Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
json
Sub-tasks:
fact-checking
Languages:
Slovak
Size:
10K - 100K
License:
Override
Browse files
README.md
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---
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language:
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- sk
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- question-answering
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- medical
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- slovak
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- conversational
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license: cc-by-4.0
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task_categories:
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- question-answering
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- text-generation
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- conversational
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size_categories:
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---
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#
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## Dataset Description
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- Pain management (headaches, joint pain, muscle pain)
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- Medication advice and drug interactions
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- Common ailments and symptoms
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- Chronic conditions (diabetes, neuropathy, arthritis)
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- Over-the-counter medication recommendations
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- General health and wellness questions
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- Medical information retrieval systems
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- Understanding common health concerns in Slovak-speaking populations
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- Research in pharmaceutical and medical NLP
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### Languages
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## Dataset Structure
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### Data Fields
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- `url` (string): The full URL to the Q&A page on DrMax.sk
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- `slug` (string): URL slug/identifier for the question
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- `title` (string): The title/summary of the question
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- `question` (string): Full text of the patient's question
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- `answer` (string): Complete pharmacist's response with recommendations
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- `date` (string): Publication date of the Q&A (format: DD. M. YYYY)
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- `tags` (list of strings): Categorization tags (average 2.04 tags per entry, 367 unique tags)
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- `question_author` (string): Name of the person who asked (usually empty for privacy)
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- `answer_author` (string): Name and credentials of the responding pharmacist
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- `scraped_at` (string): ISO 8601 timestamp of when the data was collected
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### Data Splits
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This dataset contains a single split with 4,703 examples.
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### Example
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```python
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{
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'url': 'https://www.drmax.sk/spytajte-sa-lekarnika/bolest-hlavy-a-nevolnost',
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'slug': 'bolest-hlavy-a-nevolnost',
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'title': 'bolesť hlavy a nevoľnosť',
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'question': 'dobrý deň\n(Som cudzinec a môj jazyk nie je dobrý)\nMám migrénu na ľavej strane a za uchom, stav 6/10.\nSprevádzané pretrvávajúcou únavou a nevoľnosťou. Moja choroba sa stala v posledných dvoch dňoch\nĎakujem',
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'answer': 'Dobrý deň,\nďakujeme za Vašu otázku. Migréna sa vyznačuje silnou a pulzujúcou bolesťou len na jednej polovici hlavy...',
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'date': '25. 6. 2022',
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'tags': ['bolesť', 'bolesť hlavy', 'migréna', 'tlmenie bolesti', 'nevoľnosť'],
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'question_author': '',
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'answer_author': 'PharmDr. Dominika Titková',
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'scraped_at': '2025-11-11T17:00:33.177495'
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}
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```
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## Dataset Creation
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### Source Data
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The Q&A pairs were collected from DrMax.sk's "Spýtajte sa lekárnika" (Ask the Pharmacist) section, where real patients ask health-related questions and licensed pharmacists provide professional answers.
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#### Data Collection
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- **Collection Date**: November 11, 2025
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- **Collection Method**: Automated web scraping using Scrapy and Playwright
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- **Source Website**: DrMax.sk (leading pharmacy chain in Slovakia and Central Europe)
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- **Content Type**: Public Q&A forum moderated by licensed pharmacists
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- **Time Range**: Questions and answers from 2022 onwards
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### Annotations
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- **Tags**: The dataset includes 367 unique tags covering medical topics, symptoms, conditions, and treatments
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- **Average Tags per Entry**: 2.04
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- **Author Attribution**: Most answers include the pharmacist's name and credentials (PharmDr., Mgr.)
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## Dataset Statistics
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- **Total Q&A Pairs**: 4,703
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- **Unique Tags**: 367
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- **Average Tags per Entry**: 2.04
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- **Questions with Tags**: 100%
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- **File Size**: ~2.7 MB (Parquet format)
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- **Language**: Slovak
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### Common Topics (by tag frequency)
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The dataset covers a wide range of pharmaceutical and medical topics including pain management, vitamins, skin conditions, digestive issues, respiratory problems, and medication advice.
