Reasoning with Language Models and Knowledge Graphs for Question Answering

Approach We design an end-to-end question answering model that uses a pre-trained LM and KG. First, as commonly done in existing systems, we use an LM to obtain a vector representation for the QA context, and retrieve a KG subgraph by entity linking.