Supervised learning model for extracting terror attack motives from attack summary (NLP)
Use word embedding and encode the entire sentence into one fixed feature vector by using vanilla RNN or more sophisticated model like attentional LSTM.
see Sentiment analysis using RNNs(LSTM)
Concat the other features with the fixed length representation of the sentence and append on top of them either dense layer.
the architecture 
 feedforward(concat(other_features,RNN(sentence)))