  Limerick generation exemplifies some of the most difficult challenges faced
in poetry generation, as the poems must tell a story in only five lines, with
constraints on rhyme, stress, and meter. To address these challenges, we
introduce LimGen, a novel and fully automated system for limerick generation
that outperforms state-of-the-art neural network-based poetry models, as well
as prior rule-based poetry models. LimGen consists of three important pieces:
the Adaptive Multi-Templated Constraint algorithm that constrains our search to
the space of realistic poems, the Multi-Templated Beam Search algorithm which
searches efficiently through the space, and the probabilistic Storyline
algorithm that provides coherent storylines related to a user-provided prompt
word. The resulting limericks satisfy poetic constraints and have thematically
coherent storylines, which are sometimes even funny (when we are lucky).
