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Subject Event Extraction from Chinese Court Verdict Case via Frame-filling

机译：通过框架填充从中国法院判决书中提取主题事件

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摘要

At present, the query and acquisition of the fragmented knowledge in Chinese court verdicts mainly adopt the class case retrieval method based on the search engine and the rough extraction method for a part of the data in court verdicts. These traditional methods cannot structurally extract fragmented knowledge in Chinese court verdicts and meet the needs of people for the follow-up analysis of court verdicts. Thus, in this paper, we present a structured subject event extraction method (SEE) for Chinese court verdict cases combining with techniques of event extraction (EE) and attribute-value pair extraction (AVPE). Specifically, we provide a subject event representation frame for organizing fragmented knowledge in Chinese court verdict cases. Then, we extract subject events from the unstructured cases based on the trained sequence labeling models and constructed heuristic rules, and fill them into the subject event representation frame in the form of attribute-value pairs (AVPs). The experimental results show that SEE can efficiently and automatically extract subject events from Chinese court verdict cases and visually display them via frame-filling, which promotes the efficiency of people in searching for legal materials and facilitates further research and analysis.
机译：目前，中国法庭判决中碎片知识的查询和收购主要采用了基于搜索引擎的课程案例检索方法和法院判决中的一部分数据的粗略提取方法。这些传统方法无法在中国法院判决中构建分散知识，满足人们对法院判决的后续分析的需求。因此，在本文中，我们提出了一种结构化的主题提取方法（参见）用于中式法庭判决病例，其与事件提取（EE）和属性值对提取（AVPE）的技术组合。具体而言，我们提供了一个主题事件表示框架，用于在中国法庭判决案件中组织碎片知识。然后，我们基于训练的序列标记模型和构造的启发式规则来提取来自非结构化案例的主题事件，并以属性值对（AVPS）的形式填充它们进入主题事件表示帧。实验结果表明，可以有效地和自动从中国法庭判决案例中提取主题事件，并通过帧填充目视显示它们，这促进了人们寻找法律材料的效率，并促进进一步的研究和分析。

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