Modeling Graph Structure in Transformerfor Better AMR-to-Text Generation
Table 2: Ablation results of our baseline system on the LDC2015E86 development set.
['[BOLD] Model', '[BOLD] BLEU', '[BOLD] Meteor', '[BOLD] CHRF++']
We first show the performance of our baseline system. As mentioned before, BPE and sharing vocabulary are two techniques we applied to relieving data sparsity. From the results we can see that BPE and vocabulary sharing are critical to building our baseline system (an improvement from 18.77 to 24.93 in BLEU), revealing the fact that they are two effective ways to address the issue of data sparseness for AMR-to-text generation.