FAME: A Framework for Argument Mining and Evaluation

FAME：论证挖掘和评估的框架

• 批准号: 406289255
• 负责人: Dr. Ringo Baumann
• 金额: --
• 依托单位: Sächsische Akademie der Wissenschaften zu Leipzig
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2019
• 资助国家: 德国
• 起止时间: 2018-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/406289255?language=en
• 关键词: FAME; Framework; Argument; Mining; Evaluation

Two different perspectives on argumentation have been pursued in recent research, namely approaches of argument mining from natural language texts on the one hand and formal argument evaluation on the other. So far these research areas are largely independent and unrelated. The overall goal of the FAME project is to link these two perspectives and their respective research agendas. We develop a framework which integrates argument mining and formal argument evaluation. This connection will allow for evaluation of 'deep' semantic argument structures in natural language text and new forms of queries to retrieval systems. The challenge here is to bridge the gap between processing texts in natural language and evaluating arguments expressed in some formal language with a corresponding formal semantics. The hypothesis underlying this proposal is that controlled natural language (CNL) can provide the necessary link for bridging this gap. CNL can serve as an intermediate representation of argumentative text. They have the look and feel of natural language and are thus close enough to natural language based argument processing. On the other hand, the CNL we will be using is one which also possesses a well-defined formal semantics and is thus amenable to formal evaluation methods. CNLs of the kind mentioned already exist. A prominent example is Attempto Controlled English (ACE). ACE is easily understood by humans. At the same time, its semantics is formally defined based on a translation into discourse representation structures, which can be further translated into predicate logic. Since ACE was not primarily developed with argumentation in mind, we will thoroughly investigate whether the language constructs provided are sufficient for our purposes, or whether we need to extend the language. Within the project, we investigate argumentation in public, political discourse represented in newspaper text and related user comments with respect to five selected, controversial issues (e.g. free trade agreements). By modeling specific, empiric issues as CNL statements in a knowledge base, we extend existing approaches of argument mining from identification of generic, functional types of argument structures (e.g. premise, claim) towards semantic argument constituents. At the same time, representing such constituents as formally evaluable statements in a knowledge base allows for combination with approaches of abstract argumentation evaluation. We expect this to be a suitable framework to investigate specific argument structures as they generally occur in empiric communication (e.g. incomplete or inconsistent arguments).

近年来的研究主要从两个不同的角度对论证进行研究，一是从自然语言文本中挖掘论证，二是从形式论证评估的角度对论证进行研究。到目前为止，这些研究领域在很大程度上是独立和不相关的。FAME项目的总体目标是将这两种观点及其各自的研究议程联系起来。我们开发了一个框架，它集成了参数挖掘和正式的参数评估。这种连接将允许评估自然语言文本中的“深层”语义参数结构和对检索系统的新形式的查询。这里的挑战是弥合处理自然语言中的文本和评估具有相应形式语义的某种形式语言中表达的参数之间的差距。该提议的假设是受控自然语言（CNL）可以为弥合这一差距提供必要的联系。CNL可以作为议论文的中间表示。它们具有自然语言的外观和感觉，因此足够接近基于自然语言的论点处理。另一方面，我们将使用的CNL是一个也拥有一个定义良好的正式语义，因此适合于正式的评估方法。上述的CNL已经存在。一个突出的例子是企图控制英语（ACE）。ACE很容易被人类理解。同时，它的语义被形式化定义的基础上，翻译成话语表示结构，可以进一步翻译成谓词逻辑。由于ACE的开发最初并没有考虑到论证，我们将彻底调查所提供的语言结构是否足以满足我们的目的，或者我们是否需要扩展语言。在该项目中，我们调查了在公共，政治话语中的报纸文本和相关的用户评论方面的五个选定的，有争议的问题（如自由贸易协定）的论证。通过建模具体的，经验性的问题作为CNL语句在知识库中，我们扩展现有的方法，从通用的，功能类型的参数结构（如前提，索赔）的参数识别语义参数成分。同时，在知识库中将这些成分表示为形式上可评估的陈述，允许与抽象论证评估方法相结合。我们希望这是一个合适的框架来研究特定的论点结构，因为它们通常发生在经验交流（例如不完整或不一致的论点）。