1. A method of semantically classifying numeric data of a data source including numeric data sets and non-numeric data sets, the method comprising: loading, by a processing device, a data source comprising numeric data and non-numeric data; extracting, by the processing device, one or more open class nouns from at least one non-numeric data set of the data source, the one or more open class nouns being in a proximity to the numeric data set of the data source; determining, by the processing device, at least one semantic classification for the non-numeric data set of the data source using a semantic classification technique; extracting, by the processing device, one or more number values from at least one numeric data set of the data source; querying, by the processing device, an EKB to determine if the semantic classification for the non-numeric data set and one or more number values of the numeric data set exist in the EKB and, if so, querying the EKB based on the at least one semantic classification of the non-numeric data set and one or more number values of the numeric data set to retrieve one or more results corresponding to each of the number values of the numeric data set, the one or more results including a property and a value; comparing, by the processing device, each value returned by the EKB against a corresponding number value from the numerical data set; applying an acceptable tolerance in which to consider a respective value returned from the EKB to match a respective number value of the numerical data set, deriving, by the processing device, a confidence score for the numeric data set based on the one or more results; and determining, by the processing device, at least one classification for the numerical data set based on the confidence score.