Narrative Modeling with Memory Chains and Semantic Supervision

Published:

Fei Liu, Trevor Cohn and Timothy Baldwin (2018) Narrative Modeling with Memory Chains and Semantic Supervision, In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), Melbourne, Australia.

@InProceedings{Liu+:2018,
  author    = {Liu, Fei  and  Cohn, Trevor and Baldwin, Timothy},
  title     = {Narrative Modeling with Memory Chains and Semantic Supervision},
  booktitle = {Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018)},
  year      = {2018},
  address   = {Melbourne, Australia},
  pages     = {1--10}
}

Abstract

Story comprehension requires a deep semantic understanding of the narrative, making it a challenging task. Inspired by previous studies on ROC Story Cloze Test, we propose a novel method, tracking various semantic aspects with external neural memory chains while encouraging each to focus on a particular semantic aspect. Evaluated on the task of story ending prediction, our model demonstrates superior performance to a collection of competitive baselines, setting a new state of the art.