Network Features Based Co-hyponymy Detection
Table 1: The network properties of sample cases taken from BLESS dataset.
['[BOLD] Type', '[BOLD] Word pair', '[ITALIC] SS', '[ITALIC] SP', '[ITALIC] SPW', '[ITALIC] EDin', '[ITALIC] EDun']
The feature SS captures mainly the degree of overlap of the neighborhoods of the word pairs, whereas SPW and SP indicate the distance between them in the DT network by considering and not considering the weight of the edges along the shortest path, respectively. The intuition behind taking these features is that if two words are distributionally very similar, there should be a short path between the two words via common neighbors. We observe in the DT network that, sometimes only the length of the shortest path is not enough to indicate the distributional similarity between two words; the average edge weight along the shortest path provides the hints of similarity between two words as well. This is the intuition behind proposing the measure SPW along with SP. The last two proposed features, EDin and EDun, capture the degree of closeness between the neighborhood of the word pair. It is clearly seen that the SP, EDin and EDun values are higher for co-hyponymy pairs compared to other relations and the other two features SP and SPW are comparatively lower, justifying the fact that co-hyponymy pairs are distributionally more similar and the words exist in close proximity in the DT network.