Papers with BERT-based neural-symbolic architecture

1 papers
Event Semantic Knowledge in Procedural Text Understanding (2023.starsem-1)

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Challenge: Annotators’ reliance on commonsense knowledge to annotate implicit state information is a challenge for entity state tracking.
Approach: They propose a method for entity state tracking that incorporates commonsense entity-centric knowledge from ConceptNet into a BERT-based neural-symbolic architecture.
Outcome: The proposed model outperforms existing models on the ProPara dataset and is domain-agnostic.

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