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Register a new userPredicting and Explaining French Grammatical Gender
توقع وشرح الجنس النحوي الفرنسي
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قد يتم تحديد الجنس النحاسي من قبل دلالات أو إجمالية أو علم الصوتيات أو يمكن أن يكون تعسفيا.تحديد الأنماط في العوامل التي تحكم نون الجنسين يمكن أن تكون مفيدة لمتعلمي اللغة، وفهم المصادر اللغوية الفطرية للتحيز بين الجنسين.قد يتم استبدال النهج اليدوية القائمة على القواعد اليدوية من خلال النهج الحسابية الأكثر دقة وقابلة للتطوير ولكن أصعب من أجل تفسيرها للتنبؤ بنوع الجنس من المعلومات النموذجية.في هذا العمل، نقترح نماذج تصنيف الجنسية القابلة للتفسير للفرنسية، والتي تحصل على أفضل ما في العالمين.نقدم نهج عصبي عالية الدقة التي تعززها نهج قائم على بديل عالمي جديد لتوضيح التنبؤات.نقدم سمات مساعدة "لتوفير تعقيد تفسير الضبط.
Grammatical gender may be determined by semantics, orthography, phonology, or could even be arbitrary. Identifying patterns in the factors that govern noun genders can be useful for language learners, and for understanding innate linguistic sources of gender bias. Traditional manual rule-based approaches may be substituted by more accurate and scalable but harder-to-interpret computational approaches for predicting gender from typological information. In this work, we propose interpretable gender classification models for French, which obtain the best of both worlds. We present high accuracy neural approaches which are augmented by a novel global surrogate based approach for explaining predictions. We introduce auxiliary attributes' to provide tunable explanation complexity.
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Since language is a natural concrete phenomenon, it became a fact that
language has been a matter of induction by making it go through
experiment in attempt to attain the rules that can take hold of the
language's partial phenomena and organize th
em in general regulations,
and if we observed the linguistic matter which grammarians investigated,
we could find that their work involved both the complete induction and
the incomplete induction according to Aristotle's induction method, but
they disagreed with this method in accordance with the nature of Islamic
method of thinking; therefore they had their own distinguishing method
of induction.
Understanding robustness and sensitivity of BERT models predicting Alzheimer's disease from text is important for both developing better classification models and for understanding their capabilities and limitations. In this paper, we analyze how a c
ontrolled amount of desired and undesired text alterations impacts performance of BERT. We show that BERT is robust to natural linguistic variations in text. On the other hand, we show that BERT is not sensitive to removing clinically important information from text.
The syntax is the spirit of language , the core of its movement, it is living heart.
And it is way of interpretation which is a pure mental manner . Taken by Arab Grammarians, so they gave it great effort in order to interpret the syntactic and morp
hological bases .
The following research considers the most important views of the old and modern syntax-specialists as starting point of studying the syntax – interpretations at two levels : the first Level contains concept and approach, It monitors the concept of reasoning in as, and the implications at rules of this term, the statement its motive which is based language in use . and the second level is referential . It demands its elements and the views of Arab syntax in it , and it clears its rules which was established tell the six migration century .
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