Document Processing · Enterprise Knowledge Search
Mexico's Supreme Court, the Supreme Court of Justice of the Nation (SCJN), digitized millions of physical files and built a legal search engine for the public using language models created with artificial intelligence and Azure cognitive services.
Reported impact
Today, the model is trained to identify the names of organizations, suggest precepts in the field of human rights, identify executory statements using common language, and to classify articles of the American Convention on Human Rights, the UN Universal System of Human Rights, the Constitutional Courts of Spain and Chile, and the Courts of different other countries.
Mexico's Supreme Court, the Supreme Court of Justice of the Nation (SCJN), digitized millions of physical files and built a legal search engine for the public using language models created with artificial intelligence and Azure cognitive services. “In Azure and particularly, with Databricks Machine Learning we could quickly build an architecture for data processing and model training.” The Supreme Court of Justice of the Nation (SCJN) is the Highest Constitutional Court of Mexico and head of the Judiciary of the Mexican Federation. Through its judicial resolutions, the court defends the Political Constitution of the United Mexican States and maintains balance between the different powers and spheres of Mexico’s government.
Mexico's Supreme Court, the Supreme Court of Justice of the Nation (SCJN), digitized millions of physical files and built a legal search engine for the public using language models created with artificial intelligence and Azure cognitive services.
The Supreme Court of Justice of the Nation (SCJN) is the Highest Constitutional Court of Mexico and head of the Judiciary of the Mexican Federation. Through its judicial resolutions, the court defends the Political Constitution of the United Mexican States and maintains balance between the different powers and spheres of Mexico’s government.
The digital transformation of SCJN began in 2013, by implementing collaborative environments using Microsoft Office 365, Outlook, and Sharepoint. Under SCJN President Arturo Zaldivar in 2019, the court embarked on an ambitious project to use disruptive technologies, such as cloud computing and artificial intelligence to make the most of the court’s legal record.
Today, the model is trained to identify the names of organizations, suggest precepts in the field of human rights, identify executory statements using common language, and to classify articles of the American Convention on Human Rights, the UN Universal System of Human Rights, the Constitutional Courts of Spain and Chile, and the Courts of different other countries.
“In Azure and particularly, with Databricks Machine Learning we could quickly build an architecture for data processing and model training.”
Review how this reference was scored and trace each normalized claim back to its documented source.
Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
Field coverage shows which facts each source supports. Dates are shown only when documented by the source.
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