Knowledge representation of Urdu text using predicate logic

Knowledge representation is a key area of research in artificial intelligence which deals with the proper storage and retrieval of knowledge for various useful applications. This research paper proves that knowledge can be easily and efficiently represented in predicate logic. The algorithm in this paper splits the Urdu text/sentences into phrases/constituents and then represents these in predicate logic. This algorithm also generates the original sentences from the representation in order to check the accuracy of representation. The algorithm has been tested on real text/sentences of Urdu. The algorithm has achieved an accuracy of 88%. As the algorithms works on pre-tagged input file, so if the tagging is done correctly then the algorithm achieves high level of accuracy. Therefore it is required that there should be proper rules by the help of which one can correctly tag the input text into phrases/ constituents. The algorithm accurately represents such text in predicate logic. The algorithm also accurately retrieves the original text/sentences from such representation.