  Commonsense generation aims at generating plausible everyday scenario
description based on a set of provided concepts. Digging the relationship of
concepts from scratch is non-trivial, therefore, we retrieve prototypes from
external knowledge to assist the understanding of the scenario for better
description generation. We integrate two additional modules, namely position
indicator and scaling module, into the pretrained encoder-decoder model for
prototype modeling to enhance the knowledge injection procedure. We conduct
experiment on CommonGen benchmark, and experimental results show that our
method significantly improves the performance on all the metrics.
