تصف هذه الورقة النظام الفائز في مرحلة خطوط الأنابيب الطرفية للمهمة NLPConTribeGraph.يتكون النظام من ثلاث نماذج قائمة على بيرت وتستخدم النماذج الثلاثة لاستخراج الجمل والكيانات والألعاب الثلاثية على التوالي.تظهر التجارب أن أخذ العينات والتدريب الخصم يمكن أن يعزز النظام بشكل كبير.في مرحلة خطوط الأنابيب المناسبة، حصل نظامنا على متوسط F1 من 0.4703، أعلى بكثير من النظام الموضح الثاني الذي حصل على متوسط F1 من 0.3828.
This paper describes the winning system in the End-to-end Pipeline phase for the NLPContributionGraph task. The system is composed of three BERT-based models and the three models are used to extract sentences, entities and triples respectively. Experiments show that sampling and adversarial training can greatly boost the system. In End-to-end Pipeline phase, our system got an average F1 of 0.4703, significantly higher than the second-placed system which got an average F1 of 0.3828.
References used
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