I am trying to annotate with the help of
ner.teach recipe but after around 100 annotations, “ No Task Available” window comes up, even if there’s a plenty of data still left for annotation.
I am using this command:
prodigy ner.teach dataset_new_1 en_core_web_lg train/reviews_new_1.txt --label BEVERAGE --patterns beverage_patterns_1.jsonl
I am using
prodigy == 1.5.1
Hi! There can be several reasons for this – you might find my comment on this thread helpful. It's about
textcat.teach, but the stream behaviour is similar in
ner.teach, wihch is also an active learning-powered recipe:
Thanks for the report!
Just tested it with your example data and came across the same behaviour. There weren’t any errors either, so I think what might be happening here is the following: textcat.teach scores the stream and tries to only show you the most relevant tasks. Since there are only 100 examples, the “most relevant” selection seems to be only about 10-20%, which means the stream is exhausted after 10-20 examples.
This is probably unideal, and we’ll think about the best way to handle t…
Thanks, the batch files didn’t have enough Names Entities, So “NO TASK AVAILABLE” was coming frequently.