AI Associate Salesforce Einstein AI Features Practice Question
A data scientist is using Einstein Vision and Language Platform for text classification. They need to handle custom entities (NER) and classify text into multiple categories. Which THREE capabilities of the Einstein Platform Services API should they use?
⚠ Common exam trap
Watch out — candidates often confuse computer vision capabilities (Object Detection and Image Classification) with text-based NLP tasks, leading them to select options that are irrelevant to the given scenario of text classification and NER.
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
✓
Sentiment Analysis
Sentiment Analysis is a key capability of the Einstein Platform Services API that allows the data scientist to determine the emotional tone (positive, negative, or neutral) of text, which is essential for understanding customer feedback or social media posts. This complements the other required capabilities—Text Classification for categorizing text into multiple categories and Named Entity Recognition (NER) for extracting custom entities—forming a complete solution for the described text classification and NER tasks.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Object Detection
Why it's wrong here
Object Detection is for images, not text.
- ✗
Image Classification
Why it's wrong here
Image Classification is for images, not text.
- ✓
Sentiment Analysis
Why this is correct
Sentiment Analysis determines the sentiment of text.
- ✓
Text Classification
Why this is correct
Text Classification categorizes text into predefined classes.
- ✓
Named Entity Recognition (NER)
Why this is correct
NER extracts custom entities from text.
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