10. A computer-implemented method, comprising: receiving extraction patterns from a repository of extraction patterns; applying the extraction patterns to document text of one or more documents to derive a plurality of candidate class-instance pairs in the document text, wherein each candidate class-instance pair comprises a candidate class name and a candidate instance name derived by matching at least one of the extraction patterns to document text including the candidate class name and the candidate instance name; determining a frequency score and a diversity score for each candidate class-instance pair, wherein the frequency score relates to a frequency with which the class-instance pair was derived and the diversity score relates to a number of distinct extraction patterns that matched document text including the candidate class name and the candidate instance name of the candidate class-instance pair; and determining a pair score for each candidate class-instance pair in the plurality of candidate class-instance pairs from the frequency score and the diversity score, wherein determining the pair score comprises multiplying the frequency score by the diversity score.
13. The method of claim 10 , further comprising deriving the pair score for a candidate class-instance pair from a respective weight associated with each extraction pattern used to derive the candidate class-instance pair.