论文标题
NSURL-2019 NSURL-2019任务8：阿拉伯语的语义问题相似性
The Inception Team at NSURL-2019 Task 8: Semantic Question Similarity in Arabic
论文作者
论文摘要
本文介绍了我们在阿拉伯语中关于资源不足语言（NSURL）的NLP解决方案的阿拉伯语中语义问题相似性的任务。目的是建立一个能够以阿拉伯语言来检测提供的数据集的类似语义问题的模型。在这项工作中探讨了确定问题相似性的不同方法。提出的模型达到了高F1分数，范围为（88％至96％）。我们的官方最佳结果是由使用预训练的多语言BERT模型的合奏模型产生的，其随机种子具有95.924％的F1分数，该模型在9名参与者团队中排名第一。
This paper describes our method for the task of Semantic Question Similarity in Arabic in the workshop on NLP Solutions for Under-Resourced Languages (NSURL). The aim is to build a model that is able to detect similar semantic questions in the Arabic language for the provided dataset. Different methods of determining questions similarity are explored in this work. The proposed models achieved high F1-scores, which range from (88% to 96%). Our official best result is produced from the ensemble model of using a pre-trained multilingual BERT model with different random seeds with 95.924% F1-Score, which ranks the first among nine participants teams.
