The invention relates to computer systems and is intended for interpreting sentences in natural language. A neural network consists of layers of neurons. A first neuron layer is intended for interpreting the meanings of individual words in a sentence. Intermediate neuron layers are intended for interpreting word groups in a sentence, wherein the number of words in a word group corresponds to the number of the neuron layer. The last neuron layer is represented by an output neuron and is intended for interpreting a sentence on the basis of the word meanings interpreted in the preceding neuron layers. Each neuron of the input and intermediate layers comprises a memory cell intended for storing the meanings of a word or word group. Moreover, in order to improve the quality of interpretation, each such meaning is assigned a binary attribute, the coding of which is described according to the rule that '1' is the primary meaning of a word or word group and '0' is a secondary meaning of the word or word group.
NEURAL NETWORK FOR INTERPRETING SENTENCES IN NATURAL LANGUAGE