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

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

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Task Dataset Model Metric Name Metric Value Global Rank Result Benchmark
Question Similarity Q2Q Arabic Benchmark Tha3aroon F1 score 0.94848 # 2