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Question Answering System for Legal Bar Examination Using Predicate Argument Structure

机译:基于谓词参数结构的律师资格考试问答系统

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We developed a question answering system for legal bar exam, which can explain the way system solves based on underlying logical structures. We focus on the set of subject and object with their predicate, i.e. the predicate argument structure, in order to represent structures of legal documents. We implemented a couple of modules using different searching methods. Our system outputs results using these modules by learning each module's confidence value with SVM. We manually analyzed the difficulty level of the problems whether external knowledge is required or not. We created a structured synonym dictionary specialized to the legal domain, where predicates are categorized with their objects. This synonym dictionary could absorb superficial differences of predicates to solve the problems which do not require external knowledge. We confirmed that the system can solve more than 70% of simple problems. Our system achieved the second best score in Task 4 of the COLIEE 2018 shared task.
机译:我们为法律律师考试开发了一个问答系统,该系统可以解释基于基础逻辑结构的系统求解方式。为了表示法律文件的结构,我们专注于带有谓词的主语和宾语的集合,即谓词参数结构。我们使用不同的搜索方法实现了几个模块。通过使用SVM学习每个模块的置信度值,我们的系统使用这些模块输出结果。无论是否需要外部知识,我们都手动分析了问题的难度级别。我们创建了一个专门针对法律领域的结构化同义词词典,在该词典中,谓词按其对象分类。该同义词词典可以吸收谓词的表面差异,从而解决不需要外部知识的问题。我们确认该系统可以解决70%以上的简单问题。我们的系统在COLIEE 2018共享任务的任务4中获得了第二好的成绩。

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