BBC news data

The BBC News dataset provides a rich collection of real-world news articles spanning multiple categories like politics, health, tech, and more. Designed for advanced NLP and AI applications, it includes titles, publication dates, article summaries, and clean body text in CSV format. Ideal for tasks such as text classification, news summarization, fake news detection, headline generation, and fine-tuning language models.

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BBC news data
Multi-Source Coverage

Data aggregated from multiple credible sources: BBC, The Guardian, Sky News, Le Monde, ABC News, Al Jazeera, and more.

Editorial-Grade Language

Written and edited by professional journalists, ideal for fine-tuning language models with factual, structured writing.

Cross-National Perspective

News from UK, Australia, Europe, and Middle East — perfect for training globally aware models.

Article-Level Structuring

Each row includes article title, summary, body text, author, publication time, language, and section/category.

Multilingual Readiness

Supports English, French, German, and Arabic with optional translation mapping fields.

Summarization-Ready

Clean summary (standfirst) fields present in many articles to support summarization tasks.

Topic Richness

Includes major categories like health, science, politics, climate, world, technology, and culture.

Ready for LLMs

Formatted to feed into large language models for retrieval-augmented generation, prompt-tuning, or classification.

Dataset Pricing

Choose the tier that fits your needs - flexible pricing for all project sizes

Select Dataset Size

500 K 1 M 2 M
What's included:
  • Clean, structured data
  • Multiple format options (CSV, JSON)
  • Instant download access
  • Commercial use license
Your Selection
Records: 500,000
Price: $800.0
Secure payment • Instant access

Bbc News_data Dataset FAQs

BBC, The Guardian, Al Jazeera, Sky News, The Times (UK), ABC News (AU), Le Monde, Deutsche Welle, and others.

Yes, it includes English, French, German, and Arabic articles with optional language labels.

Each record includes the title, summary, body text, language, published date, author (if available), and URL.

Yes, we can provide filtered datasets by category, keyword, or time range.

Absolutely. The quality and structure are ideal for model training, classification, QA, and summarization tasks.

Depending on the range, 500K to 2M articles can be extracted depending on date and source filters.

Yes. We maintain a scraping and refresh pipeline for all major sources, updated weekly or monthly.

They are written by journalists in the source articles, not generated synthetically.

Yes. Most sources include category tags (e.g., World, Tech, Health), aiding in classification and training.

CSV, JSONL, and JSON formats are supported for use in Spark, Python, and cloud data pipelines.