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README.md
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## Dataset Structure
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Easy-to-use script for hashing the `document`:
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```python
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## Dataset Structure
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# Dataset Structure
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The dataset contains the following columns:
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1. **jurisdiction**: Capitalized ISO 3166-1 alpha-2 code representing the country or jurisdiction. This column is useful when stacking data from different jurisdictions.
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2. **language**: Non-capitalized ISO 639-1 code representing the language of the document. This is particularly useful for multilingual jurisdictions.
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3. **text**: The main textual content of the document.
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4. **html**: An HTML-structured version of the text. This may include additional structure such as XML (Akoma Ntoso).
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5. **title_main**: The primary title of the document. This replaces the 'book' column, as many modern laws are not structured or referred to as 'books'.
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6. **title_alternative**: A list of official and non-official (nickname) titles for the document.
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7. **id_sub**: Identifier for lower granularity items within the document, such as specific article numbers. This replaces the 'id' column.
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8. **id_main**: Document identifier for the main document, such as the European Legislation Identifier (ELI).
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9. **url_sourcepage**: The source URL of the web page where the document is published.
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10. **url_sourcefile**: The source URL of the document file (e.g., PDF file).
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11. **date_publication**: The date when the document was published.
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12. **date_signature**: The date when the document was signed.
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13. **uuid**: A universally unique identifier for each row in the dataset.
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14. **text_hash**: A SHA-256 hash of the 'text' column, useful for verifying data integrity.
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15. **formatted_date**: The publication date formatted as 'YYYY-MM-DD HH:MM:SS', derived from the 'date_publication' column.
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This structure ensures comprehensive metadata for each legal document, facilitating easier data management, cross-referencing, and analysis across different jurisdictions and languages.
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Easy-to-use script for hashing the `document`:
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```python
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