Most scholarly search services only provide basic text-matching or similarity-based searches, with limited operations that require manual configuration, such as sorting and filtering by specific metadata attributes. These capabilities are insufficient for researchers who often have queries that involve complex constraints and operations, such as ''enumerating the authors of a given paper along with the venues where they have published other papers.'' In this work, we develop an interactive and intuitive scholarly question answering system called NLQxform-UI, which allows users to pose complex queries in the form of natural language questions. It is capable of automatically translating these questions into SPARQL queries that can be executed over the DBLP knowledge graph to retrieve expected answers. Furthermore, the users can interact with each step of the answering process and browse the final results in a web-based interface. A video recording of our system is available at https://youtu.be/elq8CPykiyk Additionally, the system has been completely open-sourced: https://github.com/ruijie-wang-uzh/NLQxform-UI