If it correctly understands peanutS, it will classify it as "more likely 2 items" considering it would check everything against some sort of dictionary. Which contains "peanuts, butter, peanut butter".

PS. I implemented something similar without machine learning and that's how i did it. With text it's easier though, i suppose in NLU it could have a parameter for "pause time between words" which could also contribute to a different conclusion.