BLINK: Better entity LINKing
Entity Linking python library that uses Wikipedia as the target knowledge base.
named-entity-recognition wikification natural-language-processing code research paper library arxiv:1911.03814

In a nutshell, BLINK uses a two stage approach for entity linking, based on fine-tuned BERT architectures. In the first stage, BLINK performs retrieval in a dense space defined by a bi-encoder that independently embeds the mention context and the entity descriptions. Each candidate is then examined more carefully with a cross-encoder, that concatenates the mention and entity text. BLINK achieves state-of-the-art results on multiple datasets.

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