Hi! I am not sure, but I think there might be model version issues w

Spacy model version issues? about elevant HOT 2 OPEN

ad-freiburg commented on August 26, 2024

Spacy model version issues?

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Comments (2)

agolo-alan-hogue commented on August 26, 2024

Oh, I forgot to mention, before that I got this error, which I fixed the following way:

src/helpers/entity_linker_loader.py

pipeline = ['tagger', 'parser', 'ner', 'entity_linker']
        for pipe_name in pipeline:
            # pipe = model.create_pipe(pipe_name)
            model.add_pipe(pipe_name)

Error (truncated):

ValueError: [E966] `nlp.add_pipe` now takes the string name of the registered component factory, not a callable component. Expected string, but got <spacy.pipeline.tagger.Tagger object at 0x2b30698b0> (name: 'None').

- If you created your component with `nlp.create_pipe('name')`: remove nlp.create_pipe and call `nlp.add_pipe('name')` instead.

- If you passed in a component like `TextCategorizer()`: call `nlp.add_pipe` with the string name instead, e.g. `nlp.add_pipe('textcat')`.

- If you're using a custom component: Add the decorator `@Language.component` (for function components) or `@Language.factory` (for class components / factories) to your custom component and assign it a name, e.g. `@Language.component('your_name')`. You can then run `nlp.add_pipe('your_name')` to add it to the pipeline.

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flackbash commented on August 26, 2024

Thanks for reporting this. This should be a model version issues. I believe the models were trained with spaCy 2 still.

We had not tested the spaCy linker recently, since frankly the results were not very convincing.
I'll try to retrain the model but this was also done by a colleague a few years ago, the code is still based on spaCy 2 and there seem to have been plenty of changes in spaCy 3 that affect this code. I'll let you know if I make any progress.

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