  How can we enable users to heavily specify criteria for database queries in a
user-friendly way? This paper describes a general framework of a conversational
bot that extracts meaningful information from user's sentences, that asks
subsequent questions to complete missing information, and that adjusts its
questions and information-extraction parameters for later conversations
depending on users' behavior. Additionally, we provide a comparison of existing
tools and give novel techniques to implement such framework. Finally, we
exemplify the framework with a bot to query movies in a database, whose code is
available for Microsoft employees.
