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  ---
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- dataset_info:
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- features:
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- - name: id
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- dtype: string
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- - name: conversations
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- list:
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- - name: content
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- dtype: string
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- - name: role
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- dtype: string
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- - name: category
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- dtype: string
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- - name: is_referral
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- dtype: string
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- - name: question_length
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- dtype: int64
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- - name: answer_length
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- dtype: int64
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- splits:
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- - name: train
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- num_bytes: 19310637
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- num_examples: 11703
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- download_size: 8043699
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- dataset_size: 19310637
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ language:
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+ - ar
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+ license: apache-2.0
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+ task_categories:
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+ - text-generation
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+ - question-answering
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+ pretty_name: Fatwa Training Dataset (Standardized)
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+ tags:
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+ - islamic-jurisprudence
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+ - fatwa
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+ - sharia
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+ - fiqh
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+ - arabic
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+ - training
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+ - standardized
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+ - sahm-benchmark
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+
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+ # Fatwa Training Dataset (Standardized)
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+
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+ ## Dataset Description
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+
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+ This is the standardized conversation-format version of the Fatwa training dataset, containing Islamic jurisprudence Q&A pairs for training language models on Islamic legal rulings and religious guidance.
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+
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+ ### Dataset Summary
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+
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+ - **Language:** Arabic
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+ - **Size:** ~11,700 training examples
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+ - **Domain:** Islamic jurisprudence, Sharia law, Fiqh
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+ - **Format:** Conversational (human-agent pairs)
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+ - **Task:** Islamic fatwa generation and religious Q&A
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+
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+ ## Dataset Structure
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+
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+ ### Data Fields
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+
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+ - `id`: Unique identifier for each example
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+ - `conversations`: List containing human-agent dialogue
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+ - Human role: Contains the question with Islamic context framing
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+ - Agent role: Contains the fatwa/religious ruling
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+ - `category`: Category of the fatwa (e.g., murabaha, zakat, riba, etc.)
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+ - `is_referral`: Whether the answer mainly refers to other sources
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+ - `question_length`: Length of the question in characters
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+ - `answer_length`: Length of the answer in characters
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+
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+ ## Categories
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+
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+ The dataset covers various Islamic jurisprudence topics including:
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+ - Murabaha (Islamic financing)
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+ - Zakat (obligatory charity)
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+ - Riba (usury/interest)
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+ - Salah (prayer)
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+ - Hajj (pilgrimage)
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+ - Business transactions
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+ - Family law
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+ - And many more categories
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+
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+ ## Example
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+
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+ ```json
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+ {
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+ "id": "fatwa_00446",
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+ "conversations": [
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+ {
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+ "role": "human",
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+ "content": "بناءً على أحكام الشريعة الإسلامية والفقه الإسلامي، أجب على السؤال التالي بفتوى شرعية مفصلة ومدعمة بالأدلة عند الإمكان.\n\nالسؤال: تحريم الشيء هل يقتضي الفساد؟\n\nالفتوى الشرعية:"
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+ },
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+ {
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+ "role": "agent",
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+ "content": "قد يقتضي الفساد، وقد لا يقتضي الفساد، فالنهي عن البيع يقتضي فساد البيع..."
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+ }
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+ ],
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+ "category": "riba",
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+ "is_referral": "NO",
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+ "question_length": 45,
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+ "answer_length": 234
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+ }
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+ ```
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Load the dataset
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+ dataset = load_dataset("SahmBenchmark/fatwa-training_standardized")
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+ train_data = dataset['train']
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+
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+ # Access an example
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+ example = train_data[0]
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+ conversation = example['conversations']
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+ print(f"Category: {example['category']}")
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+ print(f"Question: {conversation[0]['content']}")
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+ print(f"Fatwa: {conversation[1]['content']}")
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+ ```
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+
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+ ## Training Considerations
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+
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+ When using this dataset for training:
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+ - Ensure the model understands the religious and cultural context
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+ - Be aware that fatwas may vary based on different schools of Islamic thought
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+ - The dataset represents specific interpretations and should be used accordingly
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+ - Consider the sensitivity of religious rulings in production applications
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @dataset{fatwa_training_standardized_2025,
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+ title={Fatwa Training Dataset (Standardized)},
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+ author={SahmBenchmark},
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+ year={2025},
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+ publisher={Hugging Face}
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+ }
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+ ```
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+
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+ ## Disclaimer
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+
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+ This dataset is for academic and research purposes. Religious rulings should be sought from qualified Islamic scholars for practical application.