metadata

language:
  - en
license: cc-by-sa-3.0
tags:
  - treecorpus
  - treecorpuscleaned
  - wikipedia
  - encyclopedia
  - knowledge-base
  - factual-knowledge
  - training-data
  - conversational-ai
  - nlp
  - language-model
  - text-corpus
  - qa-dataset
  - structured-data
  - clean-text
pretty_name: 'TreeCorpusCleaned: Basic Wikipedia Text Cleanup for AI Models'
size_categories:
  - 10M<n<100M

TreeCorpusCleaned

TreeCorpusCleaned is a modestly improved version of the TreeCorpus dataset with some additional basic cleaning to help reduce Wikipedia markup artifacts. This dataset provides a slightly cleaner version of Wikipedia content for training AI models.

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 identifier
title (string): Article title
text (string): Text with basic additional cleanup
url (string): Source Wikipedia URL
timestamp (string): Processing timestamp

Basic Additional Cleaning

TreeCorpusCleaned includes some simple improvements over the original TreeCorpus:

Basic Reference Cleanup: Additional removal of common reference markers
Simple Template Handling: Some extra template cleanup
Formatting Standardization: Basic text formatting standardization

Usage

This dataset is suitable for:

Training language models with slightly cleaner Wikipedia text
NLP tasks that benefit from reduced markup artifacts
Projects requiring basic preprocessing of Wikipedia content

License and Citation

TreeCorpusCleaned 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

TreeCorpusCleaned was created by applying some additional basic cleaning steps to the original TreeCorpus dataset to remove common artifacts and improve text quality.