EAGER: Explainable Question Answering Using Knowledge Graphs

Abstract

We present EAGER: a tool for answering questions expressed in natural language. Core to EAGER is a modular pipeline for generating a knowledge graph from raw text without human intervention. Notably, EAGER uses the knowledge graph to answer questions and to explain the reasoning behind the derivation of answers. Our demonstration will showcase both the automated knowledge graph generation pipeline and the explainable question answering functionality. Lastly, we outline open problems and directions for future work.