11. A computer system comprising: one or more computer processors; one or more computer readable storage media; computer program instructions; and said computer program instructions being stored on said computer readable storage media for execution by at least one of said one or more processors, said computer program instructions comprising instructions to: receive a question, said question being directed to a domain-specific question answering system, wherein said question is requesting at least two distinct pieces of information; extract two or more distinct queries from said question, based on a query decomposing rule library by comparing said question to said query decomposing rule library to identify a matching decomposition rule, wherein said comparing includes using an index scan, using a keyword scan, parsing said query decomposing rule library, and using a segment scan, wherein said query decomposing rule library includes combinations of semantic, syntactic, grammatical, structural, and other predetermined rules for identifying distinct queries within said question; generate two or more question sets, each of said two or more question sets addressing all of said two or more queries, wherein said generated two or more questions sets are expressed in a language and format that said question answering system can interpret and process, wherein both said first question set and said second question set include at least one question for each of said two or more queries extracted from said question, and wherein said second question set includes at least one question different from said first question set; select one of said two or more question sets to yield a selected question set, based on analyzing each of said two or more question sets according to a pre-trained model, wherein said pre-trained model is a term vector model, wherein said term vector model is an algebraic model for representing elements within a text document as vectors and generates a number of dimensions based on keywords, terms, and elements within said extracted queries, wherein said two or more question sets are selected based on a first optimal score, wherein said first optimal score is based on a number of specific terms and irrelevant terms in questions in each said two or more question sets, and wherein said irrelevant terms lower said first optimal score; present said selected question set to said question answering system and a user; determine at least one answer set for said selected question set by accessing a structured repository of information using said pre-trained model; and present said answer set to said question answering system.
11. A computer system comprising: one or more computer processors; one or more computer readable storage media; computer program instructions; and said computer program instructions being stored on said computer readable storage media for execution by at least one of said one or more processors, said computer program instructions comprising instructions to: receive a question, said question being directed to a domain-specific question answering system, wherein said question is requesting at least two distinct pieces of information; extract two or more distinct queries from said question, based on a query decomposing rule library by comparing said question to said query decomposing rule library to identify a matching decomposition rule, wherein said comparing includes using an index scan, using a keyword scan, parsing said query decomposing rule library, and using a segment scan, wherein said query decomposing rule library includes combinations of semantic, syntactic, grammatical, structural, and other predetermined rules for identifying distinct queries within said question; generate two or more question sets, each of said two or more question sets addressing all of said two or more queries, wherein said generated two or more questions sets are expressed in a language and format that said question answering system can interpret and process, wherein both said first question set and said second question set include at least one question for each of said two or more queries extracted from said question, and wherein said second question set includes at least one question different from said first question set; select one of said two or more question sets to yield a selected question set, based on analyzing each of said two or more question sets according to a pre-trained model, wherein said pre-trained model is a term vector model, wherein said term vector model is an algebraic model for representing elements within a text document as vectors and generates a number of dimensions based on keywords, terms, and elements within said extracted queries, wherein said two or more question sets are selected based on a first optimal score, wherein said first optimal score is based on a number of specific terms and irrelevant terms in questions in each said two or more question sets, and wherein said irrelevant terms lower said first optimal score; present said selected question set to said question answering system and a user; determine at least one answer set for said selected question set by accessing a structured repository of information using said pre-trained model; and present said answer set to said question answering system. 12. The computer system of claim 11 , wherein instructions to extract two or more queries from said question is based on one or more semantic rules.