Changing the Narrative Perspective: From Deictic to Anaphoric Point of View
This addresses a specific problem in natural language processing for fiction writing and text generation applications, representing an incremental advancement in narrative manipulation.
The paper tackles the task of changing narrative point of view from deictic to anaphoric perspectives, introducing a benchmark dataset and a neural pipeline for mention selection, which substantially outperforms baselines by generating less ambiguous and more natural mentions.
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.