What features are generally used from Parse trees in classification process in NLP?
By using a parse tree, you divide your sentence into parts. Suppose, in the example of sentiment analysis, you can use those parts to assign a positive/negative sentiment to each part and then take the cumulative effect of those parts.



This image will help you understand more. The first half has a negative sentiment(mainly because of the word "dry") but because of the word "but" and the usage of the word "enjoyed", the negative sentiment is turned into a positive sentiment.

As for using them, you can simply generate a word vector representation of the individual words in the sentence and use neurons in place of the parent nodes. Each neuron should be connected to another neuron through weights. All the leaf nodes will be the word vector representations of words of the sentence. The top parent neuron(in this case the top blue + symbol) should generate a positive/negative sentiment according to the sentence. This tree structure can be trained in a supervised manner.

Read this paper for a more through understanding.

Image credits: cs224.stanford.edu