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Recently Clark and Eyraud (2007) have shown that substitutable context-free languages, which capture an aspect of natural language phenomena, are efficiently identifiable in the limit from positive data. Generalizing their work, this paper presents a polynomialtime learning algorithm for new subclasses of mildly context-sensitive languages with variants of substitutability.