How to setup prodigy for several tasks on the same data points.

I'm trying to setup prodigy to annotate texts for several classification tasks (e.g. one task just being binary classification - is it about topic x or not and others multilabel classification - which method(s) is/are used from method a to method d). Currently, I have a custom recipe with a choice block that covers all classification tasks (basically just a long flattened list of all labels of all classification task) which obviously is not optimal.
Having seen other forum post, I was thinking of breaking it down into several tasks to make it less tedious and error-prone to the annotators, i.e. the annotators seeing the text several time, each time annotating for a different task (sometimes single, sometimes multiple choice depending on the task). Do you have any guidance on how to set this up? I was looking at task routing but that seems to be more about coordinating several annotators; we only have one annotator at the time.

Welcome to the forum @vera-bernhard :wave:

You're definitely right about separating different classification tasks into different annotation workflows. If there's not much dependency between the binary and multiple choice decisions, the easiest way to set up the annotation in your case would be to run one textcat.manual session with the binary classification task i.e. specifying just one label, then stop the Prodigy server and then run another textcat.manual session with multiple choice classification storing the examples to a different dataset to keep your annotations in order.
This way you would be able to use out-of-the-box recipes and train by specifying the corresponding datasets for textcat and textcat-multilabel components. Prodigy train command (as well as data-to-spacy) will take care of merging the annotations for spaCy training function (which is used under hood).