Is there an example of whole procedure of NER using Prodigy?

Is there an example of whole procedure of NER using Prodigy?
The procedure need to include:

  1. how to labelling the text files, analysis of the labeled results;
  2. How to export the labeled data in prodigy;
    3.How to trained the labeled data in Bert Model;
    4.How to the the Bert Model.

I'm a newbie, I'd like to know the step-by-step example of how to extract named objects from the text files.
Thank you all in advance.

Hi! It ultimately depends on the exact use case, but there are several end-to-end examples in the docs, including a full project on detecting fashion brands (with code and data), a video and other examples for different use cases:

If you're just getting started, you might also want to check out the 101 guide, which shows how to get started, how to run Prodigy, how to start annotating, how to export the data, train and so on:

This is slightly out-of-scope for Prodigy itself – fundamentally, Prodigy is an annotation tool. How you train your model is up to you and depends on what you're training, the library you want to use etc. Prodigy stores the annotations in a very straightforward JSON format that includes the entity offsets for NER. Here's an example: Also see the docs here for how to convert offsets to token-based tags. You can always export the data and use it to train your models, or write a custom training recipe that does this automatically.