HTTP client
  • npm, only if you want the classify CLI
  • The texts you want to label and a set of label names

Steps

  1. Read the tier notes in the docs with curl classifier.dev to confirm how the tier option is set on a request.
  2. Add the smart tier to the request for single-label classification. (inferred, check the README)
  3. Check each result for escalated: true to find the answers that were replaced.
  4. Compare the escalated answers against a small hand-checked sample before trusting the whole batch.

Prompt for your agent

Using the classifier-dev repo at classifier.dev, classify each item in <input file> with the smart tier for single-label work. Output a table of item, label, confidence and whether it was escalated. Verify that every escalated row has a label that was returned by the service.

Caveat. The README says smart re-asks single-label answers below 0.7 but does not show the parameter name, and multi-label requests ignore the tier, so verify the request format first.

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