Syntax-aware Multilingual Semantic Role Labeling
Table 2: Precision, recall and semantic F1-score on CoNLL-2009 English in-domain data and Chinese test set.
['Model', 'English P', 'English R', 'English F1', 'Chinese P', 'Chinese R', 'Chinese F1']
Our baseline is a modification to the model of Cai et al. For English, our baseline gives slightly weaker performance than the work of Li et al. Our model with the proposed argument pruning layer (+ AP) brings absolute improvements of 0.35% and 0.5% F1 on English and Chinese, respectively, which is on par with the best published scores. Moreover, we introduce deep enhanced representation based on the argument pruning. Our model utilizing BERT (+ AP + BERT) achieves the new best results on English and Chinese benchmarks.