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arXiv 2104.10263cs.CLcs.DLcs.HC
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StateCensusLaws .org:一个用于法律语篇学习的网络应用

StateCensusLaws.org: A Web Application for Consuming and Annotating Legal Discourse Learning

Information Sciences Institute(信息科学研究所);University of Southern California(南加州大学)

Alexander Spangher, Jonathan May

摘要:

在这项工作中,我们创建了一个Web应用程序来突出NLP模型的输出,这些模型经过训练可以解析和标记法律文本中的话语片段。我们的系统主要是建立在记者和法律口译员的头脑中,我们专注于使用美国的州一级法律人口普查数字来分配资源和组织政府。我们的系统公开了我们收集的6,000个与美国人口普查有关的州一级法律的语料库,使用我们构建的25个抓取器来抓取我们发布的州法律网站。我们还建立了一个新颖的,灵活的注释框架,可以处理任何输入文本文档的跨度标记和关系标记,并简单地嵌入到任何网页。这个框架允许记者和研究人员通过纠正和标记新数据来添加到我们的注释数据库中。

英文摘要:

In this work, we create a web application to highlight the output of NLP models trained to parse and label discourse segments in law text. Our system is built primarily with journalists and legal interpreters in mind, and we focus on state-level law that uses U.S. Census population numbers to allocate resources and organize government. Our system exposes a corpus we collect of 6,000 state-level laws that pertain to the U.S. census, using 25 scrapers we built to crawl state law websites, which we release. We also build a novel, flexible annotation framework that can handle span-tagging and relation tagging on an arbitrary input text document and be embedded simply into any webpage. This framework allows journalists and researchers to add to our annotation database by correcting and tagging new data.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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