NameTag 3支持多语言多数据集命名实体识别，无需安装即可使用。
NameTag 3: A Tool and a Service for Multilingual/Multitagset NER
- 基于单一355M参数模型实现跨语言、跨数据集的平铺与嵌套实体识别
- 在15种语言21个数据集上达到顶尖性能，部分任务优于更大模型
- 提供免安装云端服务，适合急需多语言文本标注的研究者和开发者
我们介绍NameTag 3，一个开源工具与云服务平台，支持多语言、多数据集、多标签体系的命名实体识别（NER），涵盖平铺与嵌套实体。该系统在15种语言的21个测试数据集上达到最先进水平，且在其余任务中仍保持竞争力，甚至优于更大模型。其云端服务提供17种语言的平铺NER，基于21个语料库与3种实体标签体系训练，由单一355M参数微调模型驱动；捷克语嵌套NER则由126M参数模型支持。源代码采用MPL 2.0开源许可，模型为非商业性CC BY-NC-SA 4.0授权。文档见https://ufal.mff.cuni.cz/nametag，源码在https://github.com/ufal/nametag3，训练模型通过https://lindat.cz获取。REST服务与网页应用地址为https://lindat.mff.cuni.cz/services/nametag/，演示视频见https://www.youtube.com/watch?v=-gaGnP0IV8A。
原文摘要 · Abstract (English)
We introduce NameTag 3, an open-source tool and cloud-based web service for multilingual, multidataset, and multitagset named entity recognition (NER), supporting both flat and nested entities. NameTag 3 achieves state-of-the-art results on 21 test datasets in 15 languages and remains competitive on the rest, even against larger models. It is available as a command-line tool and as a cloud-based service, enabling use without local installation. NameTag 3 web service currently provides flat NER for 17 languages, trained on 21 corpora and three NE tagsets, all powered by a single 355M-parameter fine-tuned model; and nested NER for Czech, powered by a 126M fine-tuned model. The source code is licensed under open-source MPL 2.0, while the models are distributed under non-commercial CC BY-NC-SA 4.0. Documentation is available at https://ufal.mff.cuni.cz/nametag, source code at https://github.com/ufal/nametag3, and trained models via https://lindat.cz. The REST service and the web application can be found at https://lindat.mff.cuni.cz/services/nametag/. A demonstration video is available at https://www.youtube.com/watch?v=-gaGnP0IV8A.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。