نادرا ما تعطي أنظمة NLP اعتبارا خاصا للأرقام الموجودة في النص.هذا يتناقض بشكل صارخ مع توافق الآراء في علم الأعصاب، في الدماغ، يتم تمثيل الأرقام بشكل مختلف عن الكلمات.نحن نقوم بترتيب أعمال NLP الأخيرة على الحساب في تصنيف شامل للتصنيف والأساليب.نقوم بفحص الفكرة الشخصية للعسمة في 7 مجموعات فرعية، مرتبة على طول الأبعاد: الحبيبية (التقريبي الدقيق التقريبي) والوحدات (مجردة مقابل مؤسسة).نقوم بتحليل الخيارات التمثيلية لا تعد ولا تحصى التي قامت بأكثر من عشرة أرقام منشورة سابقا وروائح الكشف.نتوضع أفضل الممارسات لتمثيل الأرقام في النص والتعبير عن رؤية للحساب الشمولي في NLP، تتألف من مفاضات التصميم وتقييم موحد.
NLP systems rarely give special consideration to numbers found in text. This starkly contrasts with the consensus in neuroscience that, in the brain, numbers are represented differently from words. We arrange recent NLP work on numeracy into a comprehensive taxonomy of tasks and methods. We break down the subjective notion of numeracy into 7 subtasks, arranged along two dimensions: granularity (exact vs approximate) and units (abstract vs grounded). We analyze the myriad representational choices made by over a dozen previously published number encoders and decoders. We synthesize best practices for representing numbers in text and articulate a vision for holistic numeracy in NLP, comprised of design trade-offs and a unified evaluation.
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