Error when trying to retrain the NER model for Spacy v2.2.1

Hi, I'm using a model that I retrained with Prodigy for more accurate NER detection. The model was trained with Spacy 2.1 and previous version of Prodigy.
After updating both packages (Prodigy 1.8.4, Spacy 2.2.1, redownloaded models vor v2.2) and trying to retrain the model with existing dataset, which worked fine before, I now get an error:

Loaded model en_core_web_sm
Using 5% of accept/reject examples (933) for evaluation
Using 100% of remaining examples (17739) for training
Dropout: 0.15  Batch size: 16  Iterations: 4  

BEFORE      0.671             
Correct     589 
Incorrect   289
Entities    2870              
Unknown     2241              

#            LOSS         RIGHT        WRONG        ENTS         SKIP         ACCURACY  
Traceback (most recent call last):                                                                                                                                                                                                      
  File "/usr/lib/python3.6/", line 193, in _run_module_as_main
    "__main__", mod_spec)
  File "/usr/lib/python3.6/", line 85, in _run_code
    exec(code, run_globals)
  File "/home/virostatiq/PycharmProjects/prodigy_annotation/venv/lib/python3.6/site-packages/prodigy/", line 380, in <module>
    controller = recipe(*args, use_plac=True)
  File "cython_src/prodigy/core.pyx", line 212, in prodigy.core.recipe.recipe_decorator.recipe_proxy
  File "/home/virostatiq/PycharmProjects/prodigy_annotation/venv/lib/python3.6/site-packages/", line 328, in call
    cmd, result = parser.consume(arglist)
  File "/home/virostatiq/PycharmProjects/prodigy_annotation/venv/lib/python3.6/site-packages/", line 207, in consume
    return cmd, self.func(*(args + varargs + extraopts), **kwargs)
  File "/home/virostatiq/PycharmProjects/prodigy_annotation/venv/lib/python3.6/site-packages/prodigy/recipes/", line 621, in batch_train
    examples, batch_size=batch_size, drop=dropout, beam_width=beam_width
  File "cython_src/prodigy/models/ner.pyx", line 362, in prodigy.models.ner.EntityRecognizer.batch_train
  File "cython_src/prodigy/models/ner.pyx", line 441, in prodigy.models.ner.EntityRecognizer._update
  File "gold.pyx", line 597, in
  File "gold.pyx", line 809, in
**ValueError: [E103] Trying to set conflicting doc.ents: '(0, 4, '!ORG')' and '(0, 4, 'PERSON')'. A token can only be part of one entity, so make sure the entities you're setting don't overlap.**

How could I fix the dataset?


We released Prodigy v1.8.4 to make the current bugfixes for Prodigy available to everyone, before we release v1.9. The v1.8 release is compatible with spaCy v2.1 --- we wouldn't change the compatibility in a patch release, as it would break people's existing installations.

We should have v1.9 out shortly, which will include support for spaCy v2.2. In the meantime, you should be able to use v1.8.4 with spaCy v2.1 without issues.