---
title: "Narrative Hermeneutic Circle: Improving Character Role Identification from Natural Language Text via Feedback Loops"
authors:
  - "Josep Valls-Vargas"
  - "Jichen Zhu"
  - "Santiago Ontañón"
doi: ""
url: "https://ijcai.org/proceedings/2015/357"
pdf: "https://ijcai.org/proceedings/2015/0357.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "2517-2522"
track: "Special Track on Artificial Intelligence and the Arts"
keywords:
---

# Narrative Hermeneutic Circle: Improving Character Role Identification from Natural Language Text via Feedback Loops

Josep Valls-Vargas, Jichen Zhu, Santiago Ontañón

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 2517-2522.

## Abstract

While most natural language understanding systems rely on a pipeline-based architecture, certain human text interpretation methods are based on a cyclic process between the whole text and its parts: the hermeneutic circle. In the task of automatically identifying characters and their narrative roles, we propose a feedback-loop-based approach where the output of later modules of the pipeline is fed back to earlier ones. We analyze this approach using a corpus of 21 Russian folktales. Initial results show that feeding back high-level narrative information improves the performance of some NLP tasks.