In addition to my main question, I’m hoping to understand how to build a good workflow for my problem.
I have a new tag I’d like to train (a particular set of names, company and persons only) in documents. I’ve split a few of those documents into sentences and I’m feeding them into ner.manual
.
As I understood ner.teach
, it’s good to have somewhat equal balance between positive and negative examples. How does this work for ner.manual
?
My guess is that the workflow should be like so:
ner.manual
-
ner.teach
based on the manual tags from before
Alternatively, I also tried this workflow:
terms.teach
ner.teach
But this one sort of focused a lot more on the person names instead of company names, I suppose given that the word vectors are better trained on the former. I can’t exactly be sure of this though.