In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation (CTA), and Columns-Property Annotation (CPA) altogether. It is built upon our previous SemTab 2020 system, which won the 2nd prize among 28 different teams after four rounds of evaluations. Moreover, the system is unsupervised, stand-alone, and flexible for multilingual support. Its backend offers an efficient RESTful API for programmatic access, as well as an Excel Add-in for ease of use. Users can interact with LinkingPark in near real-time, further demonstrating its efficiency.

在本文中，我们提出了 LinkingPark，一种用于表格数据与知识图匹配的自动语义标注系统。LinkingPark 被设计为一个模块化框架，可以同时处理单元实体注释 (CEA)、列类型注释 (CTA) 和列属性注释 (CPA)。它建立在我们之前的 SemTab 2020 系统之上，该系统经过四轮评估，在 28 个不同的团队中获得了二等奖。此外，该系统是无监督的、独立的，并且可以灵活地支持多语言。它的后端为编程访问提供了一个高效的 RESTful API，以及一个易于使用的 Excel 插件。用户可以近乎实时地与 LinkingPark 进行交互，进一步展示了它的效率。