Improving Relation Extraction by Pre-trained Language Representations
Table 8: TACRED validation F1 scores for TACRED with different entity masking strategies.
['Entity Masking', 'Precision', 'Recall', 'F1']
It can be used to simulate different scenarios, such as the presence of unseen entities, to prevent overfitting to specific entity mentions, and to focus more on context. As we saw previously, masking with entity and grammatical role information yields the best overall performance, yielding a F1 score of 68.0. We find that using different masking strategies mostly impacts the recall, while precision tends to remain high, with the exception of the UNK masking strategy.