Coreferential Reasoning Learningfor Language Representation
Table 3: Results on DocRED measured by micro ignore F1 (IgnF1) and micro F1. IgnF1 metrics ignores the relational facts shared by the training and dev/test sets. Results with ∗, +, # are from Yao et al. (2019), Wang et al. (2019),Tang et al. (2020) respectively.
['Model', 'Dev IgnF1', 'Dev F1', 'Test IgnF1', 'Test F1']
CorefBERTBase outperforms BERTBase model by 0.7% F1. CorefRoBERTaLarge beats RoBERTaLarge by 0.3% F1 and outperforms all previous published work. It proves the effectiveness of considering coreference information of text for document-level relation classification.