Changing the Narrative Perspective: From Deictic to Anaphoric Point of View

TL;DR

This paper presents a new task of changing narrative perspective in texts, introduces a benchmark dataset, and proposes a neural architecture that effectively shifts point of view from deictic to anaphoric, enhancing narrative flexibility.

Contribution

The paper introduces a novel task of perspective shifting, creates a benchmark dataset, and develops a neural method that improves mention selection for changing narrative points of view.

Findings

The proposed neural architecture outperforms baselines in generating less ambiguous mentions.

The dataset enables evaluation of perspective-shifting models across various narrative types.

The method effectively alters narrative perspective, impacting reading experience and text generation applications.

Abstract

We introduce the task of changing the narrative point of view, where characters are assigned a narrative perspective that is different from the one originally used by the writer. The resulting shift in the narrative point of view alters the reading experience and can be used as a tool in fiction writing or to generate types of text ranging from educational to self-help and self-diagnosis. We introduce a benchmark dataset containing a wide range of types of narratives annotated with changes in point of view from deictic (first or second person) to anaphoric (third person) and describe a pipeline for processing raw text that relies on a neural architecture for mention selection. Evaluations on the new benchmark dataset show that the proposed architecture substantially outperforms the baselines by generating mentions that are less ambiguous and more natural.