DKPro TC supports the following processing modes that correspond to typical classification setups in Natural Language Processing, which are shown in the table below:
Document Mode: Classifes whole documents, classical use-case is for instance E-mail classification into
no spam (single-label)
Unit Mode: Sub-document classification, this is a special case of document mode where the classification focuses on two or more smaller portions of the text body, for instance classyfing the age-range on several user-comments under an article where both, the article and the user comments are hold together (single-label).
Sequence Mode: Classification mode for sequentially dependend information where the prediction of the preceding element is relevant for the prediction of the next one, for instance in part-of-speech tagging where the prediction sequence of word-labels carries meaning for the next word (single-label).
Classification using Multi-Label are for instance prediction of movie categories where a movie might belong to more than just a single category and the different categories have a certain correlation to (not) occur together. Regression is a special form of single-label classification where instead of a fixed label a numerica value is predicted.
The processing configuration is provided by two dimensions in a DKPro TC Experiment