Fix correctness issues in Arabic normalization and prompt loading

[RinZ27]

Several correctness issues were identified during a deep dive into the codebase, specifically affecting Arabic normalization, prompt loading, and logging hygiene.

Key changes:

• Corrected the Arabic definite article removal regex in mlqa/utils.py. The previous regex had a misplaced caret and was overly aggressive, which could lead to corrupted word forms.
• Added an else block in lm_eval/prompts/__init__.py to provide a clearer error message when an unknown prompt category is used, preventing a potential UnboundLocalError.
• Removed a debug print(prompt) statement in med_prescriptions/utils.py to keep evaluation logs clean and protect potential PII in medical datasets.
• Cleaned up redundant variable assignments (e.g., x = x) in the ruler task module to improve code clarity.

Verified the fixes by running the test_utils.py suite and confirmed everything passes correctly. These improvements directly benefit evaluation accuracy and project robustness.

[CLAassistant]

All committers have signed the CLA.