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