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Register a new userA Novel Global Feature-Oriented Relational Triple Extraction Model based on Table Filling
نموذج استخراج ثلاثي ثلاثي الطاولة على أساس تعبئة الجدول
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تعبئة الجدول تعبئة أساليب استخراج ثلاثية تستند إلى الحصول على اهتمامات بحثية متزايدة بسبب أدائها الواعد وقدراتها على استخراج ثلاث مرات من الجمل المعقدة. ومع ذلك، فإن هذا النوع من الطرق بعيدة عن إمكاناتهم الكاملة لأن معظمهم يركزون فقط على استخدام الميزات المحلية ولكنهم يتجاهلون الجمعيات العالمية للعلاقات وأزواج الرمز المميز، مما يزيد من إمكانية التغاضي عن بعض المعلومات المهمة أثناء الاستخراج الثلاثي. للتغلب على هذا النقص، نقترح نماذج استخراج ثلاثية عالمية موجهة نحو الميزات التي تجعل الاستخدام الكامل من النوعين المذكورين من الجمعيات العالمية. على وجه التحديد، نقوم أولا بتوليد ميزة جدول لكل علاقة. ثم يتم استخراج نوعين من الجمعيات العالمية من ميزات الجدول التي تم إنشاؤها. بعد ذلك، يتم دمج الجمعيات العالمية الملغومة في ميزة الجدول في كل علاقة. يتم تنفيذ عملية توليد من الألغام "" عدة مرات بحيث تكون ميزة الجدول في كل علاقة خطوة بخطوة. أخيرا، يتم ملء جدول كل علاقة بناء على ميزة جدولها المكرر، ويتم استخراج جميع ثلاث مرات المرتبطة بهذه العلاقة بناء على جدولها المليء. نقيم النموذج المقترح على ثلاث مجموعات بيانات معيار. تظهر النتائج التجريبية نموذجنا فعالا وتحقق نتائج أحدث النتائج على جميع مجموعات البيانات هذه. يتوفر رمز المصدر لعملنا على: https://github.com/neukg/grte.
Table filling based relational triple extraction methods are attracting growing research interests due to their promising performance and their abilities on extracting triples from complex sentences. However, this kind of methods are far from their full potential because most of them only focus on using local features but ignore the global associations of relations and of token pairs, which increases the possibility of overlooking some important information during triple extraction. To overcome this deficiency, we propose a global feature-oriented triple extraction model that makes full use of the mentioned two kinds of global associations. Specifically, we first generate a table feature for each relation. Then two kinds of global associations are mined from the generated table features. Next, the mined global associations are integrated into the table feature of each relation. This generate-mine-integrate'' process is performed multiple times so that the table feature of each relation is refined step by step. Finally, each relation's table is filled based on its refined table feature, and all triples linked to this relation are extracted based on its filled table. We evaluate the proposed model on three benchmark datasets. Experimental results show our model is effective and it achieves state-of-the-art results on all of these datasets. The source code of our work is available at: https://github.com/neukg/GRTE.
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In this work, three new compounds of benzoxazine monomers were
synthesized based on (phenol, hydroquinone, 2-naphthol) and
triethoxysilyl propyl amine (TESPA) and paraformaldehyde. (TESPA)
were used to study its effect on the thermal stability of
polybenzoxazine
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