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ClaimCheck v1.1.0: client-side deterministic LLM answer verifier
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<!doctype html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<title>ClaimCheck — verify LLM answers against their source</title>
<meta name="description" content="Verify LLM answers against their source context before they reach users. Deterministic, client-side, no server." />
<style>
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--derived:#2563eb; --derived-bg:#dbeafe;
--approximate:#ca8a04; --approximate-bg:#fef9c3;
--unsupported:#ea580c; --unsupported-bg:#ffedd5;
--contradicted:#dc2626; --contradicted-bg:#fee2e2;
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a{color:var(--accent)}
</style>
</head>
<body>
<div class="wrap">
<h1>🔎 ClaimCheck</h1>
<p class="lede"><strong>Verify LLM answers against their source context before they reach users.</strong></p>
<p class="lede">We cannot catch every hallucination — but dangerous hallucinations are <em>specific</em>, and specific
claims can be matched as strings. So ClaimCheck checks only what it can check deterministically, and always tells
you <strong>how much it did not check</strong>.</p>
<div class="badges">
<a class="badge" href="https://huggingface.co/NagaYu/claimcheck-rules" target="_blank" rel="noopener">📦 Rule pack</a>
<a class="badge" href="https://huggingface.co/datasets/NagaYu/claimcheck-eval" target="_blank" rel="noopener">📊 158-case eval set</a>
<span class="badge">⚡ ~0.2 ms typical</span>
<span class="badge">🔒 100% client-side</span>
</div>
<div class="note">
<strong>Nothing leaves your browser.</strong> There is no server and no network call: the whole verifier is
JavaScript running in this tab. Paste real model output if you want to — it stays on your machine.
</div>
<div class="tabs" role="tablist">
<button class="tab" role="tab" aria-selected="true" data-p="verify">Verify</button>
<button class="tab" role="tab" aria-selected="false" data-p="retry">Retry</button>
<button class="tab" role="tab" aria-selected="false" data-p="json">JSON repair</button>
<button class="tab" role="tab" aria-selected="false" data-p="about">How it works</button>
</div>
<section class="panel" id="p-verify">
<div class="grid">
<div>
<div class="field"><label for="answer">Answer — the LLM output to check</label>
<textarea id="answer" rows="9"></textarea></div>
<div class="field"><label for="context">Context — the source of truth given to the model</label>
<textarea id="context" rows="9"></textarea></div>
</div>
<div>
<div class="field"><label for="system">System prompt (optional — enables leak detection)</label>
<textarea id="system" rows="4"></textarea></div>
<div class="field"><label for="userin">User input (optional — enables injection-echo detection)</label>
<textarea id="userin" rows="3"></textarea></div>
<div class="field"><label for="schema">Schema JSON (optional — only if the answer must be JSON)</label>
<textarea id="schema" rows="3" placeholder='{"title": "str", "score": "float"}'></textarea></div>
<div class="field"><label for="policy">Policy JSON (optional — threshold overrides)</label>
<textarea id="policy" rows="5"></textarea></div>
</div>
</div>
<button class="go" id="run">Verify</button>
<div id="out"></div>
</section>
<section class="panel" id="p-retry" hidden>
<p class="muted">A blind retry re-sends the whole system prompt + context + question and regenerates everything.
A targeted retry re-sends only the answer plus the specific failing claims. The difference is the estimate below.
