Difficulty: Easy
Correct Answer: All of the above
Explanation:
Introduction / Context:
Natural language understanding (NLU) refers to computational methods that parse and interpret human language input to extract meaning, intent, and actionable structure. This capability underpins a variety of system categories used in databases, applications, and information extraction.
Given Data / Assumptions:
Concept / Approach:
NLU powers natural language interfaces (directly querying systems in everyday language), natural language front ends (wrapping existing systems like databases or search with NLU), and text understanding systems (information extraction, summarization, sentiment). Therefore, all listed categories legitimately employ NLU techniques.
Step-by-Step Solution:
Verification / Alternative check:
Industry applications—from voice assistants (interfaces/front ends) to document mining (text understanding)—demonstrate NLU’s breadth.
Why Other Options Are Wrong:
Common Pitfalls:
Assuming NLU is only for unstructured text analytics; forgetting that front ends and conversational interfaces depend on the same semantic parsing.
Final Answer:
All of the above
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