Extracting Multiple-Relations in One-Pass with Pre-Trained Transformers
Table 1: Main Results on ACE 2005.
['[BOLD] Method', '[BOLD] dev', '[BOLD] bc', '[BOLD] cts', '[BOLD] wl', '[BOLD] avg']
The first observation is that our model architecture achieves much better results compared to the previous state-of-the-art methods. Note that our method was not designed for domain adaptation, it still outperforms those methods with domain adaptation. This result further demonstrates its effectiveness. Therefore, we compare the same methods when applied to the multi-relation and single-relation settings. For BERTSP with entity indicators on inputs, it is expected to perform slightly better in the single-relation setting, because of the mixture of information from multiple pairs. A 2% gap is observed as expected. By comparison, our full model has a much smaller performance gap between two different settings (and no consistent performance drop over different domains).