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Feasible Annotation Scheme for Capturing Policy Argument Reasoning using Argument Templates

机译:使用参数模板捕获策略参数推理的可行注释方案

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Most of the existing works on argument mining cast the problem of argumentative structure identification as classification tasks (e.g. attack-support relations, stance, explicit premise/claim). This paper goes a step further by addressing the task of automatically identifying reasoning patterns of arguments using predefined templates, which is called argument template (AT) instantiation. The contributions of this work are three-fold. First, we develop a simple, yet expressive set of easily annotatable ATs that can represent a majority of writer's reasoning for texts with diverse policy topics while maintaining the computational feasibility of the task. Second, we create a small, but highly reliable annotated corpus of instantiated ATs on top of reliably annotated support and attack relations and conduct an annotation study. Third, we formulate the task of AT instantiation as structured prediction constrained by a feasible set of templates. Our evaluation demonstrates that we can annotate ATs with a reasonably high inter-annotator agreement, and the use of template-constrained inference is useful for instantiating ATs with only partial reasoning comprehension clues.
机译:现有的关于论证挖掘的大多数工作都将论证结构的识别问题归类为分类任务(例如攻击-支持关系,立场,明确的前提/主张)。本文通过解决使用预定义的模板自动识别参数的推理模式的任务而进一步前进,这称为参数模板(AT)实例化。这项工作的贡献是三方面的。首先,我们开发了一组简单但易于表达的易于注释的AT,这些AT可以代表大多数作者对具有不同策略主题的文本的推理,同时保持任务的计算可行性。其次,我们在可靠的带注释的支持和攻击关系的基础上,创建了一个小型但高度可靠的带注释的实例化AT主体,并进行了注释研究。第三,我们将AT实例化的任务表述为受一组可行模板约束的结构化预测。我们的评估表明,我们可以使用合理的批注者之间的较高协议对AT进行批注,并且模板约束推理的使用对于仅使用部分推理理解线索的AT实例化是有用的。

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