README.md

---
configs:
- config_name: default
  data_files:
  - split: Dialect2SQL
    path: Dialect2SQL.csv
  - split: train
    path: train.csv
  - split: validation
    path: validation.csv
  - split: test
    path: test.csv
task_categories:
- text-generation
- translation
language:
- en
- ar
tags:
- text-to-sql
- question-to-sql
- nlq-to-sql
- SQL
- english-to-sql
- low-resource-languages
- darija
- Arabic-dialect
size_categories:
- 1K<n<10K
---

# Dialect2SQL

## Dataset Description

**Dialect2SQL** is a novel dataset designed for the **Text-to-SQL** task in **Arabic dialects**, with a particular focus on **Moroccan Darija**.  
It provides natural language questions written in Darija, paired with corresponding SQL queries and database schemas.  
The dataset enables research on **low-resource natural language interfaces to databases (NLIDB)** in non-standard Arabic varieties.

---

## Dataset Summary

Dialect2SQL aims to bridge the gap between Arabic dialects and structured query understanding.  
The dataset consists of manually and semi-automatically curated **Darija–SQL** pairs mapped to realistic database schemas spanning multiple domains (e.g., education, e-commerce, banking, and transportation).  
Each entry contains:
- a **Darija** question (`darija_question`)
- an optional **English translation** (`en_question`)
- the **SQL query** (`sql`)
- the **database schema** (`db_schema`)
- the **database name** (`db_id`)

---

## Supported Tasks and Leaderboards

### Task: Text-to-SQL / NLQ-to-SQL

Given a natural language question written in **Darija (Moroccan Arabic)**, the goal is to generate the correct **SQL query** that retrieves the requested information.

**Example Task:**

| Field | Example |
|-------|----------|
| `darija_question` | شحال من تلميذ عندو أكثر من 15 ف الرياضيات؟ |
| `en_question` | How many students scored more than 15 in mathematics? |
| `sql` | SELECT COUNT(*) FROM Grades WHERE subject = 'Mathematics' AND grade > 15; |
| `db_schema` | CREATE TABLE Grades(student_id number, subject varchar, grade real); |
| `db_id` | School_DB |

---

## Languages

- **Darija (Moroccan Arabic)** — primary source language  
- **English** — provided for reference and cross-lingual studies  

---

## Data Splits

| Split | Size (approx.) | Description |
|-------|----------------|-------------|
| `train` | ~7,000 | Main training set |
| `validation` | ~1,000 | Development split |
| `test` | ~1,000 | Evaluation split |
| `Dialect2SQL` | full dataset | Combined dataset file |

---

## Dataset Structure

Each row in the dataset includes:

| Column | Description |
|---------|--------------|
| `db_id` | Database identifier |
| `db_schema` | SQL table definitions |
| `darija_question` | Question in Moroccan Darija |
| `en_question` | English translation (optional) |
| `sql` | Target SQL query |

---

## Use Cases

- Fine-tuning **text-to-SQL models** for Arabic dialects  
- Research on **multilingual and dialectal NLIDB systems**  
- **Cross-lingual transfer learning** for SQL understanding  
- Evaluating **low-resource adaptation** of code LLMs (e.g., Qwen, StarCoder, Codex)

---

## Limitations

- The dataset currently focuses on **Moroccan Darija**, and performance may not generalize to other Arabic dialects.
- Some questions are written using **Arabic script**, while others mix **Latin characters** (Arabizi), reflecting real user input diversity.
- SQL coverage is limited to **single-domain, schema-bounded** tasks.

---

## Citation

If you use this dataset, please cite the following paper:

```bibtex
@inproceedings{chafik2025dialect2sql,
  title={Dialect2SQL: A Novel Text-to-SQL Dataset for Arabic Dialects with a Focus on Moroccan Darija},
  author={Chafik, Salmane and Ezzini, Saad and Berrada, Ismail},
  booktitle={Proceedings of the 4th Workshop on Arabic Corpus Linguistics (WACL-4)},
  pages={86--92},
  year={2025}
}