As distributional word vectors, we use the word2vec representations provided by  (trained with CBOW, 5-word context window, 10 negative samples, 400 dimensions).
whereas Zarrieß and Schlangen (2016) propose a strategy to avoid object names when the systems confidence is low, we focus on improving the generation of object names, using distributional knowledge as an additional source.