Towards an Automatic Text Comprehension for the Arabic Question-Answering: Semantic and Logical Representation of Texts

Automatic text comprehension is an arduous task of automatic natural language processing. This task has been addressed in several NLP applications, namely, question-answering, information retrieval, etc. In some cases, these applications require a minimal understanding of the text. The use of this task in questionanswering requires that the result must be the accurate answer to a question, instead of a number of references to documents that contain the answer. It makes it possible to construct a coherent representation of the content of a text to answer a question in natural language. In this paper, we propose to construct a semantic and logical representation of Arabic texts (the question and the passages of texts). Therefore, we propose a new approach for the Arabic question-answering. This approach is based on the automatic understanding of Arabic texts (question or passages of texts) to transform them into semantic and logical representations. The experiments results of our approach achieved an accuracy of 74%.

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