🤯 Did You Know (click to read)
BERT can connect 'Apple' in text to either the company or the fruit based on surrounding context and embeddings.
BERT generates contextual embeddings for entity mentions and compares them to candidate entities in a structured knowledge base. Fine-tuning allows it to disambiguate homonyms and identify correct references across documents. This improves search, QA, and information retrieval systems by connecting text to factual knowledge.
💥 Impact (click to read)
Entity linking enhances the discoverability and integration of information in AI systems. Applications include knowledge graphs, semantic search, and fact-checking.
For users, entity linking makes AI responses more accurate and contextually informed. The irony is that linking is achieved through statistical similarity, not true knowledge of entities.
Source
Devlin et al., 2018, BERT: Pre-training of Deep Bidirectional Transformers
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