[
Table 5: Comparison of the performance of the Vector Addition Baseline, Smoothed Vector Addition Baseline, and the Structured Distributional Model (SDM) on the typical items of DTFit Patients (Spearman correlations). Δ reports the SDM improvements over the basic additive models. Significance is noted with the following notation: * p<0.05.
['[BOLD] Model', '[BOLD] Additive', '[BOLD] Smoothed', '[BOLD] SDM', 'Δ']
One of our basic assumptions about gek is that semantic memory stores representations of typical events and their participants. Therefore, we expect that integrating gek into our models might lead to an improvement especially on the typical items of the DTFit dataset. Notice that this is true only for SDM, which is enriched with gek. On the other hand, the simple addition of the nearest neighbors never leads to improvements, as proved by the low correlation scores of the smoothed additive baseline. As new and larger datasets for compositionality tasks are currently under construction (Vassallo et al.