1. A method, in a data processing system comprising at least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a question answering system, for question answering using multi-instance learning, the method comprising: training an answer ranking multi-instance learned model using a ground truth question and answer-key pairs set, wherein the data processing system executes in accordance with the answer ranking multi-instance learned model to implement the question answering system, wherein the answer ranking multi-instance learned model is trained by labeling each passage set returned for each correct answer as true responsive to determining the passage set collectively does support a correct answer according to the question and answer-key pairs set and labeling each passage set returned for an incorrect answer as false responsive to determining the passage set collectively does not support a correct answer according to the question and answer-key pairs set; receiving, by the question answering system, an input question from a user; generating, by a hypothesis generation phase of a question answering pipeline of the question answering system, one or more candidate answers to the input question, wherein each of the one or more candidate answers has an associated set of supporting passages; determining, by a hypothesis and evidence scoring phase of the question answering pipeline of the question answering system, a confidence value for each of the one or more candidate answers by applying the answer ranking multi-instance learned model to the associated sets of supporting passages; ranking, by an answer ranking phase of the question answering pipeline of the question answering system, the one or more candidate answers by confidence value to form a ranked set of answers; and presenting, by the question answering system, a final answer from the ranked set of answers, the confidence value for the final answer, and supporting evidence for the final answer to the user.