POTATO: The Portable Text Annotation Tool

TL;DR

POTATO is an open-source, customizable text annotation tool that enhances labeling efficiency for diverse data types and complex tasks, supporting active learning and user-friendly features.

Contribution

It introduces a flexible, feature-rich annotation system that improves productivity and customization for NLP and multimodal data labeling.

Findings

Increased labeling speed for long documents and complex tasks

Supports multiple data types and multimodal annotation

Enhances productivity with templates and shortcuts

Abstract

We present POTATO, the Portable text annotation tool, a free, fully open-sourced annotation system that 1) supports labeling many types of text and multimodal data; 2) offers easy-to-configure features to maximize the productivity of both deployers and annotators (convenient templates for common ML/NLP tasks, active learning, keypress shortcuts, keyword highlights, tooltips); and 3) supports a high degree of customization (editable UI, inserting pre-screening questions, attention and qualification tests). Experiments over two annotation tasks suggest that POTATO improves labeling speed through its specially-designed productivity features, especially for long documents and complex tasks. POTATO is available at https://github.com/davidjurgens/potato and will continue to be updated.