Run <strong>Verify</strong> first.</p>
<button class="go" id="run-retry">Build retry instruction</button>
<div id="retry-out"></div>
</section>
<section class="panel" id="p-json" hidden>
<p class="muted">Structural repair only. <strong>The point is to never burn a retry on formatting.</strong>
Fences, trailing commas, single quotes, raw newlines inside strings, fullwidth punctuation and Python literals
are all fixed locally — retries are reserved for claims that are actually wrong.</p>
<div class="grid">
<div class="field"><label for="raw">Raw model output</label><textarea id="raw" rows="12"></textarea></div>
<div class="field"><label for="schema2">Schema JSON (optional)</label><textarea id="schema2" rows="12"></textarea></div>
</div>
<button class="go" id="run-json">Extract / repair / coerce</button>
<div id="json-out"></div>
</section>
<section class="panel" id="p-about" hidden>
<h2>Always read <code>coverage</code></h2>
<p>Every result carries two independent numbers, and reporting one without the other is the most dangerous way to
misuse this tool.</p>
<table>
<tr><th>field</th><th>question it answers</th></tr>
<tr><td><code>grounding_score</code></td><td>Of the claims I checked, what share held up?</td></tr>
<tr><td><code>coverage</code></td><td>What share of the answer did I check at all?</td></tr>
</table>
<p><code>grounding_score</code> alone is a trap. An answer of pure vague hedging produces <strong>zero</strong>
claims and scores <strong>1.00</strong> on any naive groundedness metric — while being completely unverified.
A high score at low coverage means <em>"I could not find anything to check"</em>, not <em>"everything is fine"</em>.</p>
<h2>Claim statuses</h2>
<table>
<tr><th>status</th><th>meaning</th></tr>
<tr><td><span class="st supported">supported</span></td><td>Appears literally in the context after normalisation</td></tr>
<tr><td><span class="st derived">derived</span></td><td>Computable from context numbers by 2–3 term arithmetic; the formula is shown</td></tr>
<tr><td><span class="st approximate">approximate</span></td><td>A near match exists — paraphrase, finer-grained date, related URL</td></tr>
<tr><td><span class="st unsupported">unsupported</span></td><td>Nothing in the context backs it</td></tr>
<tr><td><span class="st contradicted">contradicted</span></td><td>The context holds a <strong>near but different</strong> value</td></tr>
</table>
<p class="muted"><code>approximate</code> is deliberately <em>not</em> counted as grounded: a paraphrased quote is
still an inaccurate quote.</p>
<h2>Measured behaviour</h2>
<p>On the <a href="https://huggingface.co/datasets/NagaYu/claimcheck-eval" target="_blank" rel="noopener">158-case
bilingual evaluation set</a>:</p>
<pre>answer-level recall 56/56 (100%) cases that should be flagged, and were
clean answers passing 44/46 (96%) the rest were annotated, never blocked
known false positives 22 (13.9%)
known false negatives 3 (1.9%)
JS/Python parity 158/158 (100%)</pre>
<p>The false-positive rate is published deliberately. It is the number that decides whether anyone keeps a verifier
switched on, and hiding it helps nobody.</p>
<h2>The most serious failure: semantic reversal</h2>
<p>All three false negatives are the same shape. A one-character change that reverses meaning keeps character
similarity above 0.9, so a reversed quote reads as a faithful paraphrase:</p>
<table>
<tr><th>context</th><th>answer</th><th>similarity</th><th>status</th></tr>
<tr><td>売上高は7%<strong>増加</strong>した</td><td>売上高は7%<strong>減少</strong>した</td><td>0.97</td><td><span class="st approximate">approximate</span> ❌</td></tr>
<tr><td>提案は全会一致で<strong>承認</strong>された</td><td>提案は全会一致で<strong>否決</strong>された</td><td>0.92</td><td><span class="st approximate">approximate</span> ❌</td></tr>
<tr><td>revenue <strong>grew</strong> 8%</td><td>revenue <strong>declined</strong> 8%</td><td>0.97</td><td><span class="st approximate">approximate</span> ❌</td></tr>
</table>
<p>Character-level matching cannot detect negation or antonym substitution. If your domain turns on
approve/reject or increase/decrease, <strong>do not rely on quote status alone.</strong> In all three cases the
answer-level verdict was still <code>retry</code>, because the NUMERIC and ENTITY claims inside the quote are the
layer that catches what the quote check misses.</p>
<h2>When it is wrong (false positives)</h2>
<ul class="muted">
<li><strong>Faithful paraphrase</strong> — meaning preserved, wording replaced. The largest group.</li>
<li><strong>Generic noun phrases</strong> — "Machine Learning" flagged as an unsupported entity.</li>
<li><strong>Acronym expansion</strong> — context "World Health Organization", answer "WHO".</li>
<li><strong>Rounding</strong> — context 12,345 vs answer "roughly 12,000": inside the near-miss window.
