A Model for Generating Arabic Text from Semantic Representation

Text Generation is a challenging task in Natural Language Processing (NLP). Its purpose is to generate grammatically correct text from machine representation source such as a knowledge base. One of the most recent semantic representation is Rich Semantic Graph (RSG). It exploits not only the semantic representation techniques but also the Language structure and writing styles. Our work is a part of an ongoing research to create an abstractive summary for a single input document in the Arabic Language. The abstractive summary is generated through three modules; converting the input Arabic text into an RSG, then performing Graph Reduction, and finally generating the summarized text from the reduced graph. This is achieved with the aid of a domain Ontology. In this paper, we are illustrating the architecture of the third module, which works on generating Arabic text from RSG using Ontology.