The NSQA system proposed by Kapanipathi et al. (2020) operates via the following procedure: (1) convert natural language questions into Abstract Meaning Representation (AMR) graphs using explicit linguistic rules, (2) use a neural network model to identify and link entities and relationships to a knowledge base, (3) convert the resulting representation into logical queries, and (4) use a Logical Neural Network reasoner to infer based on the execution of those queries.

Authors

• Person: Not available Organization: arXiv
  Neuro-Symbolic AI: Explainability, Challenges, and Future Trends

Sources

• Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv via serper

Referenced by nodes (2)

• artificial neural networks concept
• Logical Neural Networks concept