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Protegrity-PII Technical Report

A technical report submitted to arXiv on 21 October 2026 presents Protegrity-PII, a new PII decision model for structured and unstructured text that achieves a typed recall of 0.915 with a precision of 0.907 on PII-SCOPE, a new benchmark the authors propose. The model processes text at 0.49 seconds per million characters at $0.0005 per million characters on a single RTX 6000 using batched inference, and the authors report superior out-of-distribution generalization against a selection of state-of-the-art models and datasets, attributed in part to the expansive entity type taxonomy used in training.

by read1 min views2 publishedOct 23, 2026
Protegrity-PII Technical Report
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  [Submitted on 21 Oct 2026]


[View PDF](https://arxiv.org/pdf/2610.30518)

[HTML (experimental)](https://arxiv.org/html/2610.30518v1)

Abstract:We present Protegrity-PII, a new PII decision model for structured and unstructured text. Protegrity-PII achieves a typed recall of 0.915 with a precision of 0.907 on a new benchmark we propose, PII-SCOPE. Our model processes text in 0.49 seconds per million characters at $0.0005 per million characters on a single RTX 6000 using batched inference. Due in part to the expansive nature of the entity type taxonomy used in training, Protegrity-PII achieves superior out-of-distribution generalization when benchmarked against a selection of state of the art models and datasets.

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