🤯 Did You Know (click to read)
BERT can identify that 'she' refers to 'Dr. Smith' earlier in the text using context embeddings.
BERT uses transformer attention mechanisms to resolve coreferences by comparing contextual embeddings of pronouns and candidate entities. Fine-tuning on annotated datasets allows the model to maintain coherence and correctly identify references across sentences and paragraphs, supporting tasks like summarization and reading comprehension.
💥 Impact (click to read)
Coreference resolution improves document understanding, dialogue systems, and content summarization by ensuring entities are tracked accurately.
For users, pronoun references appear coherent. The irony is that BERT achieves this through statistical correlations rather than comprehension of entities.
Source
Devlin et al., 2018, BERT: Pre-training of Deep Bidirectional Transformers
💬 Comments