While conventional machine comprehension models were given a paragraph that always contains an answer to a question, some researchers have extended the models to an open-domain setting where relevant documents have to be searched from an extremely large knowledge source such as Wikipedia (Chen et al., 2017;Wang et al., 2017a).
most of the open-domain QA pipelines depend on traditional information retrieval systems which use TF-IDF rankings (Chen et al., 2017;Wang et al., 2017b).