Raise <code>numeric_tolerance</code> rather than lowering <code>contradiction_rel</code>.</li>
<li><strong>Fiscal vs calendar year</strong> — FY2024 and 2024 treated as the same period.</li>
<li><strong>Identifier variants</strong> — ISO 9001:2015 where the source says ISO 9001. The deliberate cost of
catching one-digit-off fabrications.</li>
<li><strong>URL query parameters</strong> — a tracking parameter breaks exact matching.</li>
</ul>
<p><strong>ENTITY is the noisiest check.</strong> Set <code>{"enable_entity": false}</code> in the policy box first
if you see too much noise, and start from <code>annotate</code>, never <code>block</code>.</p>
<h2>Not checked, on purpose</h2>
<ul class="muted">
<li><strong>Relative dates</strong> ("last year", "昨年") — unresolvable without a generation date.</li>
<li><strong>Bare small integers</strong> (0–10, no unit) are never marked contradicted: they sit near everything.</li>
<li><strong>List markers</strong> ("1.", "2)") are not numeric claims.</li>
<li><strong>Reasoning, tone, completeness, relevance.</strong> None are string-checkable.</li>
</ul>
<p class="warn">ClaimCheck is one layer of defence, not a correctness guarantee.</p>
</section>
<footer>
Apache-2.0 ·
<a href="https://huggingface.co/NagaYu/claimcheck-rules" target="_blank" rel="noopener">rule pack</a> ·
<a href="https://huggingface.co/datasets/NagaYu/claimcheck-eval" target="_blank" rel="noopener">evaluation set</a> ·
verification runs entirely in your browser
</footer>
</div>
<script type="module">
import * as cc from "./claimcheck.js";
const DEMO = {
context: ["2024年度の売上高は12,000百万円、営業利益は1,800百万円でした。",
"従業員数は3,400人で、前年度(2023年度)は3,200人でした。",
"新製品Xは2024年3月15日に発売されました。",
"IR資料は https://example.com/ir/2024 に掲載しています。",
"契約は第12条に基づき自動更新されます。"].join("\n"),
answer: ["2024年度の売上高は12,000百万円、営業利益は1,800百万円でした。",
"したがって営業利益率は15%です。",
"従業員数は3,400人、前年度は3,250人でした。",
"新製品Xは2024年3月15日に発売されています。",
"なお解約率は7.2%に達しており、注意が必要です。",
"詳細は https://example.com/ir/2025 をご覧ください。"].join("\n"),
system: ["あなたは企業のIR資料に基づいて回答するアシスタントです。",
"与えられた文脈のみを根拠とし、文脈に無い数値を作らないでください。"].join("\n"),
policy: JSON.stringify({ enable_entity: true, retry_on_contradicted: 1, pass_grounding: 0.95, pass_coverage: 0.5 }, null, 2),
raw: ['```json', '{', ' \'title\': "Quarterly report",', ' "score": 0.87,',
' "tags": ["ir", "2024",],', ' "note": "a multi-line', 'memo",', ' "published": True,', '}', '```'].join("\n"),
schema2: JSON.stringify({ title: "str", score: "float", tags: "list", published: "bool", "note?": "str" }, null, 2),
};
const $ = (id) => document.getElementById(id);
$("answer").value = DEMO.answer; $("context").value = DEMO.context;
$("system").value = DEMO.system; $("policy").value = DEMO.policy;
$("raw").value = DEMO.raw; $("schema2").value = DEMO.schema2;
for (const t of document.querySelectorAll(".tab")) {
t.addEventListener("click", () => {
for (const o of document.querySelectorAll(".tab")) o.setAttribute("aria-selected", String(o === t));
for (const p of document.querySelectorAll(".panel")) p.hidden = p.id !== "p-" + t.dataset.p;
});
}
const esc = (s) => String(s).replace(/[&<>"]/g, (c) => ({ "&": "&amp;", "<": "&lt;", ">": "&gt;", '"': "&quot;" }[c]));
const BADGE = { pass: "✅ PASS", annotate: "🟡 ANNOTATE", retry: "🟠 RETRY", block: "🔴 BLOCK" };
let LAST = null;
function render(r, answer) {
if (!r || !r.ok) return `<p class="warn">Error: ${esc(JSON.stringify(r && r.error))}</p>`;
