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Register a new usertextit{StateCensusLaws.org}: A Web Application for Consuming and Annotating Legal Discourse Learning
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Added by
Alexander Spangher
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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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.
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News article revision histories have the potential to give us novel insights across varied fields of linguistics and social sciences. In this work, we present, to our knowledge, the first publicly available dataset of news article revision histories, or textit{NewsEdits}. Our dataset is multilingual; it contains 1,278,804 articles with 4,609,43
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