Deep Semantic Role Labeling with Self-Attention
Table 6: Comparison with the previous work on identifying and classifying semantic roles. We list the percentage of correctly identified spans as well as the percentage of correctly classified semantic roles given the gold spans.
['Model', 'Constituents', 'Semantic Roles']
Detailed Scores Compared with He et al. \shortcitehe2017deep, our model shows improvement on all labels except AM-PNC, where He’s model performs better. Our model improves the previous state-of-the-art on both identifying correct spans as well as correctly classifying them into semantic roles. However, the majority of improvements come from classifying semantic roles. This indicates that finding the right constituents remains a bottleneck of our model.