We also present results for a least squares fitting model, which approximates the distributional behaviour of holistic phrase/sentence vectors along the lines of ( Baroni and Zamparelli, 2010).
for each verb, we compute an estimator that predicts the ith element of the resulting vector as follows: Here, the rows of matrix X are the vectors of the subjects (or objects) that occur with our verb, and − → y i is a vector containing the ith elements of the holistic phrase vectors across all training instances; the resulting − → w i 's form the rows of our verb matrix.