  Manual annotation of textual documents is a necessary task when constructing
benchmark corpora for training and evaluating machine learning algorithms. We
created a comprehensive directory of annotation tools that currently includes
93 tools. We analyzed the tools over a set of 31 features and implemented
simple scripts and a Web application that filters the tools based on chosen
criteria. We present two use cases using the directory and propose ideas for
its maintenance. The directory, source codes for scripts, and link to the Web
application are available at: https://github.com/mariananeves/annotation-tools
