يوروفوك هو عبارات متعددة اللغات تم بناؤها لتنظيم الوثائقي التشريعي لمؤسسات الاتحاد الأوروبي.يحتوي على الآلاف من الفئات في مستويات مختلفة من الخصوصية وتستهدف واصفاتها من قبل النصوص القانونية في ثلاثين لغة تقريبا.في هذا العمل، نقترح إطارا موحدا لتصنيف EUROVOC في 22 لغة من خلال ضبط نماذج اللغة المحولات الحديثة التي تعتمد على المحولات.نحن ندرس على نطاق واسع أداء نماذجنا المدربة وإظهار أنها تعمل بشكل كبير على تحسين النتائج التي تم الحصول عليها بواسطة أداة مماثلة - جيم - على نفس مجموعة البيانات.تم فتح الرمز والنماذج التي تم ضبطها بشكل جيد مصادر، بالإضافة إلى واجهة برنامجية تخفف عملية تحميل أوزان طراز مدرب وتصنيف مستند جديد.
EuroVoc is a multilingual thesaurus that was built for organizing the legislative documentary of the European Union institutions. It contains thousands of categories at different levels of specificity and its descriptors are targeted by legal texts in almost thirty languages. In this work we propose a unified framework for EuroVoc classification on 22 languages by fine-tuning modern Transformer-based pretrained language models. We study extensively the performance of our trained models and show that they significantly improve the results obtained by a similar tool - JEX - on the same dataset. The code and the fine-tuned models were open sourced, together with a programmatic interface that eases the process of loading the weights of a trained model and of classifying a new document.
References used
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