基于法律裁判文书的事件抽取及其应用，包括数据的分词、词性标注、命名实体识别、事件要素抽取和判决结果预测等内容
针对交通肇事案件的裁判文书进行事件要素抽取，并在此基础上加入判决结果预测、案件相似度匹配等应用场景。
数据来源：OpenLaw
分词：主要基于pkuseg
词性标注：基于哈工大LTP/pkuseg
命名实体识别：基于BiLSTM-CRF，涉及到的实体包括人名、地名、车辆信息、各类犯罪情节、判决结果等
应用部分：包括判决结果的预测、案件相似度的对比等
您好，我也是做事件抽取的，你公布的数据集非常有用，希望能加联系方式，进一步交流，QQ：2249127476
你好，请问分词是不是为了方便手动标注数据？
冒昧请问一下test5_noises.csv数据在哪里生成，另外我打算做基于结构化事件知识的事件推理。例如判决结果预测等等，请问您这边有什么好的思路推荐码？
我在项目里面找不到test5_noises.csv但是06判决结果预测进行结果分析的时候要这个文件，求解
请问您一下，咱们这个模型在应用的第二个部分-案件处理结果预测这一方面，后续有没有设计评估代码的计划嘞。或者想请问您可以使用哪些指标或者方法对于模型预测的结果进行预测。
你好。在06判决结果预测中，训练数据train6.csv中，文件内容如下。
请问分别代表什么含义：
80,8,20,-45,-15,0,1
谢谢！！
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