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This paper presents a meta-modelling architecture for knowledge bases (KB) -- large heterogeneous linked entity collections with millions of unique edge and node labels, often encoding rich semantic information over entities.
Abstract
Recent work on Web-extracted data sets has produced an interesting new source of structured Web data. These data sets can be viewed as knowledge bases (KB) -- large heterogeneous linked entity collections with millions of unique edge and node labels, often encoding rich semantic information over entities. For example, YAGO [5] and ExDB [2] have fact collections numbering in the tens and hundreds of millions respectfully, and WebTables [1] contains over one hundred million extracted relations. In terms of schema information, the ExDB, YAGO, and WebTables data sets all have schema items numbering in the millions.