thank you again for updating prodigy and such new property that you add, I am really enjoying using prodigy for NER.
I have trained a custom named entity recognition label by the label. for the most label, it works very well
but some times flr label "COOR" which basically "Coordinate " in a different format ( all old version of data format) I have problem
here you can see the result:
as you see in the second label related to"COOR"
but when I change the text ( here I changed the second label to 12 23 25) it works
why it is so error-prone, I have calculated the metrics:
for label "COOR"
I have very good metric, I know 1 percentage mistake in a large corpus could cause some mistake, but how can I improve it.
my model is made by this way, using regex --> checking by annotation and adding some human level entity---training by prodigy for each label(too see each model) --merging labels ---training whole custom NER
do you have any hint for me to improve my model?
can I use matcher from spacy only for "COOR" to improve the NER Model
Many thanks in advacne