  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.
