Knowledge representation: Predicate logic implementation using sentence-type for natural languages

Representing the content of the text is really an important issue of knowledge representation. Natural language processing (NLP) is a field of computer science, artificial intelligence, and linguistics concerned with the interactions between computers and human languages. It processes the data through lexical analysis, Syntax analysis, Semantic analysis, Discourse processing, Pragmatic analysis. This paper compares various knowledge representation schemes. The algorithm in this paper splits the English sentences into phrases and then represents these in predicate logic by considering the types of sentences (Simple, Interrogative, Exclamatory, Passive etc.). The algorithm has been tested on real sentences of English. The algorithm has achieved an accuracy of 75%. This representation would be used in future for Semantic based Text summarization.