Update README.md

README.md

@@ -34,6 +34,9 @@ tags:
 - droit
 - fiscalité
 - taxation
+- δεξιά
+- recht
+- derecho
 pretty_name: The Laws, centralizing legal texts for better use
 ---
 ## Dataset Description
@@ -43,7 +46,7 @@ pretty_name: The Laws, centralizing legal texts for better use
 
 <img src="assets/thumbnail.png">
   
-# Laws, centralizing legal texts for better use, a community Dataset.
+# The Laws, centralizing legal texts for better use, a community Dataset.
 
 The Laws Dataset is a comprehensive collection of legal texts from various countries, centralized in a common format. This dataset aims to improve the development of legal AI models by providing a standardized, easily accessible corpus of global legal documents.
 
@@ -62,6 +65,79 @@ The primary objective of this dataset is to centralize laws from around the worl
 
 By providing a standardized dataset of global legal texts, we aim to accelerate the development of AI models in the legal domain, enabling more accurate and comprehensive legal analysis across different jurisdictions.
 
+## Dataset Structure
+
+The dataset is organized with the following columns:
+
+- `book`: The name or code of the law book (e.g., "Civil Code", "Penal Code")
+- `document`: The full text content of the legal document
+- `timestamp`: The timestamp of when the law was enacted or last updated
+- `id`: A identifier for each document
+- `hash`: A SHA-256 hash of the `document` for verification purposes
+
+Easy-to-use script for hashing the `document`:
+
+```python
+import hashlib
+import datasets
+
+def hash(
+  text: str
+) -> str:
+    """
+    Create or update the hash of the document content.
+
+    This function takes a text input, converts it to a string, encodes it in UTF-8, 
+    and then generates a SHA-256 hash of the encoded text.
+
+    Parameters
+    ----------
+    text : str
+        The text content to be hashed.
+
+    Returns
+    -------
+    str
+        The SHA-256 hash of the input text, represented as a hexadecimal string.
+    """
+    return hashlib.sha256(str(text).encode()).hexdigest()
+
+dataset = dataset.map(lambda x: {"hash": hash(x["document"])})
+```
+
+## Country-based Splits
+
+The dataset uses country-based splits to organize legal documents from different jurisdictions. Each split is identified by the ISO 3166-1 alpha-2 code of the corresponding country.
+
+### ISO 3166-1 alpha-2 Codes
+
+ISO 3166-1 alpha-2 codes are two-letter country codes defined in ISO 3166-1, part of the ISO 3166 standard published by the International Organization for Standardization (ISO).
+
+Some examples of ISO 3166-1 alpha-2 codes:
+- France: fr
+- United States: us
+- United Kingdom: gb
+- Germany: de
+- Japan: jp
+- Brazil: br
+- Australia: au
+
+Before submitting a new split, please make sure the proposed split fits within the ISO code for the related country. 
+
+### Accessing Country-specific Data
+
+To access legal documents for a specific country, you can use the country's ISO 3166-1 alpha-2 code as the split name when loading the dataset. Here's an example:
+
+```python
+from datasets import load_dataset
+
+# Load the entire dataset
+dataset = load_dataset("HFforLegal/laws")
+
+# Access the French legal documents
+fr_dataset = dataset['fr']
+```
+
 ## Ethical Considerations
 
 While this dataset provides a valuable resource for legal AI development, users should be aware of the following ethical considerations:
@@ -78,7 +154,7 @@ If you use this dataset in your research, please use the following BibTeX entry.
 ```BibTeX
 @misc{HFforLegal2024,
   author =       {Louis Brulé Naudet},
-  title =        {The Law, centralizing legal texts for better use},
+  title =        {The Laws, centralizing legal texts for better use},
   year =         {2024}
   howpublished = {\url{https://huggingface.co/datasets/HFforLegal/laws}},
 }