Downstream Model Design of Pre-trained Language Model for Relation Extraction Task
Table 3: Micro-F1 scores of our method tested on multiple datasets, compared with other four baseline methods. The first two methods are GNN-based while the last two are PLM-based. Their performances come from their original papers, as quoted above.
['[BOLD] Methods', '[BOLD] SemEval', '[BOLD] NYT', '[BOLD] WebNLG']
Given different test settings, we find that our model generally outperformed the baseline models, with a margin over the optimal baseline ranging from 1% to 8%.