I have a set of 100 examples annotated for Span Classification task using Prodigy. I realised, that some of them (let's say, 35) should be corrected and re-annotated. I can extract all 100 annotations into either .spacy or .jsonl format and find those examples I need to amend.
My question is: once I found the required 35 examples, how do I load them back into Prodigy to correct?
Specifically, I loaded 100 examples using spaCy into Doc objects, selected the required ones and saved as .spacy. Is there a simple way of loading .spacy format into Prodigy to continue annotation, or I need to reformat it in a different way?
Overall, I heed to load these 35 examples back into Prodigy, amend the spans and save them again.
If the examples you need to correct are in .jsonl format it's as easy as feed them into the ner.manual recipe specifying the labels you want to have available.
So if the input file is called to_be_corrected.jsonl and assuming blank:en as the base model then the call would be: