AWED-FiNER: 基于代理、网络应用和专家检测器的细粒度命名实体识别工具，支持36种语言，覆盖66亿使用者
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
AI总结：
AWED-FiNER提供支持36种语言的细粒度命名实体识别解决方案，包含代理工具、网络应用及53种先进专家模型，适用于多语言和低资源场景。
摘要：
命名实体识别（NER）是自然语言处理（NLP）和信息检索（IR）中的基础任务，它有助于语义搜索和结构化数据提取。我们介绍了AWED-FiNER，这是一个开源的代理工具、网络应用和53种最先进的专家模型的集合，提供细粒度命名实体识别（FgNER）解决方案，覆盖超过66亿使用者的36种语言。代理工具能够将多语言文本路由到专门的专家模型，以在几秒钟内获取FgNER注释。基于网络的平台为非技术用户提供了即用型FgNER注释服务。此外，语言特定的极小开源最先进的专家模型集合促进了在资源受限场景下的离线部署，包括边缘设备。AWED-FiNER涵盖的语言包括全球语言如英语、中文、西班牙语和印地语，以及低资源语言如阿萨姆语、桑塔利语和奥里亚语，同时特别关注极低资源的脆弱语言，如波多语、梅顿语、比什努普里亚语和米佐语。这些资源可以在此处访问：代理工具（https://github.com/PrachuryyaKaushik/AWED-FiNER）、网络应用（https://hf.co/spaces/prachuryyaIITG/AWED-FiNER）以及53个专家检测器模型（https://hf.co/collections/prachuryyaIITG/awed-finer）
英文摘要：
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-PIPER, an open-source framework comprising agentic tools, interactive web applications, and 54 state-of-the-art expert detector models that provide unified Fine-grained Named Entity Recognition (FgNER) and reversible synthetic PII pseudonymization across 36 languages spoken by over 6.6 billion people. The system couples fine-grained multilingual sequence labeling with script-aware regex detectors to identify contextual entities (Person, Location, Organization, Medical) as well as structured technical PII (Emails, native-script Phone Numbers, IP Addresses, Credit Cards). AWED-PIPER offers a dual capability: full FgNER entity extraction and privacy-preserving reversible anonymization with persistent placeholders and de-anonymization dictionary mappings. The suite spans global languages to extremely low-resource vulnerable languages like Bodo, Manipuri, Bishnupriya, and Mizo. The resources can be accessed here: PII Protector Agentic Tool: (https://github.com/PrachuryyaKaushik/AWED-PIPER), FgNER Agentic Tool: (https://github.com/PrachuryyaKaushik/AWED-FiNER), PII Web Application: (https://hf.co/spaces/prachuryyaIITG/AWED_PII_Protector), FgNER Web Application: (https://hf.co/spaces/prachuryyaIITG/AWED-FiNER), and Edge-deployable Expert Detector Models: (https://hf.co/collections/prachuryyaIITG/awed-piper).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
