7. A database-building data processing system configured for building an analysis database associating each of a plurality of n-grams with corresponding respective cognitive motivation orientations, the system comprising: a host computer with memory and at least one processor coupled to the memory; and a database-building module, the database-building module comprising program code that, when executed in the memory of the host computer: receives a training corpus of training documents, wherein: each training document comprises a plurality of meaningfully arranged words in electronic form; each training document has at least one annotated word sequence therein; wherein within each training document, each particular annotated word sequence is annotated with a corresponding word-sequence-level annotation identifying at least one cognitive motivation orientation that is associated with that particular annotated word sequence; for each training document: for each annotated word sequence in that particular training document: extracts n-grams overlapping that particular annotated word sequence; and associates each extracted n-gram with the at least one cognitive motivation orientation associated with that particular annotated word sequence; generates a set of indicator candidate n-grams wherein: each indicator candidate n-gram represents all instances of a particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; each indicator candidate n-gram being associated with every cognitive motivation orientation that is associated with at least one instance of the particular n-gram represented by that particular indicator candidate n-gram; applies at least one relevance filter to each indicator candidate n-gram in the set of indicator candidate n-grams to obtain a set of indicator n-grams, wherein; the set of indicator n-grams is a subset of the set of indicator candidate n-grams, so that each indicator n-gram corresponds to only one indicator candidate n-gram and thereby each indicator n-gram represents all instances of a corresponding particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; and each indicator n-gram is associated with only a single cognitive motivation orientation; wherein each indicator n-gram has, as its associated single cognitive motivation orientation, that single cognitive motivation orientation with which the instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated; permitting the analysis database to support enhanced computer-implemented neurolinguistic analysis of a text sequence to identify cognitive motivation orientations expressed within the text sequence quickly, objectively and consistently.
7. A database-building data processing system configured for building an analysis database associating each of a plurality of n-grams with corresponding respective cognitive motivation orientations, the system comprising: a host computer with memory and at least one processor coupled to the memory; and a database-building module, the database-building module comprising program code that, when executed in the memory of the host computer: receives a training corpus of training documents, wherein: each training document comprises a plurality of meaningfully arranged words in electronic form; each training document has at least one annotated word sequence therein; wherein within each training document, each particular annotated word sequence is annotated with a corresponding word-sequence-level annotation identifying at least one cognitive motivation orientation that is associated with that particular annotated word sequence; for each training document: for each annotated word sequence in that particular training document: extracts n-grams overlapping that particular annotated word sequence; and associates each extracted n-gram with the at least one cognitive motivation orientation associated with that particular annotated word sequence; generates a set of indicator candidate n-grams wherein: each indicator candidate n-gram represents all instances of a particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; each indicator candidate n-gram being associated with every cognitive motivation orientation that is associated with at least one instance of the particular n-gram represented by that particular indicator candidate n-gram; applies at least one relevance filter to each indicator candidate n-gram in the set of indicator candidate n-grams to obtain a set of indicator n-grams, wherein; the set of indicator n-grams is a subset of the set of indicator candidate n-grams, so that each indicator n-gram corresponds to only one indicator candidate n-gram and thereby each indicator n-gram represents all instances of a corresponding particular n-gram in the training corpus for which at least one instance of that particular n-gram was extracted from any annotated word sequence in any training document; and each indicator n-gram is associated with only a single cognitive motivation orientation; wherein each indicator n-gram has, as its associated single cognitive motivation orientation, that single cognitive motivation orientation with which the instances of the particular n-gram represented by that particular indicator n-gram are most frequently associated; permitting the analysis database to support enhanced computer-implemented neurolinguistic analysis of a text sequence to identify cognitive motivation orientations expressed within the text sequence quickly, objectively and consistently. 9. The data processing system of claim 7 , wherein the database-building module further comprises program code that, when executed in the memory of the host computer, assigns a confidence weight to each indicator n-gram.