Adilbai/kz-rus-articles-comprehensive

🇰🇿🇷🇺 Kazakh-Russian Articles Comprehensive Dataset

A high-quality bilingual corpus for cross-lingual NLP research

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📋 Dataset Overview

The Kazakh-Russian Articles Comprehensive Dataset is a meticulously curated bilingual corpus designed to advance natural language processing research for Kazakh and Russian languages. This dataset addresses the critical need for high-quality parallel and comparable text resources in Central Asian language pairs, particularly supporting the development of machine translation, cross-lingual understanding, and multilingual language models.

🎯 Key Features

• Bilingual Coverage: Comprehensive articles in both Kazakh (kk) and Russian (ru)
• Domain Diversity: Multi-domain content spanning news, culture, technology, politics, and society
• High Quality: Professionally written articles with proper linguistic structure
• Research-Ready: Pre-processed and formatted for immediate use in NLP pipelines
• Cultural Context: Preserves cultural nuances and regional specificity

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🏗️ Dataset Structure

Data Fields

{
  "id": "unique_article_identifier",
  "language": "kk | ru",
  "title": "Article title",
  "content": "Full article text",
  "domain": "news | politics | culture | technology | sports | business | society | education",
  "publication_date": "YYYY-MM-DD",
  "source": "Source publication/website",
  "word_count": 000,
  "metadata": {
    "author": "Author name (if available)",
    "region": "Kazakhstan region/Russian region",
    "quality_score": 0.0-1.0
  }
}

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## 🔬 Research Applications

### Primary Use Cases

1. **🔄 Machine Translation**
   - Kazakh ↔ Russian translation model training
   - Cross-lingual transfer learning
   - Translation quality evaluation

2. **🌐 Cross-lingual NLP**
   - Multilingual language model pre-training
   - Cross-lingual text classification
   - Zero-shot learning across languages

3. **📝 Text Generation**
   - Kazakh text generation models
   - Style transfer between languages
   - Multilingual content creation

4. **🔍 Information Retrieval**
   - Cross-lingual document retrieval
   - Multilingual search systems
   - Question answering in both languages

### Research Areas

- **Computational Linguistics**: Morphological analysis, syntactic parsing
- **Sociolinguistics**: Language contact and bilingual text analysis  
- **Digital Humanities**: Cultural and historical text analysis
- **Language Technology**: Speech recognition, text-to-speech systems

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## 🛠️ Usage Instructions

### Quick Start

```python
from datasets import load_dataset

# Load the full dataset
dataset = load_dataset("Adilbai/kz-rus-articles-comprehensive")

# Load specific split
train_data = load_dataset("Adilbai/kz-rus-articles-comprehensive", split="train")

# Filter by language
kazakh_articles = dataset.filter(lambda x: x["language"] == "kk")
russian_articles = dataset.filter(lambda x: x["language"] == "ru")

# Filter by domain
news_articles = dataset.filter(lambda x: x["domain"] == "news")

Data Processing Example

import pandas as pd
from datasets import load_dataset

# Load and convert to pandas
dataset = load_dataset("Adilbai/kz-rus-articles-comprehensive")
df = dataset["train"].to_pandas()

# Basic statistics
print(f"Total articles: {len(df)}")
print(f"Average word count: {df['word_count'].mean():.1f}")
print(f"Language distribution:\n{df['language'].value_counts()}")
print(f"Domain distribution:\n{df['domain'].value_counts()}")

# Quality filtering
high_quality = df[df['metadata'].apply(lambda x: x['quality_score'] > 0.8)]
print(f"High-quality articles: {len(high_quality)}")

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🎓 Academic Usage

Citation

If you use this dataset in your research, please cite:

@dataset{adilbai2024kazakh_russian_articles,
  title={Kazakh-Russian Articles Comprehensive Dataset},
  author={Adilbai, [First Name]},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/Adilbai/kz-rus-articles-comprehensive},
  note={A comprehensive bilingual corpus for Kazakh-Russian NLP research}
}

Related Publications

[Add relevant publications and papers that used this dataset]

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📏 Data Quality & Preprocessing

Quality Assurance

• Language Detection: Automatic language identification with manual verification
• Content Filtering: Removal of duplicates, spam, and low-quality content
• Format Standardization: Consistent text encoding and structure
• Metadata Validation: Verified publication dates and source information

Preprocessing Steps

1. Text Cleaning: Removal of HTML tags, special characters, and formatting artifacts
2. Language Verification: Multi-stage language detection and validation
3. Deduplication: Content-based duplicate detection and removal
4. Quality Scoring: Automated quality assessment based on linguistic features
5. Metadata Enrichment: Addition of word counts, readability scores, and domain labels

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⚖️ Ethical Considerations & Limitations

Ethical Guidelines

• Copyright Compliance: All content used with proper attribution and licensing
• Privacy Protection: Personal information removed or anonymized
• Cultural Sensitivity: Respectful representation of both Kazakh and Russian cultures
• Bias Awareness: Acknowledgment of potential linguistic and cultural biases

Known Limitations

• Temporal Coverage: Limited to articles from 2020-2024
• Genre Bias: Primarily news and journalistic content
• Regional Variation: May not represent all dialectal variations
• Translation Quality: Not all content has parallel translations
• Domain Balance: Some domains may be underrepresented

Bias Considerations

• Source Diversity: Efforts made to include diverse publication sources
• Geographic Coverage: Balanced representation across Kazakhstan and Russia
• Topical Balance: Multiple domains included to reduce subject bias
• Language Variety: Inclusion of both formal and semi-formal registers

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📞 Contact & Support

Dataset Maintainer

• Name: [Baidalin Adilzhan]
• Email: [[email protected]]

Community & Support

• Issues: Report bugs and request features on the dataset page
• Discussions: Join the community discussion forum
• Updates: Follow for dataset updates and announcements

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📝 Changelog

Version 1.0 (2024-XX-XX)

• Initial release of the comprehensive dataset
• XX,XXX articles across 8 domains
• Complete metadata and quality scoring

Future Releases

• Addition of parallel translation pairs
• Expansion to include social media content
• Integration of audio/video transcripts
• Enhanced metadata with linguistic annotations

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🤝 Contributing

We welcome contributions to improve and expand this dataset! Please see our contribution guidelines for:

• Data Contributions: Adding new articles or domains
• Quality Improvements: Reporting and fixing data quality issues
• Metadata Enhancements: Adding linguistic annotations
• Documentation: Improving dataset documentation

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🙏 Acknowledgments

This dataset was created with support from:

• [List relevant institutions, grants, or organizations]
• The Kazakh and Russian NLP research communities
• Contributors who provided data and feedback

Special thanks to the journalists and authors whose work is represented in this corpus.

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🌟 Star this dataset if you find it useful for your research! 🌟