Generation of a dictionary of abstract/concrete words by a multilayer neural network

Abstract

Large dictionaries of abstract/concrete words were compiled for several languages by interviewing native speakers. The Russian dictionary contains only one thousand words. This article proposes a new method for automatic generation of a large (tens of thousands of words) Russian dictionary of abstract/concrete words by using neural networks trained on the Google Books Ngram corpus. Estimates of the quality of the dictionary compiled using this method are obtained. The correlation coefficient between the estimates obtained using a neural network for the level of word concreteness and the estimates obtained based on the native speakers‵ responds is 0.778.