kelvinmade✳Independent maker ↗
JEV USE CASE

Citation Verification.

Compare a claim, its cited passage and source context to classify whether the citation supports the claim.

THE DECISION CONTRACT
STATE

Claim: refunds rose 18%. Source: refunds rose from 10% to 11.8%.

QUESTION

What is the relationship between the source and claim?

CHOICES

supports partially_supports contradicts insufficient

TYPESCRIPT EXAMPLE

Ask for one bounded answer

This Vercel AI SDK-shaped example is illustrative. Check the current provider documentation before shipping.

import { experimental_evaluate as evaluate } from 'ai';

const result = await evaluate({
  model: 'typesafe-ai/jev',
  state: "Claim: refunds rose 18%. Source: refunds rose from 10% to 11.8%.",
  questions: {
    decision: {
      type: 'choice',
      instructions: "What is the relationship between the source and claim?",
      options: ["supports","partially_supports","contradicts","insufficient"]
    }
  }
});

// Validate permissions and thresholds before acting.
console.log(result.answers.decision);
SAFE IMPLEMENTATION

Keep the boundary clear

Guardrail

Run exact quote and source checks in code first. Route ambiguous semantic judgments to review.

  • Log the input, answer distribution, chosen threshold and resulting route.
  • Test on labelled examples from your own production distribution.
  • Send low-confidence, high-impact or out-of-distribution cases to a safer fallback.
  • Re-evaluate thresholds when the model or workflow changes.
PRIMARY SOURCES

Read before implementing

TypeSafe AI: Introducing System One Models and Jev ↗

Vercel: Jev available on AI Gateway ↗