---
license: cc-by-4.0
language:
- ar
tags:
- medical
- arabic
- first-aid
- qa
- healthcare
- emergency
- low-resource-language
- dataset
- dialect
- Msa
pretty_name: FALAH-Mix
task_categories:
- text-classification
- question-answering
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset Name

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This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1).

## Dataset Details

### Dataset Description

**FALAH** (**F**irst-**A**id **L**ifesaving **A**rabic QA Dataset for **H**elp in Emergency Situations) is a high-quality, expert-validated Arabic dataset dedicated to first-aid question answering in Modern Standard Arabic (MSA).
The dataset consists of 104 first-aid question–answer (QA) pairs, carefully extracted and filtered from large-scale Arabic medical QA datasets, then manually annotated by medical professionals to ensure clinical relevance and correctness.

**FALAH** was created to address the scarcity of Arabic first-aid conversational resources and to support the development of specialized Arabic first-aid chatbots.
- **Curated by:** Imane MABROUK (INSEA – National Institute of Statistics and Applied Economics, Rabat, Morocco)
- **Supervised by:** Dr. Rana R. Malhas (bigIR Research Group, Qatar University) & Dr. Imane Chlioui (INSEA)
- **Domain:** First Aid / Emergency Care
- **Language(s) (NLP):** Modern Standard Arabic (MSA), Arabic Dialect (AD)
- **License:** CC BY 4.0
- **Funded by:** Self-funded academic project (Academic graduation project)

The dataset was built as part of the PFE project titled:
- *Towards Building an Arabic First-Aid Chatbot using FA-AraBERT Classifier and FALAH Dataset*
### Dataset Sources [optional]

<!-- Provide the basic links for the dataset. -->
The FALAH dataset was constructed from the following publicly available Arabic medical QA datasets:
- **AHD**(Arabic Healthcare Dataset):
H. Gawbah, A. Alsubari, and N. A. Al-Majmar, “AHD: Arabic healthcare dataset,” Sept. 2024.
- **MAQA**(Medical Arabic QA Dataset):
M. Abdelhay, A. Mohammed, and H. A. Hefny, “Deep learning for Arabic healthcare: MedicalBot,” Social Network Analysis and Mining, vol. 13, p. 71, Apr. 2023.

Additional inspiration and keyword guidance were derived from:
- **Mayo Clinic First-Aid QA Dataset**:
Jomana Anwar, Peter Nadi, and Noha Seddik, “Towards Building a Chatbot-Based First Aid Service in Arabic Language,” Journal of Advanced Research in Applied Sciences and Engineering Technology, vol. 45, pp. 1–10, May 2024.


## Uses

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### Direct Use

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**FALAH** dataset is intended for:

- Arabic first-aid question answering systems
- First-aid chatbot development
- Emergency-care NLP research in Arabic
- Few-shot prompting experiments for LLMs
- Evaluation of Arabic LLMs in emergency medical scenarios

The dataset was used in the project to:
- Provide few-shot examples for LLM prompting
- Evaluate Arabic and multilingual LLMs using BERTScore


### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
FALAH dataset should NOT be used:

- As a substitute for professional medical consultation

- For real-time clinical decision-making without human supervision

- In high-risk healthcare applications without expert validation

- For non-medical NLP tasks

- This dataset is intended strictly for research and experimental development.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
The dataset consists of **104** QA pairs.


*Characteristics:*

- Focused exclusively on first-aid and emergency scenarios

- Covers QA pairs from different categories realted to first-aid 

- Expert-validated for medical relevance

- Designed for conversational AI applications

In the broader project, FALAH dataset was integrated into FALAH-Mix dataset(FALAH dataset with non first-aid QA pairs) for classification tasks and used independently for few-shot prompting.
## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->
Despite the existence of large Arabic medical QA datasets, very few resources specifically focus on first-aid scenarios.

*For example:*

- **AHD** contained only **68** explicitly labeled first-aid QA pairs.

- **Mayo Clinic First-Aid dataset** contains **374** QA pairs.

This scarcity motivated the creation of **FALAH** — a curated Arabic first-aid dataset derived from real Arabic medical consultations.

The goal was to create a clinically relevant dataset to support emergency-aware Arabic chatbot systems, particularly useful in humanitarian and crisis contexts.


### Source Data

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#### Data Collection and Processing

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[More Information Needed]

#### Who are the source data producers?

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### Annotations [optional]

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#### Annotation process

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[More Information Needed]

#### Who are the annotators?

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#### Personal and Sensitive Information

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## Bias, Risks, and Limitations

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### Recommendations

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Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

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**BibTeX:**

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**APA:**

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## Glossary [optional]

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## More Information [optional]

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## Dataset Card Authors [optional]

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## Dataset Card Contact

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