9. A computer program product for question and answer generation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive a question in a target language; apply natural language processing to parse the question into at least one focus; for each focus, determine if one or more target language verbs share direct syntactic dependency with the focus; for each of the one or more verbs sharing direct syntactic dependency, determine if one or more target language entities share direct syntactic dependency with the verb; determine one or more Abstract Universal Verbal Types associated with each verb; for each of the one or more Abstract Universal Verbal Types, determine whether a dependency between a source language entity and a source language verb is of the same type as the dependency between the target language verb and the target language entity comprising: use a cognitive system to generate a plurality of reasoning algorithms to analyze the source language and the target language, wherein each reasoning algorithm generates a dependency score; train a statistical model employed by a question answer pipeline; apply the trained statistical model to determine a weight for each dependency score; apply the weight to each dependency score to generate weighted dependency scores; and process the weighted dependency scores with the statistical model to generate one or more confidence scores measuring dependency; if the dependency is similar, return the source language entity as a member of a set; and if the set is full, return an answer in the target language to the question in the target language.
9. A computer program product for question and answer generation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive a question in a target language; apply natural language processing to parse the question into at least one focus; for each focus, determine if one or more target language verbs share direct syntactic dependency with the focus; for each of the one or more verbs sharing direct syntactic dependency, determine if one or more target language entities share direct syntactic dependency with the verb; determine one or more Abstract Universal Verbal Types associated with each verb; for each of the one or more Abstract Universal Verbal Types, determine whether a dependency between a source language entity and a source language verb is of the same type as the dependency between the target language verb and the target language entity comprising: use a cognitive system to generate a plurality of reasoning algorithms to analyze the source language and the target language, wherein each reasoning algorithm generates a dependency score; train a statistical model employed by a question answer pipeline; apply the trained statistical model to determine a weight for each dependency score; apply the weight to each dependency score to generate weighted dependency scores; and process the weighted dependency scores with the statistical model to generate one or more confidence scores measuring dependency; if the dependency is similar, return the source language entity as a member of a set; and if the set is full, return an answer in the target language to the question in the target language. 16. The computer program product as recited in claim 9 , wherein the processor is further caused to: assign a function from the one or more Abstract Universal Verbal Types to one or more verbal surface manifestations in the target language.