Modeling Semantic Relatedness using Global Relation Vectors
Table 4: Results without the relation vectors sik and tik.
['[EMPTY]', 'Google Acc', 'Google F1', 'DiffVec Acc', 'DiffVec F1']
Similar as in the GloVe model, the context words in our model are weighted based on their distance to the nearest target word. While including the vectors sik, ski, tik, tki should be helpful, it also significantly increases the dimensionality of the vectors Rlik. Given that the number of instances per relation is typically quite small for this task, this can also make it harder to learn a suitable classifier.