Paper ID: 2302.06579

AbLit: A Resource for Analyzing and Generating Abridged Versions of English Literature

Melissa Roemmele, Kyle Shaffer, Katrina Olsen, Yiyi Wang, Steve DeNeefe

Creating an abridged version of a text involves shortening it while maintaining its linguistic qualities. In this paper, we examine this task from an NLP perspective for the first time. We present a new resource, AbLit, which is derived from abridged versions of English literature books. The dataset captures passage-level alignments between the original and abridged texts. We characterize the linguistic relations of these alignments, and create automated models to predict these relations as well as to generate abridgements for new texts. Our findings establish abridgement as a challenging task, motivating future resources and research. The dataset is available at github.com/roemmele/AbLit.

Submitted: Feb 13, 2023