Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs
Table 6: Effects of the vocabulary sharing and length penalty on the test sets of AGENDA and WebNLG.
['[BOLD] AGENDA  [BOLD] Model', '[BOLD] AGENDA  [BOLD] BLEU', '[BOLD] AGENDA  [BOLD] CHRF++']
S5SS7SSS0Px1 Impact of the Vocabulary Sharing and Length Penalty. During the ablation studies, we note that the vocabulary sharing and length penalty are beneficial for the performance. To better estimate their impact, we evaluate CGE-LW model with its variations without employing vocabulary sharing, length penalty and without both mechanisms, on the test set of both datasets. We observe that sharing vocabulary is more important to WebNLG than AGENDA. This suggests that sharing vocabulary is beneficial when the training data is small, as in WebNLG.