Understanding Points of Correspondence between Sentences for Abstractive Summarization
Understanding Points of Correspondence between Sentences for Abstractive Summarization
复制标题
DOI：
10.18653/v1/2020.acl-srw.26
复制
发表时间：
2020-06
期刊：
影响因子：
--
通讯作者：
Logan Lebanoff;John Muchovej;Franck Dernoncourt;Doo Soon Kim;Lidan Wang;Walter Chang;Fei Liu
中科院分区：
文献类型：
--
作者：
Logan Lebanoff;John Muchovej;Franck Dernoncourt;Doo Soon Kim;Lidan Wang;Walter Chang;Fei Liu
融合包含不同内容的句子是一种非凡的人类能力，有助于创建信息丰富和简洁的摘要。对于人类来说，这样一个简单的任务对现代抽象摘要器来说仍然是一个挑战，大大限制了它们在现实世界中的适用性。在本文中，我们提出了一个调查融合的句子从一个文件中引入的概念，对应点，这是衔接手段，将任何两个句子连接在一起，成为一个连贯的文本。语篇衔接理论对对应点的类型进行了划分，包括代词和名词性指称、重复及其他。我们创建了一个数据集，其中包含文档、源语句和融合语句，以及语句之间对应点的人工注释。我们的数据集弥合了共指消解和摘要之间的差距。它是公开共享的，作为未来工作的基础，以衡量句子融合系统的成功。
Fusing sentences containing disparate content is a remarkable human ability that helps create informative and succinct summaries. Such a simple task for humans has remained challenging for modern abstractive summarizers, substantially restricting their applicability in real-world scenarios. In this paper, we present an investigation into fusing sentences drawn from a document by introducing the notion of points of correspondence, which are cohesive devices that tie any two sentences together into a coherent text. The types of points of correspondence are delineated by text cohesion theory, covering pronominal and nominal referencing, repetition and beyond. We create a dataset containing the documents, source and fusion sentences, and human annotations of points of correspondence between sentences. Our dataset bridges the gap between coreference resolution and summarization. It is publicly shared to serve as a basis for future work to measure the success of sentence fusion systems.