WordNet-based context enrichment uses the Word-Net synonyms to obtain the context, and concatenates them into the given word to build the ESA vector.
for instance, there is a given word pair "train and car", car has 8 different synsets that build 8 different contexts, and train has 6 different synsets that build 6 different contexts.