发表机构
BiometricsAI, Universidad Autónoma de Madrid (UAM)（生物识别人工智能公司，马德里自治大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
介绍CrimeNER演示平台，可从文档提取犯罪相关信息并分类。提供预训练模型，用户能提供数据微调。包括预训练模型、微调功能及自动提取管道，旨在推动研究，为相关机构提供实用工具，相关内容可在GitHub获取。
AI 中文摘要
我们展示了CrimeNER演示，这是一个由人工智能驱动的平台，能够从文档中提取一般犯罪相关信息，并将其分类为具有两个粒度级别的实体类型。我们在CrimeNER数据库上提供预训练的NER模型，还允许用户提供自己的注释数据来训练针对特定案例的模型。该演示旨在促进犯罪相关的NER研究，并为研究人员和执法机构提供自动提取犯罪信息的实用工具。该演示包括：犯罪领域的预训练NER模型；根据用户注释的特定数据微调模型的可能性；以及从文档中提取和注释犯罪实体的自动管道。演示平台、运行演示的教程和视频演示可在GitHub上公开获取。
英文摘要
We present CrimeNER Demo, an AI-powered platform that enables us to extract general crime-related information from documents and classify them into entity types with two levels of granularity. We provide pretrained NER models on the CrimeNER database, and we give the possibility to users to provide their own annotated data to train models for their own specific cases. This demonstrator aims to promote crime-related NER research and provides a practical tool to automatically extract crime information for researchers and law enforcement agencies. The demonstrator includes: i) Pretrained NER models on the crime domain; ii) Possibility to finetune the models on specific data annotated by the user; and iii) An automatic pipeline to extract and annotate crime entities from documents. The demo platform, a tutorial to run the demo, and a video demonstration are publicly available on GitHub.
Comments6 pages, 2 figures, IAPR Intl. Conf. on Document Analysis and Recognition Workshops (ICDARw), 2026
