MLS-C01 Amazon Comprehend Practice Question
A data scientist is working with a dataset that contains text reviews and a numeric rating (1-5). The goal is to predict the rating from the review text. During EDA, the scientist wants to check if there are any spelling errors or unusual characters. Which tool is BEST suited for this task?
⚠ Common exam trap
Candidates might think Amazon Comprehend can detect spelling errors directly, but it does not. It analyzes syntax and entities, which can help identify unusual patterns, but a custom solution or spell-check library would be needed for exact spelling correction.
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
✓
Amazon Comprehend to detect syntax and entities.
Amazon Comprehend is the best choice among the options because it is an AWS AI service that can detect syntax, entities, and key phrases in text. While it does not directly find spelling errors, it can identify unusual patterns or anomalies in text that may indicate misspellings or odd characters. SageMaker Data Wrangler is for tabular data, Athena is for SQL queries, and QuickSight is for visualization, none of which are specialized for text analysis in this context.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Amazon SageMaker Data Wrangler with a custom transform for text cleaning.
Why it's wrong here
Amazon SageMaker Data Wrangler is designed for data preparation and feature engineering on tabular data, not specifically for text analysis or spell-check. While it can apply custom transforms for text cleaning, it is not the best tool for detecting spelling errors during EDA compared to a purpose-built NLP service.
- ✗
Amazon Athena with SQL queries to find anomalies.
Why it's wrong here
Amazon Athena allows SQL queries on data in S3. It can find anomalies using patterns or regular expressions, but it is not specialized for text semantics and would require complex queries; it is less suited than Comprehend.
- ✓
Amazon Comprehend to detect syntax and entities.
Why this is correct
Correct. Amazon Comprehend provides syntax analysis and entity detection, which can help identify unusual text patterns (e.g., misspelled words or odd characters) without custom coding. It is the most appropriate AWS AI service among the options for initial text inspection.
- ✗
Amazon QuickSight to create word clouds.
Why it's wrong here
Amazon QuickSight is a business intelligence tool for creating visualizations. It can generate word clouds from text, but word clouds only show word frequency, not spelling errors or unusual characters. Thus, it is not suitable for this detection task.
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