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README.md
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## ToC (Table Of Contents)
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* [
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* [Dataset Structure](#dataset-structure)
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* [Entry Categories](#entry-categories)
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* [Source Documents](#source-documents)
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* [Dataset Versions](#dataset-versions)
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* [Examples](#examples)
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#
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This dataset contains question–answer triplets derived from publications of the Diario Oficial de Galicia (DOG), the official gazette of the autonomous community of Galicia (Spain). Each example is grounded in real legal and administrative documents, covering a wide range of domains such as public employment, housing subsidies, cultural heritage, and institutional regulations.
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import datasets
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# By default, the triplets section of the dataset will be loaded
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triplets = datasets.load("proxectonos/
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# However, it can also be manually specified
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triplets = datasets.load("proxectonos/
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```
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## Dataset Structure
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```python
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import datasets
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dog = datasets.load_dataset('proxectonos/
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dog_metadata = datasets.load_dataset('proxectonos/
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```
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Each document entry in `dog` contains:
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## ToC (Table Of Contents)
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* [DOG-RAG](#dog-rag-qa-triplets)
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* [Dataset Structure](#dataset-structure)
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* [Entry Categories](#entry-categories)
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* [Source Documents](#source-documents)
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* [Dataset Versions](#dataset-versions)
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* [Examples](#examples)
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# DOG-RAG: A Galician Benchmark for Legal Retrieval-Augmented Generation
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This dataset contains question–answer triplets derived from publications of the Diario Oficial de Galicia (DOG), the official gazette of the autonomous community of Galicia (Spain). Each example is grounded in real legal and administrative documents, covering a wide range of domains such as public employment, housing subsidies, cultural heritage, and institutional regulations.
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import datasets
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# By default, the triplets section of the dataset will be loaded
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triplets = datasets.load("proxectonos/dog-rag")
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# However, it can also be manually specified
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triplets = datasets.load("proxectonos/dog-rag","triplets")
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```
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## Dataset Structure
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```python
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import datasets
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dog = datasets.load_dataset('proxectonos/dog-rag','dog')
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dog_metadata = datasets.load_dataset('proxectonos/dog-rag','dog_metadata')
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```
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Each document entry in `dog` contains:
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