TensorFlow implementation of Tang et al.'s EMNLP 2016 work.
Given a sentence and an aspect occurring in the sentence, this task aims at inferring the sentiment polarity (e.g. positive, negative, neutral) of the aspect.
For example, in sentence ''great food but the service was dreadful!'', the sentiment polarity of aspect ''food'' is positive while the polarity of aspect ''service'' is negative.
Download the 300-dimensional pre-trained word vectors from Glove and save it in the 'data' folder as 'data/glove.6B.300d.txt'.
Train a model with 7 hops on the Laptop dataset.
python main.py --show True
Note this code requires TensorFlow, Future and Progress packages to be installed.