How to generalize comments using NLP
Basically, we want to cluster similar comments and assign a name/entity to it. I suggest you to use Doc2Vec to convert the comments to fixed-sized vectors. Each of your comments will then be a n-dimensional vector. Comments with similar words/phrases will lie in the close proximity of one another.


  Now, using K-Means Clustering, we can form clusters of vectors that
  represent comments having a similar meaning. Once the clusters are
  formed, assign a name to each of them.


For a given sample ( comment ), the model will first transform the given comment into a vector. The model will then check for a cluster that is nearest to the given sample's vector. The output will be the name of the nearest cluster.