Learning from knowledge graphs: neural fine-grained entity typing with copy-generation networks

HIGHLIGHTS

• who: Zongjian Yu et al. from the School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA have published the Article: Learning from Knowledge Graphs: Neural Fine-Grained Entity Typing with Copy-Generation Networks, in the Journal: Entropy 2022, 24, 964. of /2022/
• what: Specifically the authors propose a novel deep model called C OPY F ET for FET via a copy-generation mechanism. Since it is unknown that a certain entity mention corresponds to a certain entity in KGs, the authors propose to perform entity linking as a solution to generate the type's . . .
  

   

  

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