1. A method, in a data processing system comprising a processor and a memory, for modifying an ontology for use with a natural language processing (NLP) task, the method comprising: obtaining, by the data processing system, a model of the ontology, wherein the model of the ontology comprises nodes representing concepts of the ontology and edges between nodes representing relationships between associated nodes of the ontology; performing, by the data processing system, a spreading activation operation on the model of the ontology, wherein the spreading activation operation matches a portion of a textual source to a matching node of the model and identifies related nodes to the matching node through edges of the model associated with the matching node to thereby generate an activation network; evaluating, by the data processing system, the activation network with regard to a chosen NLP task to determine a performance metric for the NLP task associated with the nodes of the model; and in response to results of the evaluating indicating that performance of a node does not meet a desired performance for the NLP task, modifying at least one of the model or a configuration of the activation network based on results of the evaluation of the activation network.
9. The method of claim 1 , wherein the performance metric for the NLP task comprises at least one of a precision metric, a recall metric, an F-measure metric, or an accuracy metric.