Abstract
This paper presents the work carried out at ANLP Research Group for the CLEF-QA4MRE
2012 competition. This year, the Arabic language was introduced for the first time on QA4MRE lab at CLEF whose intention was to ask questions which require a deep knowledge of individual short texts and in which systems were required to choose one answer from multiple answer choices, by analyzing the corresponding test document in conjunction with background collections. In our participation, we have proposed an approach which can answer questions with multiple answer choices from short Arabic texts. This approach is constituted essentially of shallow information retrieval methods. The evaluation results of the running submitted has given the following scores: accuracy calculated overall all questions is 0.19 (i.e., 31 correct questions answered correctly among 160), while overall c@1 measure is also 0.19. The overall results obtained are not enough satisfactory comparing to the top works realized last year in QA4MRE lab. But as a first step at the roadmap of the evolution of the QA to Machine Reading (MR) systems in Arabic language and with the lack of researches investigated in the MR and deep knowledge reasoning in Arabic language, it is an encouraging step. Our proposed approach with its shallow criterion has succeeded to obtain the goal fixed at the beginning which is: select answers to questions from short texts without required enough external knowledge and complex inference.
