论文标题
Wikidata中的常识知识
Commonsense Knowledge in Wikidata
论文作者
论文摘要
Wikidata和Wikipedia已被证明对自然语言应用中的理性有用，例如回答或实体链接。然而，没有现有的工作研究Wikidata对常识性推理的潜力。本文调查了Wikidata Conains常识性知识是否与现有常识来源相辅相成。从常识的定义开始，我们就设计了三个指导原则，并将其应用于Wikidata（Wikidata-CS）的常识子图。在我们的方法中，我们将Wikidata与ConceptNet的关系绘制在一起，我们还利用将Wikidata-CS整合到现有的合并常识图中。我们的实验表明：1）尽管Wikidata-cs代表了Wikidata的一小部分，但它表明Wikidata包含相关的常识知识，可以将其映射到15个概念网络关系； 2）Wikidata-CS和其他常识来源之间的重叠很低，激发了知识整合的价值； 3）Wikidata-CS随着时间的推移与整体Wikidata相比，速度略慢，这表明可能缺乏对常识性知识的关注。根据这些发现，我们提出了三个建议的行动，以进一步提高Wikidata-CS的覆盖范围和质量。
Wikidata and Wikipedia have been proven useful for reason-ing in natural language applications, like question answering or entitylinking. Yet, no existing work has studied the potential of Wikidata for commonsense reasoning. This paper investigates whether Wikidata con-tains commonsense knowledge which is complementary to existing commonsense sources. Starting from a definition of common sense, we devise three guiding principles, and apply them to generate a commonsense subgraph of Wikidata (Wikidata-CS). Within our approach, we map the relations of Wikidata to ConceptNet, which we also leverage to integrate Wikidata-CS into an existing consolidated commonsense graph. Our experiments reveal that: 1) albeit Wikidata-CS represents a small portion of Wikidata, it is an indicator that Wikidata contains relevant commonsense knowledge, which can be mapped to 15 ConceptNet relations; 2) the overlap between Wikidata-CS and other commonsense sources is low, motivating the value of knowledge integration; 3) Wikidata-CS has been evolving over time at a slightly slower rate compared to the overall Wikidata, indicating a possible lack of focus on commonsense knowledge. Based on these findings, we propose three recommended actions to improve the coverage and quality of Wikidata-CS further.
