  Hindi question answering systems suffer from a lack of data. To address the
same, this paper presents an approach towards automatic question generation. We
present a rule-based system for question generation in Hindi by formalizing
question transformation methods based on karaka-dependency theory. We use a
Hindi dependency parser to mark the karaka roles and use IndoWordNet a Hindi
ontology to detect the semantic category of the karaka role heads to generate
the interrogatives. We analyze how one sentence can have multiple generations
from the same karaka role's rule. The generations are manually annotated by
multiple annotators on a semantic and syntactic scale for evaluation. Further,
we constrain our generation with the help of various semantic and syntactic
filters so as to improve the generation quality. Using these methods, we are
able to generate diverse questions, significantly more than number of sentences
fed to the system.
