Here, the best model proposed by <cite>Santus et al. (2016)</cite> uses Random Forest classifier which is fed with nine corpus based features like frequency of words, co-occurrence frequency etc., and the best model proposed by Jana and Goyal (2018b) use Random Forest classifier which is fed with five complex network features like structural similarity, shortest path etc. The results in Table 4 shows that, for the binary classification task of co-hyponymy vs random pairs, we achieve percentage F1 score of 99.0 with RF CC which is at par with the state-of-the-art models.