论文标题

学习检查合同不一致

Learning to Check Contract Inconsistencies

论文作者

Zhang, Shuo, Zhao, Junzhou, Wang, Pinghui, Xu, Nuo, Yang, Yang, Liu, Yiting, Huang, Yi, Feng, Junlan

论文摘要

合同一致性对于确保合同的法律有效性很重要。在许多情况下,合同是通过以预编译表格填写空白来写的。由于粗心大意,两个应该填充相同(或不同)内容的空白可能会错误地填充不同的(或相同)内容。这将导致合同不一致的问题,这可能严重损害合同的法律有效性。解决此问题的传统方法主要依赖于手动合同审查,这是劳动密集型且昂贵的。在这项工作中,我们制定了一种新颖的合同不一致检查(CIC)问题,并设计一个称为Pair-Wise空白分辨率(PBR)的端到端框架,以高精度解决CIC问题。我们的PBR模型包含一个新颖的空白编码器,以应对建模毫无意义的空白的挑战。 BlankCoder采用了两阶段的注意机制,该机制将毫无意义的空白与其相关描述相关联,同时避免纳入不相关的上下文单词。在实际数据集上进行的实验显示了我们方法的有希望的性能,在CIC问题中,平衡精度为94.05%,F1得分为90.90%。

Contract consistency is important in ensuring the legal validity of the contract. In many scenarios, a contract is written by filling the blanks in a precompiled form. Due to carelessness, two blanks that should be filled with the same (or different)content may be incorrectly filled with different (or same) content. This will result in the issue of contract inconsistencies, which may severely impair the legal validity of the contract. Traditional methods to address this issue mainly rely on manual contract review, which is labor-intensive and costly. In this work, we formulate a novel Contract Inconsistency Checking (CIC) problem, and design an end-to-end framework, called Pair-wise Blank Resolution (PBR), to solve the CIC problem with high accuracy. Our PBR model contains a novel BlankCoder to address the challenge of modeling meaningless blanks. BlankCoder adopts a two-stage attention mechanism that adequately associates a meaningless blank with its relevant descriptions while avoiding the incorporation of irrelevant context words. Experiments conducted on real-world datasets show the promising performance of our method with a balanced accuracy of 94.05% and an F1 score of 90.90% in the CIC problem.

扫码加入交流群

加入微信交流群

微信交流群二维码

扫码加入学术交流群,获取更多资源