Legal Entity Tracking Over Time

Abstract

Legal documents, such as court judgments and case files, are often lengthy and contain complex information. One way to understand this information is by using computer programs that can automatically find and highlight names, such as people, laws, courts, or organisations. This process is called Named Entity Recognition (NER). Many tools can locate these names in a single document. In this paper, we take it a step further for Legal Entity Tracking Over Time, which tracks how often and where these names appear across multiple documents over time. This data would enable insights into legal behaviour, such as identifying repeat petitioners, monitoring the activity of judges, or analysing the influence of legal statutes over time. It demonstrates how temporal entity tracking can enhance legal research, support predictive analytics, and contribute to more transparent legal data systems. By organising this information, the project makes legal data easier to understand and more useful for researchers, students, and legal professionals.