  The generation of humor is an under-explored and challenging problem.
Previous works mainly utilize templates or replace phrases to generate humor.
However, few works focus on freer forms and the background knowledge of humor.
The linguistic theory of humor defines the structure of a humor sentence as
set-up and punchline. In this paper, we explore how to generate a punchline
given the set-up with the relevant knowledge. We propose a framework that can
fuse the knowledge to end-to-end models. To our knowledge, this is the first
attempt to generate punchlines with knowledge enhanced model. Furthermore, we
create the first humor-knowledge dataset. The experimental results demonstrate
that our method can make use of knowledge to generate fluent, funny punchlines,
which outperforms several baselines.
