The decrease in perplexity across the SVD dimension shows that the SVD also plays an important role and thus for SELSA it is truely a latent syntactic-semantic analysis.
if we devise an algorithm to predict the supertag of the next word with a very high accuracy, then there is a gurantee of performance improvement by this model compared to LSA.