A method, system and computer-usable medium are disclosed for automating the generation of an incorrect answer to a question suitable for a multiple choice exam. An input corpus of human-readable text associated with a subject domain is provided to a question generation system, where it is processed to generate a set of question-answer (QA) pairs. The set of QA pairs is then processed with the corpus of input text to extract a set of input keywords and concepts. A concept dependency graph is then used to perform disambiguation operations on the set of input keywords and concepts, and the reference keywords and concepts it contains, to generate a set of distractor words. The resulting set of distractor words is then processed with the set of QA pairs to generate a set of multiple choice question-answers that include various distractor answers.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method for automating the generation of an incorrect answer to a question suitable for a multiple choice exam, comprising: receiving an input corpus associated with a subject domain; processing the input corpus to generate question-answer (QA) pairs; processing the input corpus and the QA pairs to extract a set of input keywords and concepts; performing disambiguation operations on the set of input keywords and concepts, and reference keywords and concepts, to generate a set of distract or words; and processing the set of distract or words with the QA pairs to generate a set of multiple choice question-answers containing a set of distract or answers. 2. The method of claim 1, wherein: the reference keywords and concepts are associated with the subject domain and are stored in a concept dependency graph. 3. The method of claim 2, wherein: a reference corpus containing the reference keywords and concepts associated with the subject domain is used to generate the concept dependency graph. 4. The method of claim 2, wherein: the distract or words are located in the concept dependency graph and not in the input corpus. 5. The method of claim 1, further comprising: eliminating individual multiple choice question-answers in the set of multiple choice question-answers according to a question quality criteria based upon aspects selected from a group consisting of specificity, context, and ambiguity. 6. The method of claim 1, wherein the input corpus includes at least one of the set of a text, an image, video content, and audio content. 7. A system comprising: a processor; a data bus coupled to the processor; and a computer-usable medium embodying computer program code, the computer-usable medium being coupled to the data bus, the computer program code used for automating the generation of an incorrect answer to a question suitable for a multiple choice exam and comprising instructions executable by the processor and configured for: receiving an input corpus associated with a subject domain; processing the input corpus to generate question-answer (QA) pairs; processing the input corpus and the QA pairs to extract a set of input keywords and concepts; performing disambiguation operations on the set of input keywords and concepts, and reference keywords and concepts, to generate a set of distract or words; and processing the set of distract or words with the QA pairs to generate a set of multiple choice question-answers containing a set of distract or answers. 8. The system of claim 7, wherein: the reference keywords and concepts are associated with the subject domain and are stored in a concept dependency graph. 9. The system of claim 8, wherein: a reference corpus containing the reference keywords and concepts associated with the subject domain is used to generate the concept dependency graph. 10. The system of claim 8, wherein: the distract or words are located in the concept dependency graph and not in the input corpus. 11. The system of claim 7, further comprising: eliminating individual multiple choice question-answers in the set of multiple choice question-answers according to a question quality criteria based upon aspects selected from a group consisting of specificity, context, and ambiguity. 12. The system of claim 7, wherein the input corpus includes at least one of the set of a text, an image, video content, and audio content. 13. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for: receiving an input corpus associated with a subject domain; processing the input corpus to generate question-answer (QA) pairs; processing the input corpus and the QA pairs to extract a set of input keywords and concepts; performing disambiguation operations on the set of input keywords and concepts, and reference keywords and concepts, to generate a set of distract or words; and processing the set of distract or words with the QA pairs to generate a set of multiple choice question-answers containing a set of distract or answers. 14. The non-transitory, computer-readable storage medium of claim 13, wherein: the reference keywords and concepts are associated with the subject domain and are stored in a concept dependency graph. 15. The non-transitory, computer-readable storage medium of claim 14, wherein: a reference corpus containing the reference keywords and concepts associated with the subject domain is used to generate the concept dependency graph. 16. The non-transitory, computer-readable storage medium of claim 14, wherein: the distract or words are located in the concept dependency graph and not in the input corpus. 17. The non-transitory, computer-readable storage medium of claim 13, further comprising: eliminating individual multiple choice question-answers in the set of multiple choice question-answers according to a question quality criteria based upon aspects selected from a group consisting of specificity, context, and ambiguity. 18. The non-transitory, computer-readable storage medium of claim 13, wherein the input corpus includes at least one of the set of a text, an image, video content, and audio content. 19. The non-transitory, computer-readable storage medium of claim 13, wherein the computer executable instructions are deployable to a client system from a server system at a remote location. 20. The non-transitory, computer-readable storage medium of claim 13, wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis.