The impressive results in our dataset, developed by randomly extracting 9,600 pairs from EVALution , Lenci/Benotto (Benotto, 2015) and BLESS (Baroni and Lenci, 2011) , were further tested against the state-of-the-art models presented in<cite> Weeds et al. (2014</cite> In future experiment, we plan to increase the number of features, investigating new distributional properties that may help in the classification without incurring in memorization effects such as those described by Levy et al. (2015) .