  This paper presents a dataset for closest opposite questions in Arabic
language. The dataset is the first of its kind for the Arabic language. It is
beneficial for the assessment of systems on the aspect of antonymy detection.
The structure is similar to that of the Graduate Record Examination (GRE)
closest opposite questions dataset for the English language. The introduced
dataset consists of 500 questions, each contains a query word for which the
closest opposite needs to be determined from among a set of candidate words.
Each question is also associated with the correct answer. We publish the
dataset publicly in addition to providing standard splits of the dataset into
development and test sets. Moreover, the paper provides a benchmark for the
performance of different Arabic word embedding models on the introduced
dataset.
