The paper introduces BRAT, a web-based tool for text annotation supported by Natural Language Processing (NLP) technology. BRAT aims to enhance annotator productivity and maintain annotation quality through an intuitive user interface and the integration of NLP techniques. Key features include high-quality annotation visualization, an intuitive annotation interface, versatile annotation support, NLP technology integration, and corpus search functionality. The tool is implemented using a client-server architecture and is available under an open-source license. Case studies and an evaluation demonstrate that BRAT can reduce total annotation time by 15% through semantic class disambiguation, significantly improving efficiency in multi-category entity mention annotation tasks.The paper introduces BRAT, a web-based tool for text annotation supported by Natural Language Processing (NLP) technology. BRAT aims to enhance annotator productivity and maintain annotation quality through an intuitive user interface and the integration of NLP techniques. Key features include high-quality annotation visualization, an intuitive annotation interface, versatile annotation support, NLP technology integration, and corpus search functionality. The tool is implemented using a client-server architecture and is available under an open-source license. Case studies and an evaluation demonstrate that BRAT can reduce total annotation time by 15% through semantic class disambiguation, significantly improving efficiency in multi-category entity mention annotation tasks.