Entity, Relation, and Event Extraction with Contextualized Span Representations
Table 6: Effect of BERT cross-sentence context. F1 score of relation F1 on ACE05 dev set and entity, arg, trigger extraction F1 on ACE05-E test set, as a function of the BERT context window size.
['Task', 'Variation', '1', '3']
Table 6 shows that both variations of our BERT model benefit from wider context windows. Our model achieves the best performance with a 3sentence window across all relation and event extraction tasks.