We used the public tool, word2vec, released by Mikolov-2013 to obtain the word embeddings. Their neural network approach is similar to the feed-forward neural networks BIBREF5 , BIBREF6 . In the Skip-gram model architecture we used, we have chosen 200 as the dimension of the obtained word vectors. 
 Question: What type and size of word embeddings were used?
word2vec 200 as the dimension of the obtained word vectors