Resource-Lean Modeling of Coherence in Commonsense Stories

Abstract

We present a resource-lean neural recognizer for modeling coherence in commonsense stories. Our lightweight system is inspired by successful attempts to modeling discourse relations and stands out due to its simplicity and easy optimization compared to prior approaches to narrative script learning. We evaluate our approach in the Story Cloze Test demonstrating an absolute improvement in accuracy of 4.7\% over state-of-the-art implementations.

Tasks

Reproductions