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

[ultramancode]

Thanks for the review! I've updated the PR based on your suggestions. The capability-based approach made the implementation cleaner and easier to maintain.

[omri374]

This is a breaking change. If someone has a custom nlp engine, it might stop working if this property is set to False. Better to keep it always True and False for the no-op and slim engines

[ultramancode]

Thanks! has_ner now defaults to True, while SlimSpacyNlpEngine and NoOpNlpEngine explicitly return False. Tests and documentation have been updated accordingly.