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Add sample data and dataset card for sec-filings-sample

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README.md ADDED
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - text-classification
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+ - feature-extraction
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+ language:
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+ - en
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+ tags:
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+ - sec
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+ - edgar
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+ - filings
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+ - finance
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+ - 10-K
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+ - 8-K
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+ - securities
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+ size_categories:
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+ - 1K-10K
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+ ---
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+
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+ # SEC EDGAR Filings — Sample Dataset
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+
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+ A sample of 1,000 recent 8-K filings from SEC EDGAR, containing filing metadata and document references.
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+
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+ ## Dataset Description
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+
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+ The full SEC dataset includes millions of filings across all form types (10-K, 10-Q, 8-K, S-1, DEF 14A, etc.) from all publicly traded US companies. This sample contains 1,000 recent 8-K (material event) filings for evaluation.
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+
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+ ### Source
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+
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+ - **Publisher**: U.S. Securities and Exchange Commission
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+ - **URL**: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany
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+ - **Update frequency**: Every 15 minutes
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+ - **License**: Public domain (US government work)
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+
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+ ### Fields
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+
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+ | Field | Type | Description |
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+ |-------|------|-------------|
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+ | accession_number | string | Unique filing identifier |
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+ | cik | string | Central Index Key (company ID) |
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+ | company_name | string | Registrant name |
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+ | form_type | string | Filing form type (8-K, 10-K, etc.) |
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+ | filing_date | string | Date filed with SEC |
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+ | accepted_date | string | Date accepted by EDGAR |
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+ | document_url | string | URL to primary filing document |
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+ | filing_url | string | URL to EDGAR filing index |
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+
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+ ### Use Cases
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+
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+ - Financial analysis and research
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+ - SEC compliance monitoring
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+ - Corporate event detection (8-K analysis)
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+ - Quantitative finance / NLP on filings
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+ - Company fundamental analysis
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+
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+ ## Full Dataset Access
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+
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+ This is a sample. The full dataset is available via:
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+
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+ - **x402 API**: Pay-per-query with USDC — [verilexdata.com/docs/x402](https://verilexdata.com/docs/x402)
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+ - **Snowflake**: Native App on Snowflake Marketplace — [verilexdata.com/docs/snowflake](https://verilexdata.com/docs/snowflake)
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+ - **Databricks**: Delta Sharing — [verilexdata.com/docs/databricks](https://verilexdata.com/docs/databricks)
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+
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+ Visit [verilexdata.com](https://verilexdata.com) for pricing and documentation.
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