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New AWED-PIPER framework offers FgNER and PII anonymization across 36 languages

By PulseAugur Editorial · [1 sources] ·

Researchers have developed AWED-PIPER, an open-source framework designed for fine-grained Named Entity Recognition (FgNER) and Personally Identifiable Information (PII) anonymization. This system integrates agentic tools, web applications, and 54 expert detector models to support 36 languages. AWED-PIPER can identify contextual entities like people and locations, as well as technical PII such as emails and phone numbers, offering both extraction and reversible anonymization capabilities. The framework is notable for its extensive language support, including extremely low-resource languages. AI

IMPACT Enhances information extraction and privacy preservation capabilities across a wide range of languages, including low-resource ones.

RANK_REASON The cluster contains a research paper detailing a new framework for NLP tasks. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New AWED-PIPER framework offers FgNER and PII anonymization across 36 languages

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The cluster contains a research paper detailing a new framework for NLP tasks. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Prachuryya Kaushik, Ashish Anand ·

    AWED-PIPER: Agents, Web Applications & Expert Detectors for Personally Identifiable Information Protection & Fine-grained Named Entity Recognition across 36 languages for 6.6 Billion Speakers

    arXiv:2601.10161v3 Announce Type: replace-cross Abstract: Named Entity Recognition (NER) and Personally Identifiable Information (PII) anonymization are critical tasks in Natural Language Processing (NLP) for information extraction and privacy preservation. We introduce AWED-PIPE…

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