LinkingPark: An automatic semantic table interpretation system

Shuang Chen; Alperen Karaoglu; Carina NegreanuTingting MaJin-Ge YaoJack WilliamsFeng JiangAndy GordonChin-Yew Lin

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LinkingPark: An automatic semantic table interpretation system

机译：LinkingPark: An automatic semantic table interpretation system

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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.

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来源
《Journal of web semantics: Science, services and agents on the world wide web》 |2022年第10期|100733.1-100733.13|共13页
作者
Shuang Chen; Alperen Karaoglu; Carina NegreanuTingting MaJin-Ge YaoJack WilliamsFeng JiangAndy GordonChin-Yew Lin;
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作者单位

School of Computer Science, Harbin Institute of Technology, 150001 Harbin, China;

Microsoft Research Cambridge, Cambridge CB1 2FB, UK;

Microsoft Research Asia, 100080 Beijing, China;

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原文格式 PDF
正文语种英语
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关键词
Semantic table interpretation; Entity linking; Tabular data; Knowledge graph;

LinkingPark: An automatic semantic table interpretation system

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