论文标题
为基于理论的论点质量评估创建域多样性语料库
Creating a Domain-diverse Corpus for Theory-based Argument Quality Assessment
论文作者
论文摘要
参数质量（AQ）的计算模型主要集中于评估总体质量或论证的一个特定特征，例如其令人信服的性或清晰度。但是，先前的工作声称，基于论证的理论维度的评估可能会使作家受益，但是开发这种模型受到缺乏带注释的数据的限制。在这项工作中，我们描述了Gaqcorpus，这是基于理论的AQ的第一个大型域多样性的注释语料库。我们讨论了如何设计注释任务，以可靠地通过众包，制定基于理论的指南来可靠地收集大量判断，从而帮助使AQ的主观判断更加客观。我们演示了如何识别参数并适应三个不同领域的注释任务。我们的工作将为基于理论的论点注释提供信息，并使创建更多样化的语料库以支持计算AQ评估。
Computational models of argument quality (AQ) have focused primarily on assessing the overall quality or just one specific characteristic of an argument, such as its convincingness or its clarity. However, previous work has claimed that assessment based on theoretical dimensions of argumentation could benefit writers, but developing such models has been limited by the lack of annotated data. In this work, we describe GAQCorpus, the first large, domain-diverse annotated corpus of theory-based AQ. We discuss how we designed the annotation task to reliably collect a large number of judgments with crowdsourcing, formulating theory-based guidelines that helped make subjective judgments of AQ more objective. We demonstrate how to identify arguments and adapt the annotation task for three diverse domains. Our work will inform research on theory-based argumentation annotation and enable the creation of more diverse corpora to support computational AQ assessment.
