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

TL;DR

This paper introduces a web application designed for legal discourse analysis, focusing on state laws related to the U.S. Census, featuring a new annotation framework and a publicly available corpus for legal NLP research.

Contribution

The work presents a novel web-based annotation framework and releases a large corpus of state laws, facilitating legal NLP tasks and discourse analysis.

Findings

Created a web app for legal discourse annotation

Collected and released a corpus of 6,000 laws related to the Census

Developed a flexible, embeddable annotation framework

Abstract

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.