A growing number of legal documents ranging from government regulations to case files are now available in the digital form. Coupled with the advances in natural language processing and machine learning, this gives rise to a great potential for extracting semantic insights from these documents and developing predictive models. The text contained in legal documents can lead to ambiguity and multiple interpretations, making tasks such as regulation violation identification and penalty estimation challenging. We develop a system that performs the semantic processing of documents at multiple levels to carry out a number of analyses and predictions that could help legal actors improve their productivity.
Our Team: