Entity Enabled Relation Linking

Abstract

Relation linking is an important problem for knowledge graph-based Question Answering. Given a natural language question and a knowledge graph, the task is to identify relevant relations from the given knowledge graph. Since existing techniques for entity extraction and linking are more stable compared to relation linking, our idea is to exploit entities extracted from the question to support relation linking. In this paper, we propose a novel approach, based on DBpedia entities, for computing relation candidates. We have empirically evaluated our approach on different standard benchmarks. Our evaluation shows that our approach significantly outperforms existing baseline systems in both recall, precision and runtime.