# SLATE: A Super-Lightweight Annotation Tool for Experts

arXiv: https://arxiv.org/abs/1907.08236 · HTML: https://mlsanity.com/paper/1907.08236/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Jul 2019.

## Built on by (most cited first, 2 of 2)

- [PAWLS: PDF Annotation With Labels and Structure](https://mlsanity.com/paper/2101.10281/) (2021)
- [CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction](https://mlsanity.com/paper/2307.00769/) (2023)

## Abstract (arXiv)

Many annotation tools have been developed, covering a wide variety of tasks and providing features like user management, pre-processing, and automatic labeling. However, all of these tools use Graphical User Interfaces, and often require substantial effort to install and configure. This paper presents a new annotation tool that is designed to fill the niche of a lightweight interface for users with a terminal-based workflow. Slate supports annotation at different scales (spans of characters, tokens, and lines, or a document) and of different types (free text, labels, and links), with easily customisable keybindings, and unicode support. In a user study comparing with other tools it was consistently the easiest to install and use. Slate fills a need not met by existing systems, and has already been used to annotate two corpora, one of which involved over 250 hours of annotation effort.