Manually annotated data is key to developing textmining and information-extraction algorithms. However, human annotation requires considerable time, effort and expertise. Given the rapid growth of biomedical literature, it is paramount to build tools that facilitate speed and maintain expert quality. While existing text annotation tools may provide user-friendly interfaces to domain experts, limited support is available for figure display, project management, and multi-user team annotation. In response, we developed TeamTat, a web-based annotation tool (local setup available), equipped to manage team annotation projects engagingly and efficiently. TeamTat is a novel tool for managing multi-user, multi-label document annotation, reflecting the entire production life cycle.
주요 기능
1. Project managers can select annotator(s) and distribute documents anonymously to prevent bias.
2. Multiple users can work on the same document independently.
3. the team manager can track task completion.
4. The project manager can merge all individual annotations, and evaluate corpus quality via inter-annotator agreement statistics.
사용방법
1. You need to install Ruby, MySQL, Git and NodeJS first.
2. Clone this repository : https://github.com/ncbi-nlp/TeamTat.git(Currently the repository is private. So you need a permission to access it. Soon, it will be transferred to a public repository such as NCBI GitHub repository.)
3. Configure config/database.yml
4. You need to generate a new key and secrets.
5. Install ruby packages and create database.
6. Run the server on the local computer.
7. Open the site from you web browser, such as Google Chrome.