论文标题
迈向参数挖掘管道将文本转换为参数图
Towards an Argument Mining Pipeline Transforming Texts to Argument Graphs
论文作者
论文摘要
本文以自然语言文本的自动提取了论证信息的组成部分的自动提取。此外，我们解决了当前缺乏系统，可以从任意自然语言文本中提供完整的论证结构，以供一般使用。我们提出了一个参数挖掘管道，作为将德语和英语文本转换为基于图的参数表示的一种普遍适用的方法。我们还介绍了基于现有基准参数结构评估结果的新方法。我们的结果表明，生成的参数图可以有益于检测论点文本不同语句之间的新连接。我们的管道实施在GitHub上公开可用。
This paper targets the automated extraction of components of argumentative information and their relations from natural language text. Moreover, we address a current lack of systems to provide complete argumentative structure from arbitrary natural language text for general usage. We present an argument mining pipeline as a universally applicable approach for transforming German and English language texts to graph-based argument representations. We also introduce new methods for evaluating the results based on existing benchmark argument structures. Our results show that the generated argument graphs can be beneficial to detect new connections between different statements of an argumentative text. Our pipeline implementation is publicly available on GitHub.
