Event Extraction by Answering (Almost) Natural Questions
Table 2: Trigger detection results.
['[EMPTY]', 'Trigger Identification P', 'Trigger Identification R', 'Trigger Identification F1', 'Trigger ID + Classification P', 'Trigger ID + Classification R', 'Trigger ID + Classification F1']
We also implement a BERT fine-tuning baseline and it reaches nearly same performance as its counterpart in the DYGIE++. We observe that our BERT_QA_Trigger model with best trigger questioning strategy reaches comparable (better) performance with the baseline models.