Towards a machine understanding of Malawi legal text

• DOI: 10.1007/s10506-021-09303-6
• Publication Date: 2021-10-23T07:02:28Z
• Authors: Amelia V. Taylor; Eva Mfutso-Bengo
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 16. Peace & justice

Legal professionals in Malawi find themselves having to rely on a limited number of textbooks, outdated law reports, and inadequate library services. Some of the challenges in accessing legal text have been addressed through the introduction of a case management system and services for disseminating e-documents. However, these documents are in image form, are unstructured: contain no useful legal meta-data, summaries, keynotes, and do not support a system of citation that is essential to legal research. This situation is also true of most legal text that is being made available on the internet. While advances in document processing and machine learning have benefited many fields, legal research is still only marginally affected. In this interdisciplinary research, the authors build semi-automatic tools for creating a corpus of Malawi criminal law decisions annotated with legal meta-data, case and law citations. The authors develop a new methodology for classifying Malawi criminal case law according to the recently introduced International Classification of Crime for Statistical Purposes (ICCS). The study employs well-known machine learning libraries such as spaCy and Gensim.