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We present an open-source extensible python-based toolkit that provides access to a (1) range of built-in unsupervised query expansion methods, and (2) pipeline for generating gold standard datasets for building and evaluating supervised query refinement methods. While the information literature offers abundant work on query expansion techniques, there is yet to be a tool that provides unified access to a comprehensive set of query expansion techniques. The advantage of our proposed toolkit, known as ReQue (refining queries), is that it offers one-stop shop access to query expansion techniques to be used in external information retrieval applications. More importantly, we show how ReQue can be used for building gold standards datasets that can be used for training supervised deep learning-based query refinement techniques. These techniques require sizeable gold query refinement datasets …