Concepts and measures of bureaucratic constraints in European Union laws from hand-coding to machine-learning

2023-06-28 · Source: Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai · Field: Technology & Digital — Artificial Intelligence & Machine Learning · Depth: Intermediate, quick

Summary

Machine learning models are being developed to analyze and measure bureaucratic constraints within European Union laws, marking a transition from traditional hand-coding methods. These models are designed to learn intricate relationships between text tokens and predefined entity categories. This learning process relies on training data derived from two randomly selected samples of sentences, which are extracted from a larger pre-processed corpus. Crucially, this training data undergoes meticulous manual annotation using "Prodigy," a Python-implemented platform, ensuring high-quality labels for the models to effectively identify and categorize relevant legal concepts. This methodology aims to automate the identification and quantification of regulatory complexities in EU legal texts.

Key takeaway

For Research Scientists or Legal Professionals tasked with analyzing extensive European Union legal documents, this approach highlights a viable path to automate the measurement of bureaucratic constraints. You should recognize that while machine learning offers significant scalability, its effectiveness hinges on meticulously prepared, manually annotated training data. Consider platforms like "Prodigy" for efficient and precise data labeling to ensure robust model performance in legal text analysis.

Key insights

Models learn from manually annotated text to analyze EU law constraints.

Principles

• Manual annotation is key for training specialized legal NLP models.

Method

Models learn text-entity relations from manually annotated sentence samples, extracted from a pre-processed corpus using the Python platform "Prodigy".

In practice

• Automate legal text analysis.
• Quantify bureaucratic constraints.

Topics

• Machine Learning
• Natural Language Processing
• Text Annotation
• Prodigy Platform
• European Union Law
• Bureaucratic Constraints

Best for: AI Scientist, NLP Engineer, Research Scientist, Legal Professional

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Editorial summary, takeaway, and curation by AIssential. Original article published by Explosion · Developer tools and consulting for AI, Machine Learning and NLP - Explosion.ai.