metadata

license: apache-2.0
task_categories:
  - text-classification
tags:
  - text-moderation
language:
  - en
  - de
  - fr
  - es
  - it
  - sv
  - fi
  - pl
  - cs
  - lv
  - zh
  - ja
  - ko
  - ru
  - uk
  - be
  - kk

Text-Moderation-Multilingual

A comprehensive multilingual text moderation dataset combining multiple high-quality sources for training robust content moderation classifiers.

Dataset Summary

This dataset aggregates text moderation data from multiple sources to create a large-scale, diverse training corpus for content moderation systems. It includes text samples labeled across multiple harmful content categories, supporting both multilingual and English-specific moderation use cases.

Total Size: ~1.7M entries
Languages: Multilingual (primary focus on English)
Task: Multi-label text classification for content moderation

Dataset Structure

Data Fields

prompt (string): The input text to be classified
S (int): Sexual content (0 = safe, 1 = harmful)
H (int): Hate speech (0 = safe, 1 = harmful)
V (int): Violence (0 = safe, 1 = harmful)
HR (int): Harassment (0 = safe, 1 = harmful)
SH (int): Self-harm (0 = safe, 1 = harmful)
S3 (int): Sexual content involving minors (0 = safe, 1 = harmful)
H2 (int): Hate speech (alternative labeling) (0 = safe, 1 = harmful)
V2 (int): Violence (alternative labeling) (0 = safe, 1 = harmful)

Data Splits

Train: 1459350 samples
Validation: 162150 samples

Note: Split created with 90/10 train/validation ratio using random seed 42

Source Datasets

This dataset combines and harmonizes data from:

ifmain's multilingual dataset - Multilingual moderation examples
OpenAI's English evaluation dataset - High-quality English evaluation samples
ifmain's English dataset - English moderation examples

Intended Use

Primary Use Cases

Training text moderation classifiers
Benchmarking content moderation systems
Research into automated content moderation
Multi-label classification model development

Out-of-Scope Uses

This dataset is not intended for any purpose other than training content moderation systems
Should not be used to generate harmful content
Not suitable for general text classification tasks outside of moderation

Considerations for Using the Data

Content Warning

This dataset contains examples of harmful content including hate speech, harassment, violence, and other potentially disturbing material. Users should exercise appropriate caution when working with this data.

Bias and Limitations

The dataset reflects the biases present in the source datasets
Content moderation standards may vary across different platforms and cultures
Label consistency across merged datasets may vary
Primarily English-focused despite multilingual components

Ethical Considerations

This dataset should only be used to improve content moderation and safety systems
Researchers and developers should implement appropriate safeguards when working with this data
The goal is to reduce harmful content online, not to amplify it

Example Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("KoalaAI/Text-Moderation-Multilingual")

# Access splits
train_data = dataset["train"]
val_data = dataset["validation"]

# Example entry
print(train_data[0])
# {
#   'prompt': 'Example text...',
#   'S': 0, 'H': 0, 'V': 0, 'HR': 0, 
#   'SH': 0, 'S3': 0, 'H2': 0, 'V2': 0
# }

Dataset Creation

Curation Process

Source datasets were identified and downloaded
Data was harmonized to use consistent labeling schema
Entries were merged and deduplicated where appropriate
Train/validation split was created using stratified sampling

Quality Control

Labels were preserved from original high-quality sources
Data integrity checks were performed during merging process
Consistent schema applied across all entries

License

Please refer to the licenses of the individual source datasets:

Check ifmain datasets for their respective licensing terms
OpenAI evaluation dataset licensing applies to that portion
Usage should comply with all source dataset requirements

Citation

If you use this dataset, please cite the original source datasets:

@misc{text-moderation-large,
  title={Text-Moderation-Multilingual: A Multilingual Text Moderation Dataset},
  author={[KoalaAI]},
  year={2025},
  note={Aggregated from ifmain's and OpenAI's moderation datasets}
}

Contact

For questions about this dataset compilation, please open an issue on this repository.

Disclaimer: This dataset is provided for research and safety purposes only. Users are responsible for ensuring ethical use and compliance with applicable laws and regulations.