基于论证型式应用的论证挖掘

本文旨在为构建一种以论证型式为基础的方法,用以帮助非形式逻辑的学生分析自然语言对话的文本,并识别出其中所出现的常见论证类型.他们在这一过程中时常会错误地辨识论证类型,而本文将表明所发展的这种方法对于学习非形式逻辑的学生们是非常有帮助的.另外,对于那些可用于构建一种有用的论证识别方法的理论资源,本文对其最新发展动态进行了考察,并且也概览了当前人工智能领域中所发展的自动论证挖掘工具.

Argument Mining by Applying Argumentation Schemes

The aim of this paper is to lay the foundations for building a method based on argumentation schemes that can be used to help a student of informal logic to go through a text of discourse in a natural language and identify common types of arguments that occur in the text. It is shown how this procedure is very helpful for students learning informal logic skills, as they sometimes misidentify arguments. The paper presents the state-of-the-art on what resources are available to build a useful argument identification procedure, and includes a survey of work done on automated argument mining tools used in artificial intelligence.