Examples of techniques for generating streaming analytics applications are described herein. An example computer-implemented method includes receiving, via a processor, subject matter requirements in a semi-structured format. The method includes classifying, via the processor, the subject matter requirements based on a predefined taxonomy. The method includes extracting, via the processor, a list of entities from the subject matter requirements based on grammar. The method includes generating a solution based on a glossary and the list of extracted entities. The method includes generating, via the processor, a streaming analytics application based on the solution.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system, comprising: a processor configured to: receive subject matter requirements in a semi-structured format; classify the subject matter requirements based on a predefined taxonomy; extract a list of entities from the subject matter requirements based on grammar; generate a solution based on a glossary, wherein to generate the solution the processor is further configured to: detect an applicable training data set in a model repository based on the classifications and the extracted entities, and generate a model based on the training data set; and generate a streaming analytics application in real-time based on the solution, wherein the streaming analytics application includes the model. 2. The system of claim 1, wherein to generate the solution, the processor is further configured to generate a streaming analytics application component by mapping the extracted entities to conceptual graphs and properties in the glossary. 3. The system of claim 1, wherein the subject matter requirements comprise a plurality of constraints in a human-readable language. 4. The system of claim 1, wherein the glossary comprises a predefined glossary of an organization. 5. The system of claim 1, wherein the training data set comprises classified training data. 6. The system of claim 1, wherein the predefined taxonomy comprises predefined categories comprising words. 7. The system of claim 6, wherein the processor is further configured to determine whether an applicable model exists in a model repository and fetch the applicable model from the model repository if the applicable model exists, the applicable model to be included in the streaming analytics application. 8. A computer-implemented method, comprising: receiving, via a processor, subject matter requirements in a semi-structured format; classifying, via the processor, the subject matter requirements based on a predefined taxonomy; extracting, via the processor, a list of entities from the subject matter requirements based on grammar; generating, via the processor, a solution based on a glossary and the list of extracted entities; and generating, via the processor, a streaming analytics application in real-time based on the solution. 9. The computer-implemented method of claim 8, wherein generating the solution based on the glossary and the extracted entities further comprises: determining, via the processor, whether an applicable model exists in a model repository; fetching, via the processor, the applicable model from the model repository if the applicable model is detected; detecting, via the processor, an applicable training data set in the model repository based on the classifications and the extracted entities if no applicable model is detected in the model repository; generating, via the processor, a model based on the training data set; and generating, via the processor, a streaming analytics application component by mapping the extracted entities to conceptual graphs and properties in the glossary. 10. The computer-implemented method of claim 8, further comprising scoring solutions based on metadata comparisons and returning a set of solutions with a higher score. 11. The computer-implemented method of claim 8, wherein generating the solution comprises mapping the list of entities to solution components. 12. The computer-implemented method of claim 9, wherein determining whether the applicable model exists comprises mapping the list of entities to solution components and comparing the mapped solution components to solution components in existing models in the model repository. 13. The computer-implemented method of claim 9, wherein detecting an applicable training data set comprises comparing training data metadata with the extracted list of entities. 14. The computer-implemented method of claim 8, further comprising receiving feedback from a subject matter expert and updating the streaming analytics application conceptual graph in the glossary based on the feedback. 15. A computer program product for generating streaming analytics applications, the computer program product comprising: a computer-readable non-transitory storage medium having program code embodied therewith, the program code executable by a processor to cause the processor to: receive subject matter requirements in a semi-structured format; classify the subject matter requirements based on a predefined taxonomy; extract a list of entities from the subject matter requirements based on grammar; detect an applicable training data set in a model repository based on the classifications and the extracted entities; generate a model based on the training data set; and generate a streaming analytics application in real-time comprising a mining component. 16. The computer program product of claim 15, further comprising program code executable by the processor to: detect an existing model in a model repository; and generate the streaming analytics application based on the existing model in the model repository. 17. The computer program product of claim 15, further comprising program code executable by the processor to map the list of entities to solution components and compare the mapped solution components to solution components in existing models in the model repository. 18. The computer program product of claim 15, further comprising program code executable by the processor to detect that an operator does not exist and send a task generation request to a user interface. 19. The computer program product of claim 15, further comprising program code executable by the processor to receive feedback from a subject matter expert and modify the streaming analytics application based on the feedback. 20. The computer program product of claim 16, further comprising program code executable by the processor to fetch the existing model from the model repository and generate a mining component based on the model.