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The Web stores a large volume of web-tables with semi-structured data. The Semantic Web community considers them as a valuable source for the knowledge graph population. Interrelated named entities can be extracted from web-tables and mapped to a knowledge graph. It generally requires reconstructing the semantics missing in web-tables to interpret them according to their meaning. This paper discusses prospects of an end-to-end solution for the knowledge graph population by entities extracteddoi:10.6084/m9.figshare.16621528.v1 fatcat:gwhxeemhqvds7d54dykreqez3a