Prediction of Chinese Semantic Word Formation Patterns Based on Annotated Corpus

This paper proposes a method for predicting the formation patterns of Chinese semantic words based on annotated corpus. A method for predicting the formation mode of Chinese semantic words based on lexical and syntactic information. The main idea of this method is that it can be used as a tool to analyze and evaluate the construction quality of Chinese semantic words. It has been widely used in linguistics, computer science, psychology and many other fields. This method is based on two main steps: firstly, unsupervised machine learning algorithm is used to identify semantic word formation patterns; Secondly, it predicts these patterns by using supervised machine learning algorithms. In order to ensure that these two methods can work together well, they are applied in parallel and combined to provide more accurate results. Experimental results show that this method can successfully recognize and predict the formation of a large number of semantic words, and has high accuracy and accuracy.