amzn_sec_db / README.md
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---
# HF Dataset Card metadata
pretty_name: "AMZN SEC Filings – Chunk-level Corpus (10-K, 10-Q, 8-K)"
license: mit
language:
- en
tags:
- finance
- sec-edgar
- chromadb
- retrieval
- embeddings
- amzn
task_categories:
- text-retrieval
- question-answering
size_categories:
- 100K<n<1M
source_datasets:
- external:sec-edgar # original raw source
---
# AMZN SEC Filings – Chunk-level Corpus (10-K, 10-Q, 8-K)
<p align="center">
<img alt="Amazon logo" width="120" src="https://upload.wikimedia.org/wikipedia/commons/a/a9/Amazon_logo.svg">
</p>
A ready-to-use, **chunk-level** corpus of Amazon's (AMZN) recent SEC filings
(10-K, 10-Q, and 8-K).
Each paragraph *and* sentence is stored together with rich metadata,
making the dataset ideal for:
* semantic search / RAG pipelines (ChromaDB, FAISS, Weaviate, …)
* question-answering over financial filings
* experimenting with financial-domain embeddings
> Time span : last **5 fiscal years** (rolling window, as of 2025-05-11)
> Collection : 10-K, 10-Q, 8-K (including MD&A summaries & optional exhibits)
> Granularity: ~1000-char paragraphs **and** ≤80-token sentences
---
## Contents
1. [Dataset structure](#dataset-structure)
2. [Download & usage](#quick-start)
3. [Creation process](#creation-process)
4. [Intended use](#intended-use)
5. [Limitations & ethical considerations](#limitations--ethical-considerations)
6. [Citation](#citation)
7. [License](#license)
8. [Contact](#contact)
---
## Dataset structure
The data are stored in Arrow (the native format of 🤗 `datasets`)
so they can be accessed in-memory or streamed on-the-fly.
| Column | Type | Description |
|---------------|------|------------------------------------------------------------------------|
| `text` | str | Plain-text chunk (paragraph or sentence) |
| `metadata` | dict | All fields defined in `FilingMetadata` (ticker, cik, filing_type, …) |
| `id` | str | SHA-1 hash → unique, deterministic identifier |
| `chunk_type`* | str | Paragraph / sentence / summary / exhibit / press_release |
*`chunk_type` is embedded inside `metadata`.
Total size: **≈ 200-400 k chunks** (depends on new filings).
### Example metadata object
```json
{
"ticker": "AMZN",
"cik": "0001018724",
"company_name": "AMAZON.COM, INC.",
"filing_type": "10-K",
"filing_date": "2025-02-02",
"filing_period": "2024-12-31",
"filing_url": "https://www.sec.gov/Archives/...",
"section_id": "item7",
"section_title": "Management’s Discussion and Analysis",
"section_level": 1,
"chunk_index": 3,
"chunk_count": 42,
"chunk_type": "paragraph"
}
```