optimize complexity of filter out unwanted recognizers from O(n*m ) to O(n)

[rgupta2508]

Change Description

Code refactor.

Improve complexity of filter out unwanted recognizers from O(n*m )to O(n)

In current code for loop is running inside for loop that makes complexity to O(n*m). after this change there is only one loop by using one extra variable.
where
m = total number of all_possible_recognizers
n= total supported entities which we want to include .

Describe your changes

Issue reference

This PR fixes issue #XX

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[rgupta2508]

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[omri374]

/azp run

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Azure Pipelines successfully started running 1 pipeline(s).

[Copilot]

Copilot reviewed 1 out of 1 changed files in this pull request and generated 1 comment.

[Copilot]

If multiple recognizers support the same entity, only the last one will be stored in the dictionary. This could lead to unintended behavior if the order of recognizers matters.

Suggested change

	all_entity_recognizers.update(dict.fromkeys(rec.supported_entities, rec))
	all_entity_recognizers.setdefault(entity, []).append(rec)

[omri374]

Hi, thanks for creating this PR! Assuming it is possible for multiple recognizers to support the same entity, how to this mapping look like?