fix(analyzer): skip SpacyRecognizer for SlimSpacyNlpEngine

[ultramancode]

Change Description

SlimSpacyNlpEngine disables NER, but the recognizer registry treated it like a regular spaCy engine and added SpacyRecognizer.

When SpacyRecognizer received an empty supported-entities list from the slim engine, it fell back to its default entities. As a result, the registry reported NER entities that the slim engine could not produce.

When SlimSpacyNlpEngine is used, the registry no longer adds SpacyRecognizer automatically.
If SpacyRecognizer is explicitly configured, analyzer initialization fails because the slim engine does not produce the NER results it requires.

This does not affect tokenization, lemmatization, or context-based score enhancement provided by the slim engine.

Checklist

• I have reviewed the contribution guidelines
• I agree to follow this project's Code of Conduct
• I confirm that I have the right to submit this contribution and that it does not knowingly contain proprietary or confidential code.
• My code includes unit tests
• All unit tests and lint checks pass locally
• My PR contains documentation updates / additions if required

[omri374]

Could be a debug message

[omri374]

This list is a good start, but it's (a) hard to maintain (we might forget to update it) and (b) hard to customize for a user downloading from pypi and adding a custom Nlp Engine.
Here's my suggestion. In NlpEngine, add a has_ner property

class NlpEngine(ABC):
    ...
    @property
    def has_ner(self) -> bool:
        """Returns True if this engine performs Named Entity Recognition natively."""
        return False

And use this to filter out the SpacyRecognizer