This paper describes our participation in the Triple Scoring task of WSDM Cup 2017, which aims at ranking triples from a knowledge base for two type-like relations: profession and nationality. We introduce a supervised ranking method along with the features we designed for this task. Our system has been top ranked with respect to average score difference and 2nd best in terms of Kendall's tau.
翻译:本文介绍我们参与2017年WSDM杯三分赛任务的情况,其目的是从知识库中为两种类型的关系(专业和国籍)排列三分之一:职业和国籍。我们采用了监督排名的方法以及我们为这项任务设计的特点。我们的系统在平均得分差异方面排名最高,在肯德尔的塔乌方面排名第二。