  With the expanding growth of Arabic electronic data on the web, extracting
information, which is actually one of the major challenges of the
question-answering, is essentially used for building corpus of documents. In
fact, building a corpus is a research topic that is currently referred to among
some other major themes of conferences, in Natural Language Processing (NLP),
such as, Information Retrieval (IR), Question-Answering (QA), Automatic Summary
(AS), etc. Generally, a question-answering system provides various passages to
answer the user questions. To make these passages truly informative, this
system needs access to an underlying knowledge base; this requires the
construction of a corpus. The aim of our research is to build an Arabic
question-answering system. In addition, analyzing the question must be the
first step. Next, it is essential to retrieve a passage from the web that can
serve as an appropriate answer. In this paper, we propose a method to analysis
the question and retrieve the passage answer in the Arabic language. For the
question analysis, five factual question types are processed. Additionally, our
purpose is to experiment with the generation of a logic representation from the
declarative form of each question. Several studies, deal with the logic
approaches in question-answering, are discussed in other languages than the
Arabic language. This representation is very promising because it helps us
later in the selection of a justifiable answer. The accuracy of questions that
are correctly analyzed and translated into the logic form achieved 64%. And
then, the results of passages of texts that are automatically generated
achieved an 87% score for accuracy and a 98% score for c@1.
