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 # Video files - compressed
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README.md

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----
-license: cc-by-4.0
----
+---
+annotations_creators:
+- no-annotation
+language_creators:
+- found
+language:
+- it
+- fr
+- es
+- en
+- de
+license: cc-by-4.0
+multilinguality:
+- multilingual
+size_categories:
+- 100K<n<1M
+source_datasets:
+- original
+task_categories:
+- text-retrieval
+- sentence-similarity
+task_ids:
+- semantic-search
+- document-retrieval
+pretty_name: European National Implementing Measures Dataset (ENIMD)
+tags:
+- legal
+- european-union
+- harmonization
+- legislation
+---
+
+# ENIMD: European National Implementing Measures Dataset
+
+**ENIMD** is a large-scale multilingual dataset designed for **legal semantic search** and **harmonization analysis**. It pairs **European Directives (EUDs)** with their corresponding **National Implementing Measures (NIMs)** across five Member States.
+
+The dataset enables the training of models to automatically identify national laws that implement EU directives, distinguishing them from domestic legislation that does not.
+
+## 📄 Paper
+**Pairing EU directives and their national implementing measures: A dataset for semantic search**
+*Roger Ferrod, Denys Amore Bondarenko, Davide Audrito, Giovanni Siragusa*
+Published in **Computer Law & Security Review**, Volume 51, 2023.
+
+[**Read the Paper**](https://doi.org/10.1016/j.clsr.2023.105862) | [**GitHub Repository**](https://github.com/rogerferrod/ENIMD)
+
+## 💾 Dataset Structure
+
+The dataset is organized into three components, catering to different research needs:
+
+### 1. `ML-dataset`
+A shuffled, machine-learning-ready collection of articles split into **Train** and **Test** sets.
+* **Content:** Pairs of EUD articles (Queries) and National Law articles (Documents).
+* **Labels:** Includes `positive` examples (NIMs) and `negative` examples (irrelevant national laws).
+* **Structure:** Articles are labeled with the CELEX number, country code and transposition hash.
+* **Preprocessing:** Filtered using an IDF-based method to remove boilerplate text (e.g., entry into force dates, financial clauses).
+
+### 2. `filtered`
+The parsed collection of articles where irrelevant/boilerplate provisions have been removed using the method described in the paper. Useful for analysis without the noise of administrative clauses.
+
+### 3. `raw`
+The full parsed collection of Directives and National Laws in their original structure (articles/paragraphs), without any filtering.
+
+## 📊 Statistics
+
+The dataset covers legislation from five EU Member States:
+
+| Country   | Language | EUD Articles (Queries) | National Corpus Articles |
+|:----------| :--- |:-----------------------|:-------------------------|
+| Italy     | Italian | 11,514                 | 135,221                  |
+| France    | French | 11,386                 | 236,762                  |
+| Spain     | Spanish | 11,249                 | 209,795                  |
+| Ireland   | English | 11,344                 | 157,601                  |
+| Austria   | German | 11,837                 | 199,781                  |
+| **Total** | **Multilingual** | **57,330**             | **939,160**              |
+
+* **Total Directives:** 906
+* **Total National Documents:** 9,016
+* **Ratio:** ~88% of the national corpus consists of "irrelevant" laws (negative examples), providing a realistic retrieval challenge.
+
+## 💻 Usage
+
+You can load the dataset using the Hugging Face `datasets` library. 
+
+```python
+from datasets import load_dataset
+
+# Load the ML-ready dataset
+dataset = load_dataset("rogerferrod/ENIMD", data_dir="ML-dataset")
+
+# Example: Inspect the first training example
+print(dataset['train'][0])
+```
+
+## ⚖️ Legal Harmonization Task
+
+The primary task is Semantic Search / Retrieval:
+
+1. Query: An article from an EU Directive.
+2. Target: The specific article(s) in National Law that implement that directive.
+3. Challenge: The model must retrieve the correct implementation from a pool of ~900k national articles, most of which are unrelated.
+
+## 📚 Citation
+
+If you use this dataset in your research, please cite the original paper:
+
+```bibtex
+@article{FERROD2023105862,
+title = {Pairing EU directives and their national implementing measures: A dataset for semantic search},
+journal = {Computer Law & Security Review},
+volume = {51},
+pages = {105862},
+year = {2023},
+issn = {2212-473X},
+doi = {https://doi.org/10.1016/j.clsr.2023.105862},
+url = {https://www.sciencedirect.com/science/article/pii/S0267364923000729},
+author = {Roger Ferrod and Denys Amore Bondarenko and Davide Audrito and Giovanni Siragusa}
+}
+```

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