uploading spacy model for ner.make-gold annotation

Dear @ines and @honnibal,

I saw that some people had used the trained spacy model recursively for improving the accuracy of the NER tagging.

I trained an entity that is "SPORT" by using the spacy's train_new_entity_type.py with an existing "en_core_web_lg" model, and saved the output model for re-using it in the ner.make-gold. But when I run this command:
prodigy ner.make-gold sport_terms_2 /../prodigy/spaCy/examples/training/model_SPORT/ner/model ../raw_data_8_8_2019.jsonl --label "SPORT, ORG, GPE”
it did not start the API for annotation. May be I try to import wrong output of the spacy.

Could you please tell me how can I import the spacy_model that I obtained in order to use it for making gold data again?

Thanks,

What do you mean by "did not start the API for annotation"? Did you get an error?

The command you run looks correct, but this potentially wrong:

You'll need to load the entire model directory you exported when you pre-trained the model. The same thing that spaCy expects for spacy.load. It should be the directory that has a meta.json in it, and a bunch of directories for the pipeline components. From your example, it looks like you might be trying to just load the ner subdirectory?

I didn't get any error but I was waiting for a link to access the localhost:8080.
Actually I only tried to import the model file inside the ner subdirectory.

So, I tried to import the output directory that I got from the spacy training as you said, but there is no error it just give me ">" command line. I don't understand.

$ prodigy ner.make-gold sport_terms_2 /Users/asli/Desktop/NER/prodigy/spaCy/examples/training/model_SPORT ../raw_data_8_8_2019.jsonl --label "SPORT, ORG, GPE”

I want to use that model for annotating the new texts and make new annotations by using suggestions from the model so that I could use the new annotations for training spacy's train_new_entity_type.py again.
But, I guess ner.make-gold is not a method that suggests the entity from a given text, am I right? I would like to speed up annotation process for me since GPE and ORG entities are already in the pretrained model. So what do you suggest to me ?

I hope I am clear cause I am new to prodigy, and I get some difficulty to explain my problem with the syntactic language of the prodigy and spacy.

When I tried that command:

import spacy
spacy.load("/Users/asli/Desktop/NER/prodigy/spaCy/examples/training/model_SPORT")
<spacy.lang.en.English object at 0x10cb64320>
It seems like working but I cannot upload this model with:
prodigy ner.make-gold sport_terms_2 "/Users/asli/Desktop/NER/prodigy/spaCy/examples/training/model_SPORT" ../raw_data_8_8_2019.jsonl --label "SPORT, ORG, GPE”

I also checked the spaCy's Saving, loading and distributing models but I didn't understand clearly. Could you please help me.

I found my error. It's because of different type of double quote at the end of the labels. So it works now.

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