民事裁判文书中论辩元素识别研究

Research on the Identification of Argumentation Elements in Civil Judgment Documents

【目的】构建适用于民事判决文书的论辩结构,实现论辩元素的自动化抽取。【方法】基于图尔敏论证模型构建民事裁判文书的论辩结构,用于指导民事裁判文书论辩语料库的标注。随后,提出一种基于上下文感知的多头注意力论辩元素分类模型(CAMA-AECM)用于自动抽取论辩元素。【结果】本文模型在不同论辩主体的数据集上均表现出较好的性能。在Macro-F1值指标上,模型在原告、被告和法院这三个论辩主体对应的数据集上分别实现了最大1.73%、5.72%和3.92%的提升。【局限】受限于论辩语料构建的成本和规模,并未探索全部民事案由的裁判文书论辩结构和特征。【结论】本研究构建的模型有效实现了论辩元素的自动识别,不仅可以提高对裁判文书中论辩知识的挖掘能力,还为裁判文书自动化分析提供了一个新的工具。

[Objective]This study aims to construct an argumentation structure suitable for civil judgment documents and to achieve automated extraction of argumentation elements.[Methods]Based on the Toulmin’s argument model,we constructed an argumentation structure for civil judgment documents to guide the annotation of a corpus of argumentation in civil judgment documents.We then proposed a Context-Aware Multi-Head Attention Argumentation Element Classification Model(CAMA-AECM)for the automatic extraction of argumentation elements.[Results]The proposed model showed superior performance on different datasets of argumentation subjects.In terms of Macro-F1 score,the model achieved maximum improvements of 1.73%,5.72%,and 3.92%on the datasets corresponding to the plaintiff,defendant,and court,respectively.[Limitations]Due to the cost and scale of constructing argumentation corpora,we did not explore the argumentation structure and features of judgment documents for all civil cases.[Conclusions]This model can effectively identify argumentation elements,not only enhancing the in-depth exploration of argumentation knowledge in judgment documents,but also providing a new automated tool for judgment document analysis.