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一个系统的程序,从印尼的司法判决中提取法律实体
Eka Qadri Nuranti1, Naili Suri Intizhami1, Evi Yulianti2
1Department of Computer Science, Institut Teknologi Bacharuddin Jusuf Habibie, Parepare, Indonesia.
MethodsX
|January 6, 2026
概括
本研究介绍了一种系统的方法,使用命名实体识别 (NER) 来从印尼法院判决中提取法律实体. 该方法通过对司法数据进行结构化来提高法律透明度和研究.
科学领域:
- 法律信息学 法律信息学
- 计算语言学 计算语言学
- 自然语言处理自然语言处理.
背景情况:
- 从非结构化的司法决定中提取法律实体是具有挑战性的.
- 印尼的法律文件需要专门的方法来获取信息.
- 命名实体识别 (NER) 为结构化数据提取提供了一个强大的解决方案.
研究的目的:
- 开发和介绍一种系统的方法来从印尼司法判决中提取法律实体.
- 应用结构化的命名实体识别 (NER) 方法来处理法律文本.
- 加强法律透明度,促进对印尼司法数据的研究.
主要方法:
- 开发了一个结构化的管道,用于收集,过和注释印尼法院判决.
- 从印度尼西亚最高法院网站自动抓取网页,然后进行手动过.
- 使用Label Studio手动注释2687份法庭文件,通过Fleiss' Kappa评估注释者之间的协议 (平均分数为0.705).
- 对50多种法人实体类型实施层次结构和BIO标签方案.
主要成果:
- 成功注释了2687个印度尼西亚法院的判决,涉及三个层次:一审,上诉和上诉.
- 实现了良好的注释器间可靠性 (Fleiss' Kappa = 0.705),确保了注释质量.
- 开发了一种能够标记50多种类型法律实体的方法,包括被告,法官,法律条款,指控和判决.
- 证明了法律信息提取,分类和分析方法的实用性.
结论:
- 拟议的系统方法提供了一个结构化的管道,用于从印尼司法判决中提取法律实体.
- 使用BIO标记和层次结构的NER方法对于处理法律文本是有效的.
- 这种方法对提高法律透明度和推进印尼司法数据分析研究做出了重大贡献.
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