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The ReCAP Corpus: A Corpus of Complex Argument Graphs on German Education Politics

机译:Recap Corpus:德国教育政治上复杂的论点图表的语音

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The automatic extraction of arguments from natural language texts is a highly researched area and more important than ever today, as it is nearly impossible to manually capture all arguments on a controversial topic in a reasonable amount of time. For testing different algorithms such as the retrieval of the best arguments, which are still in their infancy, gold standards must exist. An argument consists of a claim or standpoint that is supported or opposed by at least one premise. The generic term for a claim or premise is Argumentative Discourse Unit (ADU). The relationships between ADUs can be specified by argument schemes and can lead to large graphs. This paper presents a corpus of 100 argument graphs with about 2,500 ADUs in German, which is unique in its size and the utilisation of argument schemes. The corpus is built from natural language texts like party press releases and parliamentary motions on education policies in the German federal states. Each high-quality text is presented by an argument graph and created by the use of a modified version of the annotation tool OVA. The final argument graphs resulted by merging two previously independently annotated graphs based on detailed discussions.
机译:自然语言文本的自动提取争论是一个高度研究的区域,比以往任何时候更重要,因为它几乎不可能在合理的时间内手动捕获有争议的主题的所有参数。用于测试不同的算法,例如检索最佳参数,这些参数仍然存在于初期,金标准必须存在。一个论据包括至少一个前提支持或反对的索赔或观点组成。索赔或前提的通用术语是争论性话语单位(ADU)。 Adus之间的关系可以由参数方案指定,可以导致大图。本文介绍了100个参数图表,其中德语大约2,500个Adus,其大小是独一无二的,其参数方案的利用率是独一无二的。语料库是由自然语言文本构建的,如党内新闻稿和德国联邦国家教育政策的议会动议。每个高质量的文本由参数图表呈现,并通过使用Annotation Tool OVA的修改版本来创建。通过基于详细讨论合并两个以前独立的注释的图形来产生最终的参数图。

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