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## Use Cases
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### Question-Answering Systems
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Train or fine-tune models to answer health and pharmaceutical questions in Slovak.
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### Medical Chatbots
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Develop conversational AI assistants for pharmacy and healthcare contexts.
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### Information Retrieval
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Build semantic search systems for medical information in Slovak language.
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### Research Applications
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- Study common health concerns in Slovak-speaking populations
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- Analyze patient-pharmacist communication patterns
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- Research pharmaceutical recommendations and practices
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- Develop medical NLP tools for Slovak language
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### Educational Tools
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Create training materials for pharmacy students or healthcare professionals.
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## Considerations for Using the Data
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### Social Impact
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**Positive Impacts:**
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- Improves healthcare information accessibility in Slovak
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- Provides training data for medical AI systems in underrepresented language
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- Democratizes access to pharmaceutical knowledge
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- Can help reduce healthcare information gaps
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**Potential Risks:**
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- Models trained on this data should NOT replace professional medical advice
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- Automated systems should clearly indicate they are not substitutes for doctors/pharmacists
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- Misinformation risk if models generate incorrect medical advice
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### Discussion of Biases
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**Known Biases:**
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- **Commercial Bias**: Answers often recommend DrMax products by name
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- **Demographic Bias**: Questions may reflect specific age groups or populations more than others
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- **Geographic Bias**: Slovak-specific pharmaceutical products and healthcare system
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- **Temporal Bias**: Medical knowledge and pharmaceutical recommendations from 2022+ only
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- **Selection Bias**: Only includes questions that were selected for publication on the website
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**Recommended Mitigations:**
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- Cross-reference with multiple medical sources
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- Include disclaimers about medical advice
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- Consider fine-tuning with more diverse medical sources
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- Validate recommendations against current medical guidelines
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- This data should be used responsibly for healthcare improvement
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- Do not use for generating medical advice without human oversight
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- Consider impact on healthcare accessibility and safety
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- Respect patient privacy even though data is public
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- **Domain**: Pharmacy/OTC medication focused - not comprehensive medical knowledge
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- **Temporal**: Snapshot from specific time period - medical knowledge evolves
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- **Quality Variance**: Answer quality may vary between different pharmacists
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- **Product Focus**: Tendency to recommend specific branded products
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- **Scope**: Limited to questions deemed appropriate for pharmacist advice (no serious diagnosis)
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- Provide attribution to both this dataset and DrMax as the source
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- Not claim the medical advice as their own
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- Respect DrMax's terms of service
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If you use this dataset, please cite:
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```bibtex
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@dataset{drmax_pharmacy_qa_2025,
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title={DrMax Pharmacy Q&A Dataset},
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author={NaiveNeuron},
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year={2025},
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publisher={HuggingFace},
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url={https://huggingface.co/datasets/[your-username]/drmax-pharmacy-qa},
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note={4,703 Slovak pharmacy Q&A pairs from DrMax.sk}
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}
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```
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### Contributions
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Dataset created and maintained by the pharmacy-scrapers project.
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**Data Source**: DrMax.sk "Spýtajte sa lekárnika" section
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**Scraping Tools**: Scrapy, Playwright
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**Collection Date**: November 11, 2025
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## Usage
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### Loading the Dataset
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```python
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from datasets import load_dataset
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# Load the dataset
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dataset = load_dataset("your-username/drmax-pharmacy-qa")
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# View first example
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print(dataset['train'][0])
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```
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### Example: Question-Answer Retrieval
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```python
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from datasets import load_dataset
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dataset = load_dataset("your-username/drmax-pharmacy-qa")
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# Find all questions about headaches
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headache_qa = [
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item for item in dataset['train']
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if 'bolesť hlavy' in item['tags'] or 'migréna' in item['tags']
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]
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print(f"Found {len(headache_qa)} Q&A pairs about headaches")
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```
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### Example: Filter by Tags
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```python
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from datasets import load_dataset
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dataset = load_dataset("
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all_tags.update(item['tags'])
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print(f"Dataset contains {len(all_tags)} unique tags")
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print(f"Sample tags: {list(all_tags)[:10]}")
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```
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```python
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from datasets import load_dataset
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dataset = load_dataset("your-username/drmax-pharmacy-qa")
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# Prepare for instruction tuning
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def format_for_training(example):
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return {
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'instruction': example['question'],
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'response': example['answer'],
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'context': f"Tags: {', '.join(example['tags'])}"
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}
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training_data = dataset['train'].map(format_for_training)
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```
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## Dataset Card Contact
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For questions, issues, or suggestions regarding this dataset:
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- Open an issue on the source repository
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- Check the documentation at the repository
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---
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---
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annotations_creators:
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- expert-generated
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language_creators:
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- found
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language:
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- sk
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license: other
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multilinguality:
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- monolingual
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pretty_name: Demagog.sk Vyroky
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size_categories:
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- 10K<n<100K
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source_datasets:
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- original
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task_categories:
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- text-classification
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task_ids:
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- fact-checking
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---
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# Demagog.sk Vyroky
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## Dataset Description
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Demagog.sk Vyroky is a collection of fact-checked political statements scraped from [Demagog.sk](https://demagog.sk/vyroky). Each record contains the original claim, the speaker, the fact-check verdict, and the supporting analysis written by the Demagog.sk editorial team.
