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In this work, we create a web application to highlight the output of NLPmodels trained to parse and label discourse segments in law text. Our system isbuilt primarily with journalists and legal interpreters in mind, and we focuson state-level law that uses U.S. Census population numbers to allocateresources and organize government.  Our system exposes a corpus we collect of 6,000 state-level laws that pertainto 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 canhandle span-tagging and relation tagging on an arbitrary input text documentand be embedded simply into any webpage. This framework allows journalists andresearchers to add to our annotation database by correcting and tagging newdata.

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