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Register a new userDocument-Level Text Simplification: Dataset, Criteria and Baseline
تبسيط النص على مستوى المستند: مجموعة البيانات والمعايير والخط الأساسي
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تبسيط النص هو تقنية قيمة.ومع ذلك، يقتصر البحث الحالي على تبسيط الجملة.في هذه الورقة، نحدد والتحقيق في مهمة جديدة من تبسيط نص المستندات على مستوى المستند، والتي تهدف إلى تبسيط وثيقة تتكون من جمل متعددة.بناء على مقالب ويكيبيديا، نقوم أولا ببناء مجموعة بيانات واسعة النطاق تسمى D-Wikipedia وأداء التحليل والتقييم البشري عليه لإظهار أن مجموعة البيانات موثوقة.بعد ذلك، نقترح مقياس تقييم تلقائي جديد يسمى D-SARI هو أكثر ملاءمة لمهمة تبسيط مستوى المستند.أخيرا، نقوم باختيار العديد من النماذج التمثيلية كطرازات أساسية لهذه المهمة وأداء التقييم التلقائي والتقييم البشري.نحن نحلل النتائج وأشرح أوجه القصور في النماذج الأساسية.
Text simplification is a valuable technique. However, current research is limited to sentence simplification. In this paper, we define and investigate a new task of document-level text simplification, which aims to simplify a document consisting of multiple sentences. Based on Wikipedia dumps, we first construct a large-scale dataset named D-Wikipedia and perform analysis and human evaluation on it to show that the dataset is reliable. Then, we propose a new automatic evaluation metric called D-SARI that is more suitable for the document-level simplification task. Finally, we select several representative models as baseline models for this task and perform automatic evaluation and human evaluation. We analyze the results and point out the shortcomings of the baseline models.
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