1. A method for constructing learning data, comprising the steps of: (a) generating learning models by performing machine learning with respect to learning data; (b) attaching tags to a raw corpus automatically using the generated learning models to thereby generate learning data candidates; (c) calculating confidence scores of the generated learning data candidates, and selecting a learning data candidate by using the calculated confidence scores; and (d) allowing a user to correct an error in the selected learning data candidate through an interface and adding the error-corrected learning data candidate to the learning data, thereby adding new learning models incrementally.