4. The method of claim 1 , wherein evaluating the activation network with regard to the chosen NLP task comprises performing differential analysis of characteristics of nodes in the model that are determined to be relatively higher performing in the activation network and nodes in the model that are determined to be relatively lower performing in the activation network.
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.