An NLP-based statistical reporting methodology applied to court decisions

Natural Language Processing (NLP) algorithms have significantly advanced the capabilities of understanding, processing and generating human language. However, one persistent challenge in NLP is the problem of uncertainty, due e.g. to the inherent complexity of human language, variations in language usage across different contexts and domains, and the presence of noisy or incomplete data. In this work we take in consideration this problem for statistics derived from court documents by NLP systems.