AI-900 Question 194
Select 3A company wants to implement a customer support chatbot that can understand and respond to user queries in natural language. Which of the following NLP workload scenarios are most relevant for this use case?
- A
Text classification
- B
Named entity recognition
- C
Sentiment analysis
- D
Language generation
- E
Translation
Show answer and explanation
Correct answers: A, B, D
Explanation
For a customer support chatbot, understanding the user's intent (text classification), extracting key details (named entity recognition), and generating appropriate natural language responses (language generation) are essential NLP features. Sentiment analysis and translation are not core requirements unless explicitly needed for the chatbot's functionality.
- A. Correct.
Text classification is relevant as the chatbot needs to classify the intent of the user's query to determine the appropriate response.
- B. Correct.
Named entity recognition is important because the chatbot may need to extract specific entities like names, dates, or product details from the user's query.
- C. Incorrect.
Sentiment analysis is not central to this use case, as the primary goal is to provide accurate responses rather than understanding user emotions.
- D. Correct.
Language generation is critical for the chatbot to construct coherent and contextually appropriate responses to user queries.
- E. Incorrect.
Translation is not directly relevant here unless the chatbot needs to support multiple languages, which is not specified in this scenario.