tanaos/synthetic-text-anonymizer-dataset-v1

🥸 Tanaos Text Anonymizer Training Dataset

This dataset was created synthetically by Tanaos with the Artifex Python library.

The dataset is designed to train and evaluate Named Entity Recognition systems for Text Anonymization — models that can identify and redact Personally Identifiable Information (PII) from text.

Our flagship Text Anonymizer model, tanaos-text-anonymizer-v1, was trained on this dataset.

📖 Dataset Summary

The dataset contains text samples labeled with named entity tags. Each sample consists of a sentence or paragraph with entities annotated, word-by-word, according to the following categories:

Entity	Description
O	No entity is present
PERSON	Individual people, fictional characters
LOCATION	Geographical areas
DATE	Absolute or relative dates, including years, months and/or days
ADDRESS	Full addresses
PHONE_NUMBER	Telephone numbers

Punctuation and special characters are not labeled.

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⚙️ How to Use

from datasets import load_dataset

dataset = load_dataset("tanaos/synthetic-text-anonymizer-dataset-v1")

print(dataset["train"][0])

🧠 Intended Use

This dataset is meant for training, fine-tuning, and evaluating Named Entity Recognition models for Text Anonymization.

Common use cases:

• Developing models to automatically redact PII from text data.
• Benchmarking the performance of Text Anonymization systems.
• Researching techniques for improving NER and PII detection.