An Arabic Question-Answering System Combining a Semantic and Logical Representation of Texts

Abstract

In this paper, we present the overall structure of our specific system for generating answers of questions in Arabic, named NArQAS (New Arabic Question Answering System). This system aims to develop and evaluate the contribution of the use of reasoning procedures, natural language processing techniques and the recognizing textual entailment technology to develop precise answers to natural language questions. We also detail its operating architecture. In particular, our system is seen as a contribution, rather than a rival, to traditional systems focused on approaches extensively used information retrieval and natural language processing techniques. Thus, we present the evaluation of the outputs of each of these components based on a collection of questions and texts retrieved from the Web. NArQAS system was built and experiments showed good results with an accuracy of 68% for answering factual questions from the Web.