Abstract
In this article is presented an approach for parsing natural language sentences using neural networks. The pre-processing technique is applied to code the sentences into string of bits and after the training process is started, is formed into patterns available in the form of coded information. The multilayer feed forward networks are used here for training to classify the words into appropriate syntactical categories. The classified words represent the parsed information of the given sentences. The main function of the network is to assign the respective syntactical categories to each word of a sentence with a minimal error rate. The comparison between the two popular neural network approaches i.e. feed forward neural network and radial basis neural network is presented to analyze performance for the new and unknown sentences.
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