Efficient Retrieval of Knowledge Graph Fact Evidences

Dhruv Gupta, Klaus Berberich

Abstract: We report preliminary results on the problem of efficient retrieval of evidences for knowledge graph (KG) facts from large document collections. KGs are rich repositories of human knowledge and real-world events. To verify and validate facts about entities, it is often required to spot their evidences in large news archives or on the Web. To do so, KG facts can be translated to their natural language equivalent by using surface forms. Naïvely, attempting to search for all combinations of the aliases in large document collections is a time-consuming solution. We show that by using a combination of inverted indexes over n-grams and skip-grams we can return evidences in the form of sentences for KG facts within seconds.