Tibetan interrogative sentence recognition and classification based on phrase features

Abstract

The recognition of Tibetan interrogative sentences is a basic work in natural language processing, which has a wide application value in terms of Tibetan syntactic analysis, semantic analysis, intelligent question answering, search engine and other research fields. Employing interrogative pronouns as a entry point to analyze the phrase features before and after interrogative pronouns, the paper proposes a method for Tibetan interrogative sentence recognition and classification based on phrase features by designing a Tibetan interrogative sentence recognition and classification model based on phrase features. Experimental results show that the recognition accuracy, recall rate and F value of this method are 98.21%, 100.00% and 99.10% respectively, and the average classification accuracy, recall rate and F value are 96.98%, 100.00% and 98.39%, respectively.