Semantic Comprehension Method for Chinese Sentences Based on Minimal Semantic Structures and Its Application

The importance of small Chinese sentences is no less than that of sentences, which is an inherent feature of Chinese itself. According to this characteristic, this paper proposes a sentence semantic understanding method for Chinese scientific and technological abstracts based on the minimum semantic structure. Firstly, a conceptual model was established for identifying the minimum semantic structure of a sentence based on a corpus of verbs, relative words, prepositions and markers based on Language Technology Planform (LTP) tools. Secondly, the model was used to extract the minimum semantic structure of abstract sentence. Finally, three experiments were carried out, namely, the classification of the abstract sentences, knowledge graph generation and automatic semantic inference discovery. Our study confirmed the practical value of the small Chinese sentence. The experimental results show that the effect of using small sentences to understand the semantics of Chinese text is better than that of the full stop sentence, and the minimum semantic structure can be used as the basic unit of the Chinese sentence semantic comprehension. This method is conducive in the automatic understanding of the basic semantics of sentences in unstructured Chinese science and technology text sentences.