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Syntactic Analysis of the Sentences of the Russian Language Based on Neural Networks

机译:基于神经网络的俄语句子句法分析

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The model of Russian language parser based on a combination of neural networks along with extraction of set of parameters which allows to establish relations with the minimal syntactic ambiguity is presented. The parse tree of sentence is constructed in the format of Russian National Corpus (RNC). RNC texts containing morphological and syntactic markup are used for training neural network models as part of procedure. Estimates of accuracy of the developed parser procedure in comparison with the other Russian language parser systems have been performed.
机译:提出了一种基于神经网络与参数集提取相结合的俄语语言解析器模型,该模型允许建立具有最小句法歧义性的关系。句子的分析树以俄罗斯国家语料库(RNC)的格式构建。包含形态和句法标记的RNC文本将作为过程的一部分用于训练神经网络模型。与其他俄语分析器系统相比,已执行了开发的分析器过程的准确性估计。

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