---
annotations_creators:
- machine-generated
language:
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license:
- other
multilinguality:
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size_categories:
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source_datasets:
- ehovy/race
task_categories:
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task_ids:
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paperswithcode_id: race
pretty_name: RACE
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---

# Dataset Card for EgyptianRACE Medium and High (Arabic and Latin Script)

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)

## Dataset Description

### Dataset Summary

RACE Medium and High in (Egyptian Arabic and Latin Script) is a reading comprehension benchmark sourced from high school English exams. It tests advanced reading, summarization, and inference skills using multiple-choice questions with 4 answer choices.

### Supported Tasks

- **Task Category:** Multiple-choice question answering
- **Task:** Selecting the correct answer from a list of options

### Languages

The dataset is available in **Egyptian Arabic and Latin Script**.

### Data Splits

All datasets include a test split. Some also contain a development split for few-shot purposes.

## Dataset Creation

### Curation Rationale

To evaluate LLMs in Egyptian Arabic and its Latin-script form using established MCQ formats across varied domains.

### Personal and Sensitive Information

No personal or sensitive information is included.

## Considerations for Using the Data

### Social Impact of Dataset

Supports the development of robust LLMs for underrepresented dialects and writing systems.

### Discussion of Biases

May inherit translation model biases; dialect variation not exhaustively covered.

### Other Known Limitations

- Limited to test splits
- Focused on selected subjects from original datasets

## Additional Information
### Dataset Curators
- MBZUAI-Paris team

### Licensing Information
- [MIT License](https://github.com/hendrycks/test/blob/master/LICENSE)

### Citation Information