In this paper, we present LinkingPark, our system for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020). LinkingPark is an integrated approach for semantic table interpretation. Our system includes a cascaded pipeline for candidate generation, an iterative coarse-to-fine entity disambiguation algorithm, a multi-pass property linking algorithm, and a type inference algorithm tackling the issue of loose ontology in Wikidata. Results on SemTab 2020 demonstrate the effectiveness of our approach.<\/p>\n","protected":false},"excerpt":{"rendered":"
In this paper, we present LinkingPark, our system for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2020). LinkingPark is an integrated approach for semantic table interpretation. Our system includes a cascaded pipeline for candidate generation, an iterative coarse-to-fine entity disambiguation algorithm, a multi-pass property linking algorithm, and a type inference algorithm 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