Persons, GLAM institutes and collections: an analysis of entity linking based on the COURAGE registry

Ghazal Faraj, A. Micsik
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引用次数: 2

Abstract

It is an important task to connect encyclopaedic knowledge graphs by finding and linking the same entity nodes. Various available automated linking solutions cannot be applied in situations where data is sparse, private or a high degree of correctness is expected. Wikidata has grown into a leading linking hub collecting entity identifiers from various registries and repositories. To get a picture of connectability, we analysed the linking methods and results between the COURAGE registry and Wikidata, VIAF, ISNI and ULAN. This paper describes our investigations and solutions while mapping and enriching entities in Wikidata. Each possible mapped pair of entities received a numeric score of reliability. Using this score-based matching method, we tried to minimise the need for human decisions, hence we introduced the term human decision window for the mappings where neither acceptance nor refusal can be made automatically and safely. Furthermore, Wikidata has been enriched with related COURAGE entities and bi-directional links between mapped persons, organisations, collections, and collection items. We also describe the findings on coverage and quality of mapping among the above mentioned authority databases.
个人、GLAM机构和收藏:基于COURAGE登记的实体链接分析
通过查找和链接相同的实体节点来实现百科知识图谱的连接是一项重要的任务。在数据稀疏、私有或要求高度正确的情况下,各种可用的自动链接解决方案都无法应用。Wikidata已经成长为一个领先的链接中心,从各种注册中心和存储库收集实体标识符。为了获得可连接性的图像,我们分析了COURAGE注册表与Wikidata、VIAF、ISNI和ULAN之间的链接方法和结果。本文描述了我们在绘制和丰富维基数据中的实体时所做的研究和解决方案。每个可能映射的实体对都获得了可靠性的数字分数。使用这种基于分数的匹配方法,我们试图最大限度地减少对人工决策的需求,因此我们为无法自动安全地接受或拒绝的映射引入了术语“人工决策窗口”。此外,维基数据还被相关的COURAGE实体和映射的人员、组织、集合和集合项目之间的双向链接所丰富。我们还描述了在上述权威数据库中映射的覆盖率和质量的发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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