text classification

[robertto]

Hi @ines
Morning! good news! I managed to run
textcat.manual on a raw text without label in order to gather labels as follows

python -m prodigy textcat.manual dfobsv02 en_core_web_sm dfObsV02.jsonl --label Observational,Nonobservational --exclusive

now annotator can manually annotate observational sentence from nonobservational sentences

my question is if I have predefined labels (y values, basically 0 and 1) how can I run textcat.manual to edit those (similar to ner.manual)
I think I should change the type of my data since now it is so:

{"text":"my text."}
{"text":"my test 02."}
{"text":"my test 03."}

my second question is , can I see my ner labels when I classify the sentences in textcat.manual how to use my NER label .. to kind of improve classification?

and my last question maybe it is not related to this threat. how can I add-relation to entities?
I have read this

Relation Extraction annotation tests

Hi @ines, In this other thread, you told me the following: When you’re done with that, you could export the data and run one experiment where you link up highlighted spans close to each other and collect binary feedback on whether they are connected. You could either create data in the dep format (with a head and child), or use the choice interface with the options “For”, “Against”, “Support” and “Attack”. So I was testing the two approaches, but I’m having a hard time making them work. I’…

still, dot now how can I use my annotated data (ner) by prodigy to make training set for relation extraction

I really like the prodigy , I have learned a lot here.
Best