Knowledge bases play a crucial role in modern search engines and provide users with information about entities. A knowledge base may contain many facts (i.e., RDF triples) about an entity, but only a handful of them are of significance for a searcher. Identifying and ranking these RDF triples is essential for various applications of search engines, such as entity ranking and summarization. In this paper, we present the first effort towards a unified supervised approach to rank triples from various type-like relations in knowledge bases. We evaluate our approach using the recently released test collections from the WSDM Cup 2017 and demonstrate the effectiveness of the proposed approach despite the fact that no relation-specific feature is used.
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机译：知识库在现代搜索引擎中扮演着至关重要的角色，并为用户提供有关实体的信息。知识库可能包含有关实体的许多事实（即RDF三元组），但其中只有少数对搜索者有意义。对这些RDF三元组进行标识和排名对于搜索引擎的各种应用（例如实体排名和摘要）至关重要。在本文中，我们提出了第一个尝试，以统一的监督方法对知识库中各种类型关系中的三元组进行排序。我们使用WSDM Cup 2017的最新发布的测试集评估了我们的方法，并证明了该方法的有效性，尽管事实是未使用任何关系特定的功能。
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