1. A method for transforming unstructured text into structured data using a domain-specific ontology, the method comprising: recording the unstructured text using an information extraction module (IEM); discovering text phrases contained in the recorded unstructured text via the IEM; retrieving lexical data from a knowledge source using the IEM and the discovered text phrases; processing each of the discovered text phrases and the lexical data using the IEM to thereby generate a plurality of nodes in the domain-specific ontology, wherein each of the plurality of nodes represents a corresponding single concept as a cluster of synonyms; using the plurality of generated nodes to classify the discovered text phrases by corresponding objects of interest, thereby transforming the unstructured text into structured data; generating a list of sub-phrases of the discovered text phrases; mapping each sub-phrase in the generated list of sub-phrases into the domain-specific ontology via the IEM; using an informativeness function to quantify each of the sub-phrases of the discovered text phrases by a normalized relative importance informativeness score of between 0 and 1; and eliminating all sub-phrases from the domain-specific ontology that have an informativeness score that is less than a calibrated threshold.