Description:
To explore how Graph Neural Networks (GNNs) improve NLP, add a notebook that compares GNN-based models for text tasks.
Tasks:
- Compare GCN (Graph Convolutional Network), GAT (Graph Attention Network), and HGT (Heterogeneous Graph Transformer) for tasks like relation extraction, entity linking, and document classification.
- Evaluate improvements over standard transformers using accuracy and F1-score metrics.
- Summarize when GNN-based approaches are useful for NLP.
- Name the notebook gnn_nlp_comparison.ipynb.
- Update the README file with relevant references.
Description:
To explore how Graph Neural Networks (GNNs) improve NLP, add a notebook that compares GNN-based models for text tasks.
Tasks: