  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.
(https://github.com/ucfnlp/points-of-correspondence)
