While LLMs excel at token synthesis and linguistic fluency, Graph Neural Networks (GNNs) specialize in topological message passing, link prediction, and neighborhood aggregation. By feeding GNN subgraph node embeddings directly into the cross-attention layers of LLMs, we produce models that understand both lexical nuance and global network topology.