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Register a new userMultiOpEd: A Corpus of Multi-Perspective News Editorials
متعددة المنصوص عليها: كائنات افتتاحية أخبار متعددة المنظور
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نقترح خلاصات الأخبار المفتوحة، ونحن مؤلف أخبار مفتوحة يدعم المهام المختلفة المتعلقة بنية الحاليات في الافتتاحيات الإخبارية، مع التركيز على اكتشاف المنظور التلقائي. أخبار الافتتاحية هي نوع من النص المقنع، حيث يكون بنية الحجة ضمنية عادة. ومع ذلك، فإن الحجج المقدمة في افتتاحية عادة مركز حول أطروحة موجزة مركزة، والتي نشير إليها كمنظورهم. تهدف Multioped إلى دعم دراسة مهام متعددة ذات صلة باكتشاف المنظور التلقائي، حيث من المتوقع أن ينتج النظام عبارة أطروحة واحدة الجملة التي تلخص الحجج المقدمة. نقول أن تحديد ومخلص من وجهات نظر اللغة الطبيعية من الافتتاحيات هو خطوة حاسمة نحو دراسة هيكل الجدال الضمني في الأخبار الافتتاحية. نناقش أولا التحديات وتحديد عدد قليل من المهام المفاهيمية تجاه هدفنا. لإظهار فائدة المهام متعددة المنصوص عليها، ندرس مشكلة تلخيص المنظور في بيئة تعليمية متعددة المهام، كدراسة حالة. نظرا لأنه، مع المهام المستحثة كامرأة مساعدة، يمكننا تحسين جودة ملخص المنظور الذي تم إنشاؤه. نأمل أن يكون multiopeded موردا مفيدا للدراسات المستقبلية عن الجدال في مجال تحرير الأخبار.
We propose MultiOpEd, an open-domain news editorial corpus that supports various tasks pertaining to the argumentation structure in news editorials, focusing on automatic perspective discovery. News editorial is a genre of persuasive text, where the argumentation structure is usually implicit. However, the arguments presented in an editorial typically center around a concise, focused thesis, which we refer to as their perspective. MultiOpEd aims at supporting the study of multiple tasks relevant to automatic perspective discovery, where a system is expected to produce a single-sentence thesis statement summarizing the arguments presented. We argue that identifying and abstracting such natural language perspectives from editorials is a crucial step toward studying the implicit argumentation structure in news editorials. We first discuss the challenges and define a few conceptual tasks towards our goal. To demonstrate the utility of MultiOpEd and the induced tasks, we study the problem of perspective summarization in a multi-task learning setting, as a case study. We show that, with the induced tasks as auxiliary tasks, we can improve the quality of the perspective summary generated. We hope that MultiOpEd will be a useful resource for future studies on argumentation in the news editorial domain.
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