Deep Structured Neural Network for Event Temporal Relation Extraction
Table 9: Ablation over word representation: BERT vs GloVe. Although BERT representation largely contributes to the performance boost, our proposed framework remains strong and outperforms current SOTA approaches when GloVe is used.
['[EMPTY]', 'previous SOTA', 'local- Glove', 'global- Glove', 'local- BERT', 'global- BERT']
In this section, we explore the impact of contextualized BERT representations under our deep SSVM framework. We replace BERT representations with the GloVe Pennington et al. BERT improves the performance with a significant margin. Besides, even without BERT representations, our RNN-based local model and the deep structured global model still outperform (MATRES and TCR) or are comparable with (TB-Dense) current SOTA. These results confirm the improvements of our method.