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What do ‘pairs’ control in NLTK rule-based Python chatbot design?
Learn how NLTK chatbot pairs define regular-expression input patterns and their matching response lists, enabling rule-based Python chatbots to map user messages to appropriate replies.
Question
What role do pairs play in chatbot design?
A. They encrypt user conversations
B. They handle SQL joins for text data
C. They define input patterns and matching responses
D. They store financial categories
Answer
C. They define input patterns and matching responses
Explanation
Pairs are central to chatbot replies.
In NLTK’s Chat class, pairs is a list of tuples where each entry contains a regex pattern and a list of candidate responses; the engine matches input to a pattern and returns a corresponding response.
Captured groups from the pattern (e.g.,.∗) can be inserted into template responses via placeholders like %1, producing context-aware replies.
The ELIZA implementation demonstrates this structure clearly, pairing patterns with response lists to drive the conversation flow.
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