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Knowledge is indispensable to understanding. The ongoing information explosion highlights the need to enable machines to better understand electronic text in human language. Much work has been devoted to creating universal ontologies or taxonomies for this purpose. However, none of the existing ontologies has the needed depth and breadth for "universal understanding". In this paper, we present a universal, probabilistic taxonomy that is more comprehensive than any existing ones. It contains 2.7doi:10.1145/2213836.2213891 dblp:conf/sigmod/WuLWZ12 fatcat:a3hxdjakvbb25jobkhcxhkangm