论文标题
协议：一种多文章的方法，用于产生科学概念的多种描述
ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts
论文作者
论文摘要
可以自动定义陌生术语的系统具有改善科学文本的可访问性的希望，尤其是对于可能缺乏前提背景知识的读者而言。但是，当前系统每个概念都采用单个“最佳”描述，该描述无法说明可以描述概念的许多潜在有用方式。我们提出Accord，这是一个端到端系统，该系统应对生成科学概念描述的新任务。我们的系统利用了整个科学文献中提到的概念的众多方式，以根据不同的参考概念对目标科学概念产生不同的描述。为了支持对任务的研究，我们发布了专家注册的资源Accord语料库，其中包括1,275个标记的上下文和1,787个手工撰写的概念描述。我们进行了一项用户研究，表明（1）用户更喜欢我们的端到端系统产生的描述，并且（2）用户更喜欢多个描述，而不是单个“最佳”描述。
Systems that can automatically define unfamiliar terms hold the promise of improving the accessibility of scientific texts, especially for readers who may lack prerequisite background knowledge. However, current systems assume a single "best" description per concept, which fails to account for the many potentially useful ways a concept can be described. We present ACCoRD, an end-to-end system tackling the novel task of generating sets of descriptions of scientific concepts. Our system takes advantage of the myriad ways a concept is mentioned across the scientific literature to produce distinct, diverse descriptions of target scientific concepts in terms of different reference concepts. To support research on the task, we release an expert-annotated resource, the ACCoRD corpus, which includes 1,275 labeled contexts and 1,787 hand-authored concept descriptions. We conduct a user study demonstrating that (1) users prefer descriptions produced by our end-to-end system, and (2) users prefer multiple descriptions to a single "best" description.
