README / index.html
yenkienoodle's picture
Sync canonical Dali one-liner, seed vs full-run, v0.2.1 framing
ec40a49 verified
Raw
History Blame Contribute Delete
7.99 kB
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1" />
<title>Dali — the open verification layer for AI</title>
<meta
name="description"
content="Dali is the open verification layer for AI: it creates, scores, and preserves evidence so AI-assisted outputs can be independently verified, exchanged, and replayed."
/>
<meta name="color-scheme" content="light dark" />
<style>
body {
margin: 0;
padding: 1.5rem 1rem 2rem;
font-family: system-ui, -apple-system, sans-serif;
line-height: 1.55;
color: CanvasText;
background: Canvas;
}
main {
max-width: 42rem;
margin: 0 auto;
}
h1 {
margin: 0 0 0.25rem;
font-size: 1.85rem;
letter-spacing: 0.04em;
}
h3 {
margin: 0 0 0.35rem;
font-size: 1rem;
font-weight: 600;
}
.lede {
margin: 0 0 1.25rem;
opacity: 0.85;
}
hr {
border: 0;
border-top: 1px solid color-mix(in srgb, CanvasText 18%, transparent);
margin: 1.25rem 0;
}
h2 {
font-size: 1rem;
margin: 0 0 0.85rem;
}
.artifact {
margin: 0 0 1rem;
}
.artifact strong a {
color: CanvasText;
text-decoration: none;
}
.artifact strong a:hover {
text-decoration: underline;
}
.artifact p {
margin: 0.15rem 0 0;
opacity: 0.8;
font-size: 0.95rem;
}
.status {
font-style: italic;
opacity: 0.7;
font-size: 0.85rem;
}
pre {
margin: 0 0 1rem;
padding: 0.85rem 1rem;
overflow-x: auto;
font-family: ui-monospace, Menlo, Consolas, monospace;
font-size: 0.82rem;
line-height: 1.45;
border: 1px solid color-mix(in srgb, CanvasText 18%, transparent);
background: color-mix(in srgb, CanvasText 4%, Canvas);
}
.cta {
margin: 0;
font-weight: 600;
}
.cta a {
color: LinkText;
text-decoration: none;
}
.cta a:hover {
text-decoration: underline;
}
table {
width: 100%;
border-collapse: collapse;
font-size: 0.92rem;
margin: 0 0 1rem;
}
th,
td {
border: 1px solid color-mix(in srgb, CanvasText 18%, transparent);
padding: 0.45rem 0.55rem;
text-align: left;
vertical-align: top;
}
th {
font-weight: 600;
}
.ecosystem {
font-size: 0.92rem;
margin: 0 0 1rem;
}
.ecosystem li {
margin-bottom: 0.35rem;
}
blockquote {
margin: 1rem 0 0;
padding-left: 0.85rem;
border-left: 3px solid color-mix(in srgb, CanvasText 25%, transparent);
font-style: italic;
opacity: 0.9;
}
</style>
</head>
<body>
<main>
<h1>Dali</h1>
<h3>The open verification layer for AI</h3>
<p class="lede">
Dali is the open verification layer for AI: it creates, scores, and preserves
evidence so AI-assisted outputs can be independently verified, exchanged, and
replayed. Legal AI is the proving ground.
</p>
<hr />
<h2>Open Artifacts</h2>
<div class="artifact">
<strong
><a href="https://huggingface.co/datasets/yenklabs/open-evidence-corpus"
>Dali Open Evidence Corpus</a
></strong
>
<span class="status">· available</span>
<p>Cross-jurisdiction seed evidence for reproducible research.</p>
</div>
<div class="artifact">
<strong
><a href="https://huggingface.co/datasets/yenklabs/dali-citation-benchmark"
>Dali Citation Benchmark (Seed Sample)</a
></strong
>
<span class="status">· available</span>
<p>5 hand-curated cases, 14 authorities — methodology review sample (not the full run).</p>
</div>
<div class="artifact">
<strong
><a href="https://huggingface.co/datasets/yenklabs/dali-verification-taxonomy"
>Dali Verification Taxonomy</a
></strong
>
<span class="status">· available</span>
<p>Shared vocabulary for classifying verification outcomes.</p>
</div>
<div class="artifact">
<strong
><a href="https://github.com/yenklabs/Dali/tree/main/data/results"
>Full evaluation run</a
></strong
>
<span class="status">· available</span>
<p>524 citations · 3 models · 5 jurisdiction tracks — on GitHub data/results/.</p>
</div>
<div class="artifact">
<strong><a href="https://github.com/yenklabs/Dali">Evidence Infrastructure</a></strong>
<span class="status">· available (early-stage v0.2.1)</span>
<p>Open verification engine, methodologies, and reproducible evaluation workflows.</p>
</div>
<hr />
<h2>Quick Start</h2>
<pre><code>from datasets import load_dataset
dataset = load_dataset("yenklabs/open-evidence-corpus")</code></pre>
<p class="cta">
<a href="https://github.com/yenklabs/Dali">GitHub</a> ·
<a href="https://github.com/yenklabs/Dali/blob/main/CONTRIBUTING.md">Contribute</a> ·
<a href="https://yenklabs.com">yenklabs.com</a>
</p>
<hr />
<h2>Research models (roadmap)</h2>
<p style="margin: 0 0 0.75rem; opacity: 0.85; font-size: 0.95rem">
Lightweight, reproducible research models — not foundation models. All <em>planned</em>.
</p>
<table>
<thead>
<tr>
<th>Release</th>
<th>Model</th>
<th>Purpose</th>
<th>Status</th>
</tr>
</thead>
<tbody>
<tr>
<td>v0.1</td>
<td>Dali Verification Taxonomy Classifier</td>
<td>Predict standardized verification outcome labels</td>
<td>planned</td>
</tr>
<tr>
<td>v0.2</td>
<td>Dali Citation Risk Classifier</td>
<td>Estimate citation verification risk from evidence metadata</td>
<td>planned</td>
</tr>
<tr>
<td>v0.3</td>
<td>Dali Authority Matching Baseline</td>
<td>Reproducible baseline for authority matching experiments</td>
<td>planned</td>
</tr>
<tr>
<td>v0.4</td>
<td>Dali Proposition Support Classifier</td>
<td>Classify proposition support relationships for legal authorities</td>
<td>planned</td>
</tr>
</tbody>
</table>
<h2>Ecosystem</h2>
<ul class="ecosystem">
<li><strong>Datasets</strong> — Open Evidence Corpus, Citation Benchmark seed sample, Verification Taxonomy · <em>available</em></li>
<li><strong>Full evaluation run</strong> — 524 citations on <a href="https://github.com/yenklabs/Dali/tree/main/data/results">github.com/yenklabs/Dali/data/results</a> · <em>available</em></li>
<li><strong>Models</strong> — Taxonomy Classifier, Citation Risk, Authority Matching, Proposition Support · <em>planned</em></li>
<li><strong>Spaces</strong> — Evidence Explorer, Benchmark Dashboard, Citation Verification Demo · <em>planned</em></li>
<li><strong>Future datasets</strong> — Evaluation Prompts, Replay Corpus, Evidence Artifacts · <em>planned</em></li>
</ul>
<blockquote>
Dali is the open verification layer for AI: it creates, scores, and preserves evidence so
AI-assisted outputs can be independently verified, exchanged, and replayed.
</blockquote>
</main>
</body>
</html>