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ACL2022顶会

EntSUM: A Data Set for Entity-Centric Extractive Summarization

Mounica Maddela, Mayank Kulkarni, Daniel Preotiuc-Pietro

2022年份
2被引次数
3顶会引用

摘要

Controllable summarization aims to provide summaries that take into account userspecified 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. 12

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