  Multiple lines of research have developed Natural Language (NL) interfaces
for formulating database queries. We build upon this work, but focus on
presenting a highly detailed form of the answers in NL. The answers that we
present are importantly based on the provenance of tuples in the query result,
detailing not only the results but also their explanations. We develop a novel
method for transforming provenance information to NL, by leveraging the
original NL query structure. Furthermore, since provenance information is
typically large and complex, we present two solutions for its effective
presentation as NL text: one that is based on provenance factorization, with
novel desiderata relevant to the NL case, and one that is based on
summarization. We have implemented our solution in an end-to-end system
supporting questions, answers and provenance, all expressed in NL. Our
experiments, including a user study, indicate the quality of our solution and
its scalability.
