On such tasks, feature selection algorithms based on feature-class correlation have been very successful.
in the current problem, which we call 'semantic classification', there seem to be a fixed number of domain specific operative words such as 'grant', 'deny', 'moot', 'strike', etc., which, almost entirely decide the class of the docket entry, irrespective of the existence of other highly correlated features.