The aims of this chapter are to survey the resources available for the project of building an exact method that will be helpful for the purpose of identifying arguments in natural language discourse, and to formulate some specific problems that need to be overcome along the way to building the method. It is argued that such a method would be useful as a tool to help students of informal logic identify arguments of the kind they encounter in natural language texts, for example, in newspapers, magazines or on the Internet. The method proposed is based on the use of argumentation schemes representing common types of defeasible arguments (Walton, 1996b; Walton, Reed and Macagno, 2008). The idea is that each scheme is associated with a set of identifiers (key words and markers locating premises and conclusions), and when the right grouping of identifiers is located at some place in a text, the argument mining method locates it as an instance of an argument of some particular, identifiable type (from a list of schemes).

The project is related to the development of argumentation systems in artificial intelligence. One of these technical initiatives, outlined in Section 7, is the project of building an automated argumentation tool for argument mining. The idea is that this tool could go onto the Internet and collect arguments of specifically designated types, for example, argument from expert opinion. These technical initiatives are connected to the aim of finding an exact method for argument identification in informal logic, because the most powerful method would likely turn out to combine both tasks. The most powerful method would have human users apply the automated tool to identify arguments on a tentative basis in a text, and then correct the errors made by the automated tool. It is not hard to see how even a semi-automated procedure of this kind could be extremely helpful for teaching courses in informal logic.