Data Augmentation for Hypernymy Detection
Table 2: Accuracy scores for the data augmentation and the two dataset extension strategies in comparison to the same FF model without any augmentation or extension.
['[BOLD] Model', '[BOLD] Weeds', '[BOLD] LEDS', '[BOLD] HP4K']
Our techniques are able to outperform a non-augmented model by 4-6 points in accuracy, representing a relative error reduction of 14%-26%. While the primary objective in this work is to improve an existing model setup with data augmentation, our augmented models compare favourably with previously published results.