Your NLP health shows you how accurately your chatbot responded to your chatbot user's messages. You can use your NLP Health to gauge how well your NLP training phrases match the messages your chatbot receives.
Your NLP health score doesn't worry about whether the chatbot had the content it needed, only whether it chose correctly from the content that it had. If you were marking a lot of responses as needing to go to a different passage (but not a new passage) this score will be a little lower.
Your NLP Health score doesn't include interactions where the chatbot sent a catch all because:
- The chatbot user sent a garbled message.
- The chatbot user sent a message the chatbot is not intended to handle.
- The chatbot did not have the correct content to respond to the user.
The NLP Health score does include instances where the chatbot sent the catch-all when it should have matched the chatbot user's message to an existing NLP question.
Remember, each review depends not just on your chatbot, but what your chatbot users happened to send to your chatbot this time around. Don't worry if your NLP health fluctuates a little between reviews.
If you want to see more of a breakdown, you can switch to the Data view:
Expected answers indicate where the chatbot replied with the correct response.
Unexpected answers indicate where the chatbot did not correctly match the NLP question, and replied with the wrong passage.
The inGenious AI platform will generate training phrase recommendations to add to your chatbot to improve your NLP accuracy. You can also open a more advanced look at the data in a new window.