Juxta is an open-source tool for comparing and collating multiple witnesses to a single textual work. Originally designed to aid scholars and editors examine the history of a text from manuscript to print versions, Juxta offers a number of possibilities for humanities computing and textual scholarship.
MALLET (MAchine Learning for LanguagE Toolkit) is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.
The Text Encoding Initiative (TEI) is a consortiumthat develops and maintains a standard for the representation of texts in digital form. Its chief deliverable is a set of Guidelines (since 1994) that specify encoding methods for machine-readable texts, chiefly in the humanities, social sciences and linguistics.
Instructors can create classes and upload texts for students to view and annotate. Classes can be divided into sections, and comments can be restricted to user groups (self only, instructors and TAs only, whole class).