Learning to Explain Entity Relationships in Knowledge Graphs

We study the problem of explaining relationships between pairs of knowledge graph entities with human-readable descriptions. Our method extracts and enriches sentences that refer to an entity pair from a corpus and ranks the sentences according to how well they describe the relationship between the entities. We model this task as a learning to rank problem for sentences and employ a rich set of features. When evaluated on a large set of manually annotated sentences, we find that our method significantly improves over state-of-the-art baseline models.

• Type: Journal
• Year: 2015
• Where: ACL
• Authors: Nikos Voskarides, Edgar Meij, Manos Tsagkias, Maarten de Rijke, Wouter Weerkamp
• Keywords: ACL 2015, Computational Linguistics