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Register a new userIterative Paraphrastic Augmentation with Discriminative Span Alignment
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مجردة، نقدم استراتيجية تكبير الشلل الرنين على أساس إعادة الصياغة المعردة على مستوى العقوبة ومحاذاة الإحصاء التمييزي.يسمح نهجنا للتوسع على نطاق واسع في مجموعات البيانات الحالية أو الإبداع السريع لمجموعات البيانات الجديدة باستخدام كوربس صغير المنتج يدويا.نوضح نهجنا مع تجارب في مشروع بيركلي فرامينيت، وهي لغة تفهم لغة واسعة النطاق تمتد أكثر من عقدين من العمل البشري.مع أربعة أيام من جمع البيانات التدريبية لنموذج محاذاة تمتد ويوم واحد من حساب متوازي، فإننا نقوم تلقائيا بإنشاء وإطلاق سراح المجتمع 495،300 فريد من فريد من 495300 (الإطار، الزناد) في سياقات حكومية متنوعة، وهو توسع تقريبا 50 أضعاف فوق Framenet V1.7.يتم تقييم مجموعة البيانات الناتجة بشكل جوهري ومن خارجي بالتفصيل، وإظهار نتائج إيجابية على مهمة المصب.
Abstract We introduce a novel paraphrastic augmentation strategy based on sentence-level lexically constrained paraphrasing and discriminative span alignment. Our approach allows for the large-scale expansion of existing datasets or the rapid creation of new datasets using a small, manually produced seed corpus. We demonstrate our approach with experiments on the Berkeley FrameNet Project, a large-scale language understanding effort spanning more than two decades of human labor. With four days of training data collection for a span alignment model and one day of parallel compute, we automatically generate and release to the community 495,300 unique (Frame,Trigger) pairs in diverse sentential contexts, a roughly 50-fold expansion atop FrameNet v1.7. The resulting dataset is intrinsically and extrinsically evaluated in detail, showing positive results on a downstream task.
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