1) The training data is used for extracting features and building a machine learning model. It represents the vocabulary which the model learns from. The test data is used as unseen data for evaluating the learning of the model.
2) The model can be updated by adding feedback data using an activity.
3) The jar consists of binary files, properties files and encoders. The binary file consists weights, vocabulary and feature set. It is not human readable.