First, I want to thank you for the great work on Prodigy and spaCy. I was able to progress much faster on my NER project since I started using Prodigy and spaCy. Now I have a trained NER model with 13 labels that performs fairly decently, overall F-score > 90%, but for one label, sometimes the prediction will only include portion of the ground truth span. However, when I tried running the same sample through
ner.teach it's highlighting the correct span. After some digging, I was able to nail down the following situation:
nlp = spacy.load(model_path) # trained NER model displacy.render(nlp(sample_text), style="ent")
while this shows the incorrect predicted entity (partially highlighted)
from prodigy.models.ner import EntityRecognizer nlp = spacy.load(model_path) # trained NER model model = EntityRecognizer(nlp) displacy.render(nlp(sample_text), style="ent")
EntityRecognizer, the error is gone. I wonder if you could shed some light on this. Thanks!