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Extraction Method of Judicial Language Entities Based On Regular Expression

机译:基于正则表达的司法语言实体提取方法

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With the coming of the era of rule of law and intelligence, natural language processing technology plays a pivotal role. At present, a large number of unstructured judicial texts rely on manual processing and archiving. In order to make better use of them and achieve professional application, this paper proposes the goal of analyzing the structure of judgments, extracting the judicial language entities, and describing cases in the form of entity circulation map. As the text carrier of unstructured public events, the judicial document is of better standard format, finely crafted and easy processing, and becomes the research object of this paper. Through the survey of the development of named entity recognition technology, testing and contrasting the use of extraction tool, GATE, as well as considering the cost and effectiveness in the judicial field, this paper put forward a rule-based regular expression method for entity recognition. The scrapy crawler framework is used to obtain judgments classified from China Judgments Online website, so as to realize the task of analyzing the structure of judgments and extracting the judicial language entities.
机译:随着法治时代的来源,自然语言加工技术发挥了关键作用。目前,大量非结构化的司法文本依赖于手动处理和归档。为了更好地利用它们并实现专业应用,本文提出了分析判断结构,提取司法语言实体的结构,并描述实体循环地图形式的案例。作为非结构化公共事件的文本载体,司法文件具有更好的标准格式,精细制作和简单的处理,成为本文的研究对象。通过对命名实体识别技术的发展,测试和对比使用提取工具,门,以及考虑司法领域的成本和有效性,本文提出了一种基于规则的实体识别的正则表达方法。 SCRAPE履带框架用于获得从中国判断在线网站分类的判决,以实现分析判断结构并提取司法语言实体的任务。

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