English

NSURL-2019 Shared Task 8: Semantic Question Similarity in Arabic

Computation and Language 2019-09-24 v1 Machine Learning Machine Learning

Abstract

Question semantic similarity (Q2Q) is a challenging task that is very useful in many NLP applications, such as detecting duplicate questions and question answering systems. In this paper, we present the results and findings of the shared task (Semantic Question Similarity in Arabic). The task was organized as part of the first workshop on NLP Solutions for Under Resourced Languages (NSURL 2019) The goal of the task is to predict whether two questions are semantically similar or not, even if they are phrased differently. A total of 9 teams participated in the task. The datasets created for this task are made publicly available to support further research on Arabic Q2Q.

Keywords

Cite

@article{arxiv.1909.09691,
  title  = {NSURL-2019 Shared Task 8: Semantic Question Similarity in Arabic},
  author = {Haitham Seelawi and Ahmad Mustafa and Hesham Al-Bataineh and Wael Farhan and Hussein T. Al-Natsheh},
  journal= {arXiv preprint arXiv:1909.09691},
  year   = {2019}
}

Comments

8 pages, 2 figure, 3 tables, conference paper

R2 v1 2026-06-23T11:21:51.364Z