Knowledge Enhanced Contextual Word Representations
Table 3: End-to-end entity linking strong match, micro averaged F1.
['System', 'AIDA-A', 'AIDA-B']
Here, KnowBert’s performance lags behind the current state-of-the-art model from Kolitsas et al. Daiber et al. We believe this is due to the selective annotation in the AIDA data that only annotates named entities. The CrossWikis-based candidate selector used in KnowBert generates candidate mentions for all entities including common nouns from which KnowBert may be learning to extract information, at the detriment of specializing to maximize linking performance for AIDA.