id stringlengths 2 6 | title stringlengths 1 110 | text stringlengths 200 567k | url stringlengths 31 140 | timestamp stringdate 2025-04-05 18:25:13 2025-04-05 20:21:55 |
|---|---|---|---|---|
12 | Anarchism | {{Short description|Political philosophy and movement}}
{{Other uses|Anarchy|Anarchism (disambiguation)|Anarchist (disambiguation)}}
{{Good article}}
{{Pp-semi-indef}}
{{Use British English|date=August 2021}}
{{Use dmy dates|date=October 2024}}
{{Use shortened footnotes|date=May 2023}}
{{Anarchism sidebar}}
Anarchism ... | https://en.wikipedia.org/wiki/Anarchism | 2025-04-05T18:25:13.545598 |
39 | Albedo | {{Short description|Ratio of how much light is reflected back from a body}}
{{Other uses}}
{{Use dmy dates|date=September 2019}}
: the map shows the difference between the amount of sunlight Greenland reflected in the summer of 2011 versus the average percent it reflected between 2000 and 2006. Some areas reflect close... | https://en.wikipedia.org/wiki/Albedo | 2025-04-05T18:25:14.057726 |
290 | A | "{{Short description|First letter of the Latin alphabet}}\n{{About|the Latin letter|the similar Gree(...TRUNCATED) | https://en.wikipedia.org/wiki/A | 2025-04-05T18:25:15.113626 |
303 | Alabama | "{{Short description|U.S. state}}\n{{hatnote group|{{for|the river of the same name|Alabama River}}{(...TRUNCATED) | https://en.wikipedia.org/wiki/Alabama | 2025-04-05T18:25:15.429504 |
305 | Achilles | "{{Short description|Greek mythological hero}}\n{{Redirect|Achilleus|the Roman usurper with this nam(...TRUNCATED) | https://en.wikipedia.org/wiki/Achilles | 2025-04-05T18:25:15.526526 |
307 | Abraham Lincoln | "{{Short description|President of the United States from 1861 to 1865}}\n{{Other uses}}\n{{redirect|(...TRUNCATED) | https://en.wikipedia.org/wiki/Abraham_Lincoln | 2025-04-05T18:25:15.694491 |
308 | Aristotle | "{{Short description|Ancient Greek philosopher and polymath (384–322 BC)}}\n{{Other uses}}\n{{Good(...TRUNCATED) | https://en.wikipedia.org/wiki/Aristotle | 2025-04-05T18:25:15.848419 |
309 | An American in Paris | "{{short description|1928 composition by George Gershwin}}\n{{About|the 1928 George Gershwin composi(...TRUNCATED) | https://en.wikipedia.org/wiki/An_American_in_Paris | 2025-04-05T18:25:15.896555 |
316 | Academy Award for Best Production Design | "{{Short description|Academy Award which recognizes achievement for art direction in film}}\n{{Use m(...TRUNCATED) | https://en.wikipedia.org/wiki/Academy_Award_for_Best_Production_Design | 2025-04-05T18:25:16.124888 |
324 | Academy Awards | "{{Short description|Annual awards for cinematic achievements}}\n{{pp-move}}\n{{Redirect-multi|2|Osc(...TRUNCATED) | https://en.wikipedia.org/wiki/Academy_Awards | 2025-04-05T18:25:16.342862 |
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TreeCorpus
TreeCorpus is a comprehensive, structured dataset derived from the latest Wikipedia dumps, specially processed to serve as high-quality training data for conversational AI models. This dataset transforms Wikipedia's encyclopedic knowledge into a format optimized for natural language understanding and generation tasks.
Dataset Statistics
- Size: 26.27 GB (26,272,580,250 bytes)
- Examples: 2,882,766 articles
- Download Size: 13.33 GB (13,326,529,312 bytes)
- Language: English
Data Structure
Each entry in the dataset contains:
id(string): Unique Wikipedia article identifiertitle(string): Article titletext(string): Clean, processed text contenturl(string): Source Wikipedia URLtimestamp(string): Processing timestamp
Key Features
- Clean, Structured Content: Meticulously processed to remove markup, templates, references, and other non-content elements while preserving the informational value of Wikipedia articles.
- Rich Metadata: Each entry includes article ID, title, clean text content, source URL, and timestamp.
- Comprehensive Coverage: Incorporates the full spectrum of Wikipedia's knowledge base, spanning nearly 3 million articles across countless topics.
- Conversational Optimization: Content is processed specifically to support training of dialogue systems, conversational agents, and knowledge-grounded language models.
- Regular Updates: Built from the latest Wikipedia dumps to ensure current information.
Usage
This dataset is ideal for:
- Training large language models requiring broad knowledge bases
- Fine-tuning conversational agents for knowledge-intensive tasks
- Question-answering systems that need factual grounding
- Research in knowledge representation and retrieval in natural language
License and Citation
TreeCorpus is derived from Wikipedia content available under the CC BY-SA 3.0 license. When using this dataset, please provide appropriate attribution to both this dataset and Wikipedia.
Dataset Configuration
The dataset is configured with a default split:
- Split name: train
- Data files pattern: data/train-*
Creation Process
TreeCorpus was created using a specialized pipeline that:
- Downloads the latest Wikipedia dumps
- Processes XML content to extract articles
- Cleans and standardizes text by removing markup, templates, and non-content elements
- Structures data in a consistent, machine-readable format
- Filters out redirects, stubs, and non-article content
For more details on the methodology and processing pipeline, please see the accompanying code documentation.
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