# ARCOQ: Arabic Closest Opposite Questions Dataset

arXiv: https://arxiv.org/abs/2310.14384 · HTML: https://mlsanity.com/paper/2310.14384/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 25 references that are in the map.
- First posted on arXiv 22 Oct 2023.

## Builds on (most cited first, 4 of 4)

- [AraBERT: Transformer-based Model for Arabic Language Understanding](https://mlsanity.com/paper/2003.00104/) (2020)
- [Learning Word Vectors for 157 Languages](https://mlsanity.com/paper/1802.06893/) (2018)
- [Polyglot: Distributed Word Representations for Multilingual NLP](https://mlsanity.com/paper/1307.1662/) (2013)
- [Computing Lexical Contrast](https://mlsanity.com/paper/1308.6300/) (2013)

## Abstract (arXiv)

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.