const v = r.verify, c = v ? v.counts : null, bs = c ? c.by_status : {};
const est = (r.retry && r.retry.estimate) || {};
const leak = (r.leak && r.leak.system_prompt) || {};
const safety = r.safety || {};
const sTypes = [...new Set((safety.findings || []).map((f) => f.type))].join(", ") || "clean";
let h = `<p class="verdict">${BADGE[r.verdict] || esc(r.verdict)}</p>`;
if (v) {
h += `<table>
<tr><th>metric</th><th>value</th><th>meaning</th></tr>
<tr><td><strong>grounding_score</strong></td><td class="num">${(v.grounding_score * 100).toFixed(1)}%</td>
<td>of the claims we checked, this share held up</td></tr>
<tr><td><strong>coverage</strong></td><td class="num">${(v.coverage * 100).toFixed(1)}%</td>
<td>share of sentences that produced <em>any</em> checkable claim</td></tr>
<tr><td>unchecked sentences</td><td class="num">${c.sentences_unverified} / ${c.sentences_total}</td>
<td class="warn">not verified — read them yourself</td></tr>
<tr><td>latency</td><td class="num">${r.meta.latency_ms} ms</td><td>measured per request, in this tab</td></tr>
<tr><td>claims</td><td class="num">${c.claims_total}</td><td>
<span class="st supported">supported ${bs.supported}</span> ·
<span class="st derived">derived ${bs.derived}</span> ·
<span class="st approximate">approximate ${bs.approximate}</span> ·
<span class="st unsupported">unsupported ${bs.unsupported}</span> ·
<span class="st contradicted">contradicted ${bs.contradicted}</span></td></tr>
<tr><td>safety</td><td class="num">${(safety.findings || []).length} / ${safety.critical || 0} critical</td><td>${esc(sTypes)}</td></tr>
<tr><td>system-prompt leak</td><td class="num">${leak.leak ? "YES" : "no"}</td>
<td>${(leak.overlap || 0).toFixed(3)} overlap vs threshold ${leak.threshold ?? "—"}</td></tr>
<tr><td>retry saving</td><td class="num">${est.saved_tokens ?? 0} tok</td><td>${esc(est.recommendation || "—")}</td></tr>
</table>`;
h += `<p class="muted"><strong>Reasons:</strong> ${esc((r.reasons || []).join("; "))}</p>`;
if (v.coverage < 0.5)
h += `<div class="note"><strong>⚠️ coverage is low.</strong> A high grounding_score here means very little —
most of this answer was never checked.</div>`;
h += `<div class="legend">` + ["supported", "derived", "approximate", "unsupported", "contradicted"]
.map((s) => `<span><i class="key" style="background:var(--${s})"></i>${s}</span>`).join("") + `</div>`;
h += `<div class="hl">` + cc.buildHighlight(answer, v.claims)
.map(([t, st]) => (st ? `<mark class="${st}">${esc(t)}</mark>` : esc(t))).join("") + `</div>`;
if (v.claims.length) {
h += `<table><tr><th>type</th><th>value</th><th>status</th><th>evidence</th></tr>` +
v.claims.map((cl) => `<tr><td class="muted">${cl.type}</td><td><code>${esc(cl.value)}</code></td>
<td><span class="st ${cl.status}">${cl.status}</span></td>
<td class="muted">${esc(cl.evidence || "—")}</td></tr>`).join("") + `</table>`;
}
if (v.unverified_sentences.length) {
h += `<details><summary>${v.unverified_sentences.length} sentence(s) were NOT checked — read these yourself</summary>`
+ v.unverified_sentences.map((u) => `<p class="muted">${esc(u.text)}</p>`).join("") + `</details>`;
}
} else {
h += `<p class="muted"><strong>Reasons:</strong> ${esc((r.reasons || []).join("; "))}</p>`;
h += `<div class="note">Verification was skipped: a critical output-safety violation short-circuits the gate.
