English

EntSUM: A Data Set for Entity-Centric Summarization

Computation and Language 2022-04-06 v1

Abstract

Controllable summarization aims to provide summaries that take into account user-specified aspects and preferences to better assist them with their information need, as opposed to the standard summarization setup which build a single generic summary of a document. We introduce a human-annotated data set EntSUM for controllable summarization with a focus on named entities as the aspects to control. We conduct an extensive quantitative analysis to motivate the task of entity-centric summarization and show that existing methods for controllable summarization fail to generate entity-centric summaries. We propose extensions to state-of-the-art summarization approaches that achieve substantially better results on our data set. Our analysis and results show the challenging nature of this task and of the proposed data set.

Keywords

Cite

@article{arxiv.2204.02213,
  title  = {EntSUM: A Data Set for Entity-Centric Summarization},
  author = {Mounica Maddela and Mayank Kulkarni and Daniel Preotiuc-Pietro},
  journal= {arXiv preprint arXiv:2204.02213},
  year   = {2022}
}

Comments

Accepted at ACL 2022

R2 v1 2026-06-24T10:38:30.130Z