A question answering system that determines whether a question is off-topic by performing the following steps: (i) receiving, by a question answering system, a set of documents; (ii) identifying topical subset(s) for each document of the set of documents using named entity recognition, where each topical subset relates to a corresponding topic; (iii) assigning a set of topic score(s) for each topical subset using natural language processing, where each topic score relates to a corresponding probability associated with the respective topical subset under a probabilistic language model; and (iv) determining, based, at least in part, on the topic score(s) corresponding to the topical subset(s), whether a question input into the question answering system is off-topic.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-9. (canceled) 10. A computer program product comprising a computer readable storage medium having stored thereon: first program instructions programmed to receive, by a question answering system, a set of documents; second program instructions programmed to identify topical subset(s) for each document of the set of documents using named entity recognition, where each topical subset relates to a corresponding topic; third program instructions programmed to assign a set of topic score(s) for each topical subset using natural language processing, where each topic score relates to a corresponding probability associated with the respective topical subset under a probabilistic language model; and fourth program instructions programmed to determine, based, at least in part, on the topic score(s) corresponding to the topical subset(s), whether a question input into the question answering system is off-topic. 11. The computer program product of claim 10, wherein each set of topic scores includes an on-topic score and an off-topic score, the on-topic score relating to a probability associated with the respective topical subset under an on-topic probabilistic language model, and the off-topic score relating to a probability associated with the respective topical subset under an off-topic probabilistic language model. 12. The computer program product of claim 10, wherein the determining includes assigning a topic score to the question input into the question answering system. 13. The computer program product of claim 12, wherein the topic score assigned to the question is determined, at least in part, by using a sigmoid function to model the difference between a logarithm probability associated with the question under the on-topic probabilistic language model and a logarithm probability associated with the question under the off-topic probabilistic language model. 14. The computer program product of claim 12, wherein the determining further includes comparing the question's assigned topic score to a relevance score associated with an answer generated by the question answering system in response to the question. 15. The computer program product of claim 14, wherein: the question is determined to be off-topic if the question's assigned topic score is greater than the generated answer's associated relevance score; and the question is determined to be on-topic if the question's assigned topic score is less than the generated answer's associated relevance score. 16. A computer system comprising: a processor(s) set; and a computer readable storage medium; wherein: the processor set is structured, located, connected and/or programmed to run program instructions stored on the computer readable storage medium; and the program instructions include: first program instructions programmed to receive, by a question answering system, a set of documents; second program instructions programmed to identify topical subset(s) for each document of the set of documents using named entity recognition, where each topical subset relates to a corresponding topic; third program instructions programmed to assign a set of topic score(s) for each topical subset using natural language processing, where each topic score relates to a corresponding probability associated with the respective topical subset under a probabilistic language model; and fourth program instructions programmed to determine, based, at least in part, on the topic score(s) corresponding to the topical subset(s), whether a question input into the question answering system is off-topic. 17. The computer system of claim 16, wherein each set of topic scores includes an on-topic score and an off-topic score, the on-topic score relating to a probability associated with the respective topical subset under an on-topic probabilistic language model, and the off-topic score relating to a probability associated with the respective topical subset under an off-topic probabilistic language model. 18. The computer system of claim 16, wherein the determining includes assigning a topic score to the question input into the question answering system. 19. The computer system of claim 18, wherein the topic score assigned to the question is determined, at least in part, by using a sigmoid function to model the difference between a logarithm probability associated with the question under the on-topic probabilistic language model and a logarithm probability associated with the question under the off-topic probabilistic language model. 20. The computer system of claim 18, wherein: the determining further includes comparing the question's assigned topic score to a relevance score associated with an answer generated by the question answering system in response to the question; the question is determined to be off-topic if the question's assigned topic score is greater than the generated answer's associated relevance score; and the question is determined to be on-topic if the question's assigned topic score is less than the generated answer's associated relevance score.