Softmax and text classification

I am going to do Sentiment Analysis over some tweet texts. So, in summary we have three classes: Positive, Neutral, Negative. If I apply Softmax in the last layer, I will have the probability for each class for each piece of text. we know that in Softmax:

P(pos) + P(neu) + P(neg) = 1

My question: suppose that we have a piece of text in Positive label. So, do we have to have these probabilities in this order:
P(pos) > P(neu) > P(neg)

What does it mean when we have them in this order:

P(pos) > P(neg) > P(neu)

Can we conclude anything from this? For example, can we say with confidence that the label is Positive like as before?