Pli Masking 100K: A Preview of Personal Location Information Anonymization Data

400 text samples demonstrate the structure and labeling for identifying and masking sensitive location information. This preview is representative of a commercial dataset containing over 100,000 entries, created by ai4privacy. The dataset page was last updated on April 4, -2026.

Use Cases

• Train named entity recognition models to detect personal location information in text.
• Develop and test text masking or redaction algorithms for privacy compliance.
• Benchmark the performance of privacy-enhancing technologies on location-based entities.
• Create synthetic training data for anonymization tasks based on the demonstrated label taxonomy.

Strengths

• Preview of 400 samples allows for initial assessment of data structure and quality.
• Based on a full dataset containing over 100,000 entries, suggesting substantial scale.
• Specialized focus on personal location information (PLI) for a targeted use case.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the full dataset is not explicitly confirmed, only estimated as '100,000+'.

Provenance

Source

ai4privacy

Collection Method

Likely annotated text data for identifying and masking personal location information.

Time Range

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Freshness

Last updated 2026-04-04 16:19:02; freshness should be verified.

Geography

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