Why does a chatbot, trained on a dataset lacking context diversity, sometimes generate semantically plausible but inappropriate responses in novel situations?

💡 Explanation

The chatbot fails because it lacks a robust model of distributional semantics, meaning it cannot effectively infer meaning from context. Therefore, it generates inappropriate responses, rather than understanding subtle nuances in language outside its training, because of incomplete data coverage.

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