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Register a new userWhat If Sentence-hood is Hard to Define: A Case Study in Chinese Reading Comprehension
ما إذا كان من الصعب تحديد العقوبة: دراسة حالة في فهم القراءة الصينية
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إن الفهم القراءة الآلي (MRC) هو مهمة NLP الصعبة التي يتطلبها التعامل بعناية مع جميع الحبيبات اللغوية من Word، الجملة إلى المرور.بالنسبة إلى MRC الاستخراجية، تم عرض فترة الإجابة في الغالب عن طريق الأدلة الرئيسية الوحدات اللغوية، حيث إنها جملة في معظم الحالات.ومع ذلك، اكتشفنا مؤخرا أن الجمل قد لا تكون محددة بوضوح في العديد من اللغات إلى النطاقات المختلفة، بحيث يؤدي ذلك إلى ما يسمى بمشكلة غموض وحدة الموقع ونتيجة لذلك، مما يجعل من الصعب على النموذج لتحديد الجملة التي تحتوي على تمديد الإجابة بالضبط عندماالجملة نفسها لم يتم تعريفها بوضوح على الإطلاق.مع أخذ اللغة الصينية كدراسة حالة، فإننا نوضح وتحليل هذه الظاهرة اللغوية واقترح قارئ مقابلة مع التنافق الصريح بالإجمال لتخفيف مثل هذه المشكلة.يساعد قارئنا المقترح في النهاية في تحقيق أحدث حالة جديدة في مؤشر MRC الصيني ويظهر إمكانات كبيرة في التعامل مع لغات أخرى.
Machine reading comprehension (MRC) is a challenging NLP task for it requires to carefully deal with all linguistic granularities from word, sentence to passage. For extractive MRC, the answer span has been shown mostly determined by key evidence linguistic units, in which it is a sentence in most cases. However, we recently discovered that sentences may not be clearly defined in many languages to different extents, so that this causes so-called location unit ambiguity problem and as a result makes it difficult for the model to determine which sentence exactly contains the answer span when sentence itself has not been clearly defined at all. Taking Chinese language as a case study, we explain and analyze such a linguistic phenomenon and correspondingly propose a reader with Explicit Span-Sentence Predication to alleviate such a problem. Our proposed reader eventually helps achieve a new state-of-the-art on Chinese MRC benchmark and shows great potential in dealing with other languages.
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