I’m using pos.teach on a dataset of 114 separate sentences. After about 10 annotations, it stops and says No tasks available.
If I stop the server and restart it, it will work again, but this isn’t a good scenario when you have someone else doing the annotations remotely. That person can’t stop and restart the server.
Is there a solution for this?
Sorry for all the questions and thank you for your quick replies.
I think one problem here is that you’re using an active learning recipe with very little data. If you’re running an active learning powered recipe like pos.teach, Prodigy will create various possible analyses for each example and only show you the most relevant for annotation. This means it’ll skip the ones with very high or very low predictions and will focus on the most relevant examples. This is nice if you have lots of data and want the best possible annotations, but not so helpful if you want to label every example.
So what’s likely happening here is that you annotate a bunch of examples and get to the end of the selected examples of your stream. So there’s nothing left to annotate. If you restart the sever, you’re resetting the model in the loop and Prodigy is trying to find you new examples to annotate.
If oyu really only have 114 sentences and it’s important to you that they’re all annotated, you probably want to use a manual recipe or semi-manual recipe (like make-gold) and go through every example. Using an active learning recipe like teach is more useful if you have lots of raw data and want to optimise the example selection.