> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/juanceresa/sift-kg/llms.txt
> Use this file to discover all available pages before exploring further.

# Examples Overview

> Explore complete sift-kg pipelines across different domains and document types

Sift-kg includes three complete example pipelines that demonstrate the full extraction, building, and narrative generation workflow across different domains and document types.

## Available Examples

<CardGroup cols={3}>
  <Card title="Transformers Research" icon="brain" href="/examples/transformers">
    12 foundational AI papers analyzed into 425 entities
  </Card>

  <Card title="FTX Collapse" icon="building-columns" href="/examples/ftx">
    9 Wikipedia articles about the cryptocurrency exchange collapse
  </Card>

  <Card title="Epstein/Maxwell Deposition" icon="scale-balanced" href="/examples/epstein">
    Court deposition with OCR-scanned PDF processing
  </Card>
</CardGroup>

## What These Examples Show

Each example includes:

* **Complete source documents** — PDFs or text files you can inspect
* **Full pipeline outputs** — Extractions, graph data, merge proposals, narratives
* **Interactive graph viewer** — Open `output/graph.html` in any browser
* **Real cost data** — Actual LLM API costs from running the pipeline
* **Reproducible commands** — Re-run from existing extractions or start fresh

## Quick Start

All examples can be explored immediately without installation:

```bash theme={null}
# Clone the repository
git clone https://github.com/ARadRareness/sift-kg.git
cd sift-kg/examples

# Open any example's interactive graph
open transformers/output/graph.html  # macOS
xdg-open ftx/output/graph.html       # Linux
start epstein\output\graph.html      # Windows
```

## Comparison Table

| Example          | Documents           | Final Entities | Relations | Domain              | Total Cost |
| ---------------- | ------------------- | -------------- | --------- | ------------------- | ---------- |
| **Transformers** | 12 PDFs             | 425            | 1,122     | Academic research   | \~\$0.72   |
| **FTX**          | 9 text files        | 373            | 1,184     | Finance/journalism  | \~\$0.28   |
| **Epstein**      | 1 PDF (36 sections) | 190            | 387       | Legal/investigative | N/A        |

## Running Examples Yourself

Each example supports two workflows:

### Start from Existing Extractions (Free)

No LLM calls required — use the pre-extracted entities:

```bash theme={null}
pip install sift-kg
sift build -o examples/transformers/output
sift view -o examples/transformers/output
```

### Re-run Full Pipeline

Extract fresh entities from source documents:

```bash theme={null}
sift extract examples/transformers/docs --model openai/gpt-4o-mini -o my-output --domain academic
sift build -o my-output
sift resolve -o my-output --model openai/gpt-4o-mini
sift review -o my-output
sift apply-merges -o my-output
sift narrate -o my-output --model openai/gpt-4o-mini
sift view -o my-output
```

<Tip>
  Start with the **Transformers** example if you're working with academic papers, **FTX** for news articles or business analysis, or **Epstein** if you need OCR support for scanned documents.
</Tip>

## Next Steps

<CardGroup cols={2}>
  <Card title="Install sift-kg" icon="download" href="/quickstart">
    Get started with your own documents
  </Card>

  <Card title="Pipeline Guide" icon="diagram-project" href="/guides/extraction">
    Understand the full extraction workflow
  </Card>
</CardGroup>