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Why do hybrid approaches often improve NLP system performance?

easy📝 Conceptual Q2 of 15
NLP - Sentiment Analysis Advanced
Why do hybrid approaches often improve NLP system performance?
AThey use only large datasets
BThey combine strengths of rules and learning
CThey avoid any manual effort
DThey rely solely on pre-trained models
Step-by-Step Solution
Solution:

  1. Step 1: Analyze benefits of combining methods

    Rules provide precision, machine learning offers flexibility; combining both covers weaknesses.

  2. Step 2: Evaluate options

    Only They combine strengths of rules and learning correctly states the benefit; others are incorrect or incomplete.

  3. Final Answer:

    They combine strengths of rules and learning -> Option B

  4. Quick Check:

    Hybrid benefit = Combining strengths [OK]
Quick Trick: Hybrid improves by mixing precise rules and flexible learning [OK]
Common Mistakes:
MISTAKES
  • Assuming hybrid avoids manual work
  • Thinking hybrid needs only big data
  • Believing hybrid uses only pre-trained models

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