Hence, we explore the effectiveness of compositionality of word embeddings in developing a model-free automatic metric to evaluate summary content quality.
we obtain the sense embeddings using the pre-trained model by Rothe and Schütze (2015), that lives in the same vector space as the pre-trained word2vec by Mikolov et al.