---
id: 20261025-T0-08
title: "Protegrity-PII模型：结构化与非结构化文本PII识别精确率0.907、召回率0.915"
title_en: "Protegrity-PII Model Hits 0.907 Precision, 0.915 Typed Recall on New PII Benchmark"
url: https://ai.daily.yangsir.net/daily/20261025-T0-08
issue_date: 2026-10-25
publish_date: 2026-10-24T04:00:00.000Z
category: research
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2610.30518
---

# Protegrity-PII模型：结构化与非结构化文本PII识别精确率0.907、召回率0.915

Protegrity发布PII判定模型Protegrity-PII，用于识别结构化和非结构化文本中的个人身份信息。在新提出的PII-SCOPE基准上，该模型的类型化召回率为0.915、精确率为0.907，单条文本处理耗时0.49秒。团队同时公开了PII-SCOPE评测集。对企业的直接影响是：可将其用于日志脱敏、客服对话审查等场景，在秒级延迟下兼顾查全与查准。

## English Version

**Protegrity-PII Model Hits 0.907 Precision, 0.915 Typed Recall on New PII Benchmark**

Protegrity presents Protegrity-PII, a decision model for detecting personally identifiable information in structured and unstructured text. On PII-SCOPE, a new benchmark the team proposes, the model reaches 0.915 typed recall and 0.907 precision while processing text at 0.49 seconds per item. The benchmark is released alongside the model. For enterprises, this means faster, more balanced PII detection in use cases such as log redaction and customer-service transcript review.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2610.30518)

**详情页**：https://ai.daily.yangsir.net/daily/20261025-T0-08

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