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- **Total examples:** 20495
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- **Latest scrape timestamp:** 2025-10-16T21:00:22.850424+00:00
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### Supported Tasks
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- **Fact-checking / claim verification:** predict the fact-check verdict (`verdict`) given the statement and optional context.
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- **Evidence summarisation:** leverage the `analysis_text` to train models that generate or evaluate fact-check rationales.
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- **Speaker and stance profiling:** analyse claims by political actor or party using the `speaker` and `speaker_party` fields.
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### Languages
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- Slovak (`sk`)
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## Data Splits
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| Split | Examples |
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| --- | --- |
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| train | 12297 |
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| validation | 4099 |
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| test | 4099 |
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## Data Fields
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- `id`: string identifier (usually the trailing portion of the vyrok URL).
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- `numeric_id`: numeric ID when available.
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- `url`: canonical Demagog.sk URL for the fact-check.
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- `statement`: verbatim political statement under review.
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- `speaker`: full name of the speaker.
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- `speaker_party`: political affiliation displayed on Demagog.sk.
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- `speaker_url`: link to the speaker profile on Demagog.sk.
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- `statement_date`: ISO date when the claim was made (if available).
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- `verdict`: fact-check verdict label in Slovak (e.g., `Pravda`, `Nepravda`).
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- `analysis_text`: editorial commentary summarising the evidence.
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- `analysis_paragraphs`: list of paragraphs extracted from the commentary.
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- `analysis_sources`: dictionary with `text` and `url` lists aligned per citation.
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- `analysis_date`: ISO date when the analysis was published (if available).
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- `scraped_at`: ISO timestamp when this dataset snapshot was collected.
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## Data Source and Collection Process
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- Statements and annotations originate from Demagog.sk fact-check articles.
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- The dataset is gathered via the public site API combined with HTML parsing of individual statement pages.
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- Verdict labels and commentary are authored by Demagog.sk fact-checkers.
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## Considerations for Use
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- Fact-check labels follow Demagog.sk taxonomy; users may wish to map them to English equivalents or merge classes for specific tasks.
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- Commentary text is written in Slovak; downstream tasks may require translation for non-Slovak models.
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- Verify licensing and usage policies of Demagog.sk before redistributing or deploying models trained on this dataset.
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## Citation
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If you use this dataset, please cite Demagog.sk and reference this repository. An example citation:
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> Demagog.sk. *Factcheck politických diskusií.* https://demagog.sk
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## Usage
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```python
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| 87 |
from datasets import load_dataset
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dataset = load_dataset("NaiveNeuron/DemagogSK", name="default")
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# For local files, replace the repo name with the path to this folder:
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| 91 |
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# dataset = load_dataset("path/to/demagogsk_vyroky", name="default")
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| 93 |
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train = dataset["train"]
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| 94 |
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validation = dataset["validation"]
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test = dataset["test"]
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| 96 |
```
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## License
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The dataset inherits the terms of use of Demagog.sk. Confirm permissions for your intended use case before redistribution.
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