English

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

Computation and Language 2023-02-14 v1

Abstract

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.

Keywords

Cite

@article{arxiv.2302.06579,
  title  = {AbLit: A Resource for Analyzing and Generating Abridged Versions of English Literature},
  author = {Melissa Roemmele and Kyle Shaffer and Katrina Olsen and Yiyi Wang and Steve DeNeefe},
  journal= {arXiv preprint arXiv:2302.06579},
  year   = {2023}
}

Comments

Accepted at EACL 2023