Our input was the raw database, and our goal was to see whether we could automatically reconstruct the commonsense knowledge that the TB health care professional has.  We discovered many useful patterns, mostly ones that are known but also some new ones.  For example, gender is correlated with HIV status.  But more surprising (and more novel), it is also correlated with the type of tuberculosis.  And there are also interactions between objects.  Contacts of foreign-born patients are more likely to have TB, but are also more likely to obtain treatment, because of the tightness of the social structure.