Multi-document Annotation Environment

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Multi-document Annotation Environment

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Introducing MAE

MAE (Multi-document Annotation Environment) is a lightweight, geneal-purpose natural language annotation tool. It was originally created by Amber Stubbs for use in her dissertation research at Brandeis University, and currently Keigh Rim is maintaininig the project.

MAE allows users to define their own annotation tasks, mark up arbitrary text spans, use non-consuming tags, easily create links between annotations, and it outputs annotations in stand-off XML. It also allows for easy adjudication with visualization of extent tags, link tags, and non-consuming tags from any XML standoff annotated documents. (for best results, the files output by MAE should be used). While it does not enforce strict rules for annotation schemes, it is very easy to set up and start running. Check out the wiki for the user guide with detailed instructions.

How to use


Latest MAE requires Java 8 to run, and Maven to build. See the project wiki for more details.

For robust Unicode support, MAE uses DejaVu Sans font as the default. If the annotation task involves lots of Unicode characters, such as Emojis, users are also recommended to have DejaVu Sans font installed.

Download and run

Download release package or executable .jar from from releases page. Once you have mae-<VERSION>.jar file, simply double click the file will run MAE. Be sure that you have a proper version of Java installed.

Annotation and Adjudication

See the project wiki for detailed users’ guide.


MAE is a free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

Also, MAE is written using open source software below.


Open source software used in MAE

Change History

All changes are documented on releases page.

See also

To learn more about natural language annotation, please refer to Amber Stubbs and James Pustejovsky’s book Natural Language Annotation for Machine Learning. (Note that the book is written using MAE 0.9.6)

You can also visit Amber Stubb’s old code base archive hosted on Google Code.