Journal of Information & Systems Management Boris Galitsky, Dmitry Ilvovsky 10 2 2020 https://doi.org/10.6025/jism/2020/10/2/42-47 https://www.dline.info/jism/fulltext/v11n2/jismv11n2_2.pdf We convert existing training datasets into the ones closed under linguistic generalization operations to expand infrequent cases. We transfer the definition of the least general generalization from logical formulas to linguistic structures, from words to phrases, sentences, speech acts and discourse trees. The main advantage of the resultant frameworks is explainability and learnability from a small set of samples. Learning via generalization of linguistic structures turned out to be well suited for industrial linguistic applications with limited training datasets.