论文标题
depparliament：法律领域的基准和国会账单预测数据集
DeepParliament: A Legal domain Benchmark & Dataset for Parliament Bills Prediction
论文作者
论文摘要
本文介绍了Deepparliament，这是一种法律域基准数据集，该数据集收集了账单文件和元数据并执行各种账单状态分类任务。拟议的数据集文本涵盖了从1986年到现在的广泛账单，并包含有关议会账单内容的更丰富信息。本文提供了数据收集，详细统计和分析。此外，我们尝试了不同类型的模型，从RNN到预估计并报告了结果。我们提出了两个新的基准：二进制和多级账单状态分类。为帐单文件和相关的支持任务开发的模型可以帮助议会成员（MPS），总统和其他法律从业人员。它将有助于审查或优先考虑账单，从而加快计费流程，提高决策质量并减少两套房屋的时间消耗。考虑到该国民主的基础是议会和州立法机关，我们预计我们的研究将是合法NLP社区的重要补充。这项工作将是第一个提出议会账单预测任务的工作。为了提高法律AI资源的可访问性并促进可重复性，我们在Github.com/monk1337/deeepparliament上公开访问代码和数据集
This paper introduces DeepParliament, a legal domain Benchmark Dataset that gathers bill documents and metadata and performs various bill status classification tasks. The proposed dataset text covers a broad range of bills from 1986 to the present and contains richer information on parliament bill content. Data collection, detailed statistics and analyses are provided in the paper. Moreover, we experimented with different types of models ranging from RNN to pretrained and reported the results. We are proposing two new benchmarks: Binary and Multi-Class Bill Status classification. Models developed for bill documents and relevant supportive tasks may assist Members of Parliament (MPs), presidents, and other legal practitioners. It will help review or prioritise bills, thus speeding up the billing process, improving the quality of decisions and reducing the time consumption in both houses. Considering that the foundation of the country's democracy is Parliament and state legislatures, we anticipate that our research will be an essential addition to the Legal NLP community. This work will be the first to present a Parliament bill prediction task. In order to improve the accessibility of legal AI resources and promote reproducibility, we have made our code and dataset publicly accessible at github.com/monk1337/DeepParliament
