1. A method, in a data processing system having a processor and a memory storing a store of semantic types and instructions for implementing a natural language processing engine for generating a question/answer pair list with semantically equivalent variants, the method comprising: generating a user interface for generating a question/answer pair list; receiving user input in the user interface specifying a question and an answer term and specifying an answer type from a list of previously created answer types, wherein the input term comprises the answer term; identifying, by the natural language processing engine executing on the data processing system, a semantic type of the answer term based on the store of semantic types; performing, by the natural language processing engine, a type-specific series of rule-based expansions of the answer term based on the identified semantic type of the answer term of the answer term; adding, by the natural language processing engine, at least one semantically equivalent variant from the set of semantically equivalent variants of the answer term in association with the specified question to the question/answer pair list to form an expanded question/answer pair list; and training, by the natural language processing engine, a question answering machine learning model for a question answering cognitive system using the expanded question/answer pair list as ground truth.