Abstract
In 2016, the Conference of Chief Justices (CCJ) and the Conference of State Court Administrators (COSCA) endorsed recommendations to leverage technology to improve civil case management. In particular, Natural Language Processing (NLP) and related tools could be used to support two areas of civil case processing: sorting cases at filing based on the anticipated level of judicial involvement in case management, and confirming that essential procedural requirements have been satisfied before entering final judgments in cases.
To explore the feasibility of NLP to support court operations in these two areas, the National Center for State Courts (NCSC) designed three distinct Proof of Concept (POC) projects. NCSC partnered with three general jurisdiction courts that participated in the CJI automated civil case triage project to use NLP techniques to identify and extract key terms and characteristics from the case pleadings for use in assigning cases to an appropriate civil case processing track. For quality control over high-volume dockets, the NCSC worked with the Cleveland Municipal Court on a POC to identify inaccurate or missing information from case documents in its consumer debt collection docket that would signal the need for increased judicial review. The NCSC partnered with two vendors that specialize in NLP technologies to control for variation in vendor quality. In addition, NCSC interviewed IT staff in the superior courts of Maricopa County, Arizona and Orange County, California about their experiences implementing these technologies for purposes similar to the POCs.
This abstract has been taken from the authors' introduction.
Document Type
Report
Publication Date
5-2023
Publication Information
National Center for State Courts (May 2023)
Repository Citation
Hannaford-Agor, Paula and Okazaki, Jannet, "Use of Natural Language Processing (NLP) in Civil Case Management: A Report on Three Proof of Concept Projects" (2023). Faculty Publications. 2377.
https://scholarship.law.wm.edu/facpubs/2377