Datasets:

JulianKrgd
/

wikipedia-en-julian

title stringclasses 1 value	text stringlengths 155 353k	url stringclasses 1 value	language stringclasses 1 value
	Anarchism is a political philosophy and movement that is skeptical of all justifications for authority and seeks to abolish the institutions it claims maintain unnecessary coercion and hierarchy, typically including nation-states, and capitalism. Anarchism advocates for the replacement of the state with stateless socie...		en
	Albedo (; ) is the fraction of sunlight that is diffusely reflected by a body. It is measured on a scale from 0 (corresponding to a black body that absorbs all incident radiation) to 1 (corresponding to a body that reflects all incident radiation). Surface albedo is defined as the ratio of radiosity Je to the irradian...		en
	A, or a, is the first letter and the first vowel of the Latin alphabet, used in the modern English alphabet, the alphabets of other western European languages and others worldwide. Its name in English is a (pronounced ), plural aes. It is similar in shape to the Ancient Greek letter Alpha, from which it derives. The up...		en
	Alabama () is a state in the Southeastern region of the United States, bordered by Tennessee to the north; Georgia to the east; Florida and the Gulf of Mexico to the south; and Mississippi to the west. Alabama is the 30th largest by area and the 24th-most populous of the U.S. states. Alabama is nicknamed the Yellowham...		en
	"In Greek mythology, Achilles ( ) or Achilleus () was a hero of the Trojan War who was known as bein(...TRUNCATED)		en
	"Abraham Lincoln ( ; February 12, 1809 – April 15, 1865) was an American lawyer, politician, and s(...TRUNCATED)		en
	"Aristotle (; Aristotélēs, ; 384–322 BC) was an Ancient Greek philosopher and polymath. His writ(...TRUNCATED)		en
	"An American in Paris is a jazz-influenced symphonic poem (or tone poem) for orchestra by American c(...TRUNCATED)		en
	"The Academy Award for Best Production Design recognizes achievement for art direction in film. The (...TRUNCATED)		en
	"The Academy Awards, mainly known as the Oscars, are awards for artistic and technical merit for the(...TRUNCATED)		en

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Wikipedia English - JULIAN Training Dataset

This dataset contains cleaned English Wikipedia articles used to train the JULIAN-100M language model.

Dataset Structure

Data Fields

title (string): Article title
text (string): Full article text (cleaned and formatted)
url (string): Original Wikipedia URL
language (string): Language code ("en")

Data Example

{
  "title": "Artificial Intelligence",
  "text": "Artificial intelligence (AI) is intelligence demonstrated by machines...",
  "url": "https://en.wikipedia.org/wiki/Artificial_Intelligence",
  "language": "en"
}

Data Collection

Source

Downloaded from Wikimedia dumps (English Wikipedia).

Processing Pipeline

Download: Latest Wikipedia XML dump
Extraction: Parse XML, extract article text
Cleaning:
- Remove Wiki markup and templates
- Remove infoboxes and navigation elements
- Clean HTML entities and special characters
- Remove very short articles (<50 characters)
- Remove duplicate content
Filtering:
- Keep only main namespace articles
- Remove disambiguation and redirect pages
- Filter low-quality content
Formatting: Convert to JSONL with structured fields

Statistics

Metric	Value
Total Articles	~6.5 million
Total Tokens	~3.5 billion
Average Article Length	~540 tokens
Total Characters	~21 billion

Usage

Loading with Datasets Library

from datasets import load_dataset

# Load full dataset
dataset = load_dataset("juliankerignard/wikipedia-en-julian", split="train")

# Stream for large datasets
dataset = load_dataset("juliankerignard/wikipedia-en-julian", split="train", streaming=True)

# Example: Get first article
print(dataset[0]['title'])
print(dataset[0]['text'][:200])

Training Example

from datasets import load_dataset
import sentencepiece as spm

# Load dataset
dataset = load_dataset("juliankerignard/wikipedia-en-julian", split="train", streaming=True)

# Load tokenizer
tokenizer = spm.SentencePieceProcessor()
tokenizer.Load("julian_24k.model")

# Tokenize and prepare for training
def tokenize_function(examples):
    return {"input_ids": tokenizer.EncodeAsIds(examples["text"])}

tokenized_dataset = dataset.map(tokenize_function, batched=True)

Limitations and Bias

Limitations

Wikipedia Bias: Reflects Wikipedia's editorial policies and contributor demographics
Coverage Gaps: Some topics are over-represented (technology, Western culture), others under-represented
Temporal Snapshot: Knowledge is frozen at the time of the dump
Style Homogeneity: Encyclopedia writing style, not conversational or creative writing

Potential Biases

Geographic: English Wikipedia has more coverage of English-speaking countries
Demographic: Reflects Wikipedia editor demographics (primarily male, Western)
Topic: Technology and pop culture are over-represented vs. non-Western topics
Recency: Recent events have more coverage than historical topics

Ethical Considerations

Contains encyclopedic content, which may include sensitive topics
Not suitable for training models to be used in high-stakes decision making
Users should be aware of Wikipedia's known biases when using this dataset
Recommended for research and educational purposes

License

This dataset is derived from Wikipedia content, which is licensed under:

Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0)
GNU Free Documentation License (GFDL)

See Wikipedia's copyright policy for details.

Citation

If you use this dataset, please cite:

@misc{julian_wikipedia_en_2025,
  title={Wikipedia English - JULIAN Training Dataset},
  author={Julian Kerignard},
  year={2025},
  howpublished={\\url{https://huggingface.co/datasets/juliankerignard/wikipedia-en-julian}},
  note={Derived from English Wikipedia dumps}
}

Also cite the original Wikipedia content:

@misc{wikipedia_en,
  author = "{Wikipedia contributors}",
  title = "English Wikipedia",
  year = "2025",
  howpublished = {\\url{https://en.wikipedia.org/}},
  note = "[Online; accessed DATE]"
}

Related Resources

Model: JULIAN-100M - Trained on this dataset
French Dataset: wikipedia-fr-julian
Tokenizer: Included in JULIAN-100M model repository

Contact

Author: Julian Kerignard
HuggingFace: https://huggingface.co/juliankerignard

Note: This is a research dataset created for training the JULIAN-100M language model. For the latest Wikipedia content, please visit wikipedia.org.