Approaches are provided for answering an inquiry of a cognitive distributed network. An approach includes receiving the inquiry at the cognitive distributed network. The approach further includes determining a classification for the inquiry based on natural language of the inquiry. The approach further includes classifying the inquiry as a single question class. The approach further includes determining, by at least one computing device, a type of introspection to be used by the cognitive distributed network on the inquiry. The approach further includes generating an answer to the inquiry based on the determined type of introspection.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for answering an inquiry of a cognitive distributed network, comprising: receiving the inquiry at the cognitive distributed network; determining a classification for the inquiry based on natural language of the inquiry; classifying the inquiry as a single question class; determining, by at least one computing a device, a type of introspection to be used by the cognitive distributed network on the inquiry; and generating an answer to the inquiry based on the determined type of introspection. 2. The method of claim 1, wherein the inquiry is received in response to a human reacting to performance of the cognitive distributed network. 3. The method of claim 1, wherein the determining the classification for the inquiry is based on key words and phrases within the natural language of the inquiry. 4. The method of claim 3, wherein the determining the type of the introspection to be used on the inquiry is based on an amount of detail provided within the inquiry. 5. The method of claim 4, wherein the determined type of introspection is one of recall, precision, and average. 6. The method of claim 1, wherein a service provider at least one of creates, maintains, deploys and supports a computer infrastructure that includes the at least one computing device. 7. The method of claim 1, wherein steps of claim 1 are provided by a service provider on a subscription, advertising, and/or fee basis. 8. A computer program product for answering an inquiry of a cognitive distributed network, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions readable/executable by a computing device to cause the computing device to: receive, by the computing device, the inquiry; determine, by the computing device, a classification for the inquiry; classify, by the computing device, the inquiry as a conversational class; determine, by the computing device, whether the inquiry pertains to past performance or future performance of the cognitive distributed network; in response to determining the inquiry pertains to the past performance, apply, by the computing device, natural language processing to the inquiry to determine how the cognitive distributed network was performing in the past; in response to determining the inquiry pertains to the future performance, apply, by the computing device, the natural language processing to the inquiry to determine how the cognitive distributed network will be performing in the future; use, by the computing device, a recall oriented introspection algorithm to minimize false negative responses; and reply, by the computing device, to the inquiry based on the determination of how the cognitive distributed network was performing in the past or will be performing in the future, and the use of the recall oriented introspection algorithm. 9. The computer program product of claim 8, wherein the determining whether the inquiry pertains to the past performance or the future performance is based on natural language of the inquiry and a temporal account of events discussed therein. 10. The computer program product of claim 8, wherein in response to determining the inquiry pertains to the past performance, use, by the computing device, distributed network based ontology to map introspection tags to analytics that measure performance of the cognitive distributed network. 11. The computer program product of claim 10, wherein the mapped introspection tags may be correlated to at least one of natural language words, focus, and entities. 12. The computer program product of claim 8, wherein in response to determining the inquiry pertains to the future performance, apply, by the computing device, forecasting based algorithms that use time series autoregressive integrated moving average methods to simulate ahead of horizon metrics. 13. The computer program product of claim 12, wherein the forecasting based algorithms are configured to simulate ahead of time horizon forecasting. 14. The computer program product of claim 8, wherein in response to determining the inquiry pertains to the future performance, use, by the computing device, symbiosis to predict fault tolerance or disk failures for performance forecasting of the cognitive distributed network. 15. The computer program product of claim 8, further comprising relax, by the computing device, a threshold of natural language processing questions to distributed network ontology relationships to minimize false positive responses. 16. The computer program product of claim 8, further comprising receive, by the computing device, additional information provided in response to the reply to the inquiry, wherein the additional information includes additional natural language to narrow a scope of the inquiry. 17. The computer program product of claim 16, further comprising: determine, by the computing device, whether the additional information pertains to the past performance or the future performance of the cognitive distributed network; in response to determining the additional information pertains to the past performance, apply, by the computing device, the natural language processing to the additional information to determine how the cognitive distributed network was performing in the past; and in response to determining the additional information pertains to the future performance, apply, by the computing device, the natural language processing to the additional information to determine how the cognitive distributed network will be performing in the future. 18. The computer program product of claim 17, further comprising use, by the computing device, a midterm introspection algorithm to minimize false positive responses. 19. The computer program product of claim 18, further comprising reply, by the computing device, to the additional information based on the determination of how the cognitive distributed network was performing in the past or will be performing in the future, and the use of the midterm introspection algorithm. 20. A system for answering an inquiry of a cognitive distributed network, comprising: a CPU, a computer readable memory and a computer readable storage medium; program instructions to receive the inquiry; program instructions to determine a classification for the inquiry; program instructions to classify the inquiry as a conversational class; program instructions to determine whether the inquiry pertains to past performance or future performance of the cognitive distributed network; in response to determining the inquiry pertains to the past performance, program instructions to apply natural language processing to the inquiry to determine how the cognitive distributed network was performing in the past; in response to determining the inquiry pertains to the future performance, program instructions to the apply natural language processing to the inquiry to determine how the cognitive distributed network will be performing in the future; program instructions to use a recall oriented introspection algorithm to minimize false negative responses; and program instructions to reply to the inquiry based on the determination of how the cognitive distributed network was performing in the past or will be performing in the future, and the use of the recall oriented introspection algorithm, wherein the program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory.