Improving Entity Linking by Modeling Latent Entity Type Information
Table 3: Results of type classification task on three typing systems: FIGER, BBN, OntoNotesfine
['Entity Embedding', 'FIGER  [ITALIC] F1mi', 'FIGER  [ITALIC] F1ma', 'FIGER Acc.', 'BBN  [ITALIC] F1mi', 'BBN  [ITALIC] F1ma', 'BBN Acc.', 'OntoNotesfine  [ITALIC] F1mi', 'OntoNotesfine  [ITALIC] F1ma', 'OntoNotesfine Acc.']
Specifically, our method improves over the baseline with an absolute 8.31, 10.43 and 9.33 F1mi point than the baseline on three typing systems respectively. This demonstrates that our proposed entity embeddings from BERT indeed capture better latent entity type information than \citeauthorganea2017deep \shortciteganea2017deep.