Selecting which claims to check is a time-consuming task for human
fact-checkers, especially from documents consisting of multiple sentences and
containing multiple claims. However, existing claim extraction approaches focus
more on identifying and extracting claims from individual sentences, e.g.,
identifying whether a sentence contains a claim or the exact boundaries of the
claim within a sentence. In this paper, we propose a method for document-level
claim extraction for fact-checking, which aims to extract check-worthy claims
from documents and decontextualise them so that they can be understood out of
context. Specifically, we first recast claim extraction as extractive
summarization in order to identify central sentences from documents, then
rewrite them to include necessary context from the originating document through
sentence decontextualisation. Evaluation with both automatic metrics and a
fact-checking professional shows that our method is able to extract
check-worthy claims from documents more accurately than previous work, while
also improving evidence retrieval.

我们提出了一种用于事实检查的文档级索取索赔的方法，旨在从文档中提取值得检查的要求，并将它们解除背景以便在任何环境下理解。使用自动评估指标和事实检查专业人员的评估结果表明，我们的方法比以前的工作更准确地从文档中提取出有价值的索赔，并改善了证据的检索。