We present Poetwannabe, a chatbot submitted by the University of Wroc{\l}aw to the NIPS 2017 Conversational Intelligence Challenge, in which it ranked first ex-aequo. It is able to conduct a conversation with a user in a natural language. The primary functionality of our dialogue system is context-aware question answering (QA), while its secondary function is maintaining user engagement. The chatbot is composed of a number of sub-modules, which independently prepare replies to user's prompts and assess their own confidence. To answer questions, our dialogue system relies heavily on factual data, sourced mostly from Wikipedia and DBpedia, data of real user interactions in public forums, as well as data concerning general literature. Where applicable, modules are trained on large datasets using GPUs. However, to comply with the competition's requirements, the final system is compact and runs on commodity hardware.

Poetwannabe是一个聊天机器人，具有自然语言对话的能力，并且主要功能是上下文感知的问答（QA），次要功能是维护用户参与度。为回答问题，对话系统主要使用来自维基百科和DBpedia的事实数据，以及公共论坛中真实用户交互的数据和一般文献的数据。

Talker Ensemble：Wrocław大学参加NIPS 2017对话智能挑战赛