AI-102 Practice Question: Implement natural language processing solutions
Your organization uses Azure AI Language to perform sentiment analysis and opinion mining on product reviews. You notice that the sentiment scores are often neutral even when the review text contains clearly positive or negative opinions. You suspect the model is not capturing the nuances. Which three actions could improve the sentiment analysis accuracy? (Choose three.)
⚠ Common exam trap
Watch out — candidates often assume pre-processing with key phrase extraction (option B) or using the basic API (option D) can fix model accuracy issues, when in fact only custom training (Azure AI Language custom sentiment analysis), opinion mining, or domain-specific models address the root cause of neutral scores due to lack of nuance.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Provide more labeled training examples that cover a wider variety of writing styles and sentiments.
Providing more labeled training examples that cover a wider variety of writing styles and sentiments directly improves the custom model's ability to learn nuanced patterns. Azure AI Language's custom sentiment analysis relies on supervised learning; more diverse, high-quality labeled data helps the model generalize better and reduces the tendency to default to neutral scores for ambiguous or complex reviews.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Provide more labeled training examples that cover a wider variety of writing styles and sentiments.
Why this is correct
More diverse training data helps the model generalize better and capture nuances.
- ✗
Pre-process the text with key phrase extraction to highlight important terms before sentiment analysis.
Why it's wrong here
Key phrase extraction does not improve sentiment analysis; the model already uses the full text.
- ✓
Use the opinion mining feature to capture sentiment targets and associated opinions.
Why this is correct
Opinion mining provides aspect-based sentiment, which can improve overall sentiment detection by analyzing specific targets.
- ✗
Use the basic sentiment analysis API without any customization.
Why it's wrong here
The basic API is what you already have; using it alone does not improve accuracy.
- ✓
Enable the domain-specific model for 'Reviews' if available.
Why this is correct
Domain-specific models are pre-trained on relevant data and can improve accuracy for that domain.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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