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In this paper, we describe our team's effort on the semantic text questionsimilarity task of NSURL 2019. Our top performing system utilizes severalinnovative data augmentation techniques to enlarge the training data. Then, ittakes ELMo pre-trained contextual embeddings of the data and feeds them into anON-LSTM network with self-attention. This results in sequence representationvectors that are used to predict the relation between the question pairs. Themodel is ranked in the 1st place with 96.499 F1-score (same as the second placeF1-score) and the 2nd place with 94.848 F1-score (differs by 1.076 F1-scorefrom the first place) on the public and private leaderboards, respectively.

Tha3aroon at NSURL-2019 Task 8: Semantic Question Similarity in Arabic