Verifying the grounding of an answer that leaks a credential is wasted work.</div>`;
if ((safety.findings || []).length)
h += `<table><tr><th>type</th><th>severity</th><th>masked</th></tr>` + safety.findings
.map((f) => `<tr><td>${esc(f.type)}</td><td class="warn">${esc(f.severity)}</td><td><code>${esc(f.value)}</code></td></tr>`).join("") + `</table>`;
}
if ((r.warnings || []).length) h += `<p class="muted"><strong>Warnings:</strong> ${esc(r.warnings.join("; "))}</p>`;
h += `<details><summary>Full result JSON</summary><pre>${esc(JSON.stringify(r, null, 2))}</pre></details>`;
return h;
}
$("run").addEventListener("click", () => {
const a = $("answer").value;
LAST = cc.gate(a, $("context").value, $("system").value, $("userin").value, $("schema").value, $("policy").value, "");
LAST._answer = a;
$("out").innerHTML = render(LAST, a);
});
$("run-retry").addEventListener("click", () => {
if (!LAST || !LAST.verify) { $("retry-out").innerHTML = `<p class="muted">Run <strong>Verify</strong> first.</p>`; return; }
const adv = cc.buildRetryInstruction({ verify: LAST.verify, meta: { sizes: LAST.meta.sizes } });
if (!adv.needed) { $("retry-out").innerHTML = `<p class="muted">No unsupported or contradicted claims — a retry is not warranted.</p>`; return; }
const e = adv.estimate;
$("retry-out").innerHTML =
`<table><tr><th>metric</th><th>value</th></tr>
<tr><td>failing claims</td><td class="num">${adv.failed_claims}</td></tr>
<tr><td>blind retry</td><td class="num">${e.blind_retry_tokens} tokens</td></tr>
<tr><td>targeted retry</td><td class="num">${e.targeted_retry_tokens} tokens</td></tr>
<tr><td>saved</td><td class="num">${e.saved_tokens} tokens</td></tr>
</table>
<p class="muted">${esc(e.recommendation)}</p>
<p class="muted"><code>saved_tokens</code> is signed on purpose: with a small context the instruction can cost more
than the blind retry it replaces, and hiding that would make this tool lie about its own value.</p>
<label>Instruction — append this to the next request</label>
<pre>${esc(adv.instruction)}</pre>
<details><summary>日本語版</summary><pre>${esc(adv.instruction_ja)}</pre></details>
<details><summary>Full advice JSON</summary><pre>${esc(JSON.stringify(adv, null, 2))}</pre></details>`;
});
$("run-json").addEventListener("click", () => {
const r = cc.structureCheck($("raw").value, $("schema2").value);
$("json-out").innerHTML =
`<table><tr><th>check</th><th>result</th></tr>
<tr><td>valid JSON after repair</td><td class="num">${r.valid_json ? "✅ yes" : "❌ no"}</td></tr>
<tr><td>satisfies schema</td><td class="num">${r.schema_ok === null ? "—" : r.schema_ok ? "✅ yes" : "❌ no"}</td></tr>
<tr><td>repairs applied</td><td>${r.repairs.length ? r.repairs.map((x) => `<code>${esc(x)}</code>`).join(" ") : "none needed"}</td></tr>
<tr><td>missing keys</td><td>${r.missing.length ? esc(r.missing.join(", ")) : "none"}</td></tr>
</table>
<label>Repaired value</label><pre>${esc(JSON.stringify(r.value, null, 2))}</pre>`;
});
$("run").click();
</script>
</body>
</html>