README.md

metadata

license: cc-by-sa-4.0
task_categories:
  - question-answering
language:
  - bem
  - fon
  - ha
  - ig
  - kin
  - sw
  - wo
  - yo
  - zu
  - tw
pretty_name: AfriQA
size_categories:
  - 10K<n<100K
multilinguality:
  - multilingual
tags:
  - cross-lingual
  - question-answering
  - qa

Dataset Card for [Dataset Name]

Table of Contents

• Table of Contents
• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
  • Annotations
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Dataset Curators
  • Licensing Information
  • Citation Information
  • Contributions

Dataset Description

• Homepage: homepage
• Repository: github
• Paper: paper
• Point of Contact: Masakhane or [email protected]

Dataset Summary

AfriQA is the first cross-lingual question answering (QA) dataset with a focus on African languages. The dataset includes over 12,000 XOR QA examples across 10 African languages, making it an invaluable resource for developing more equitable QA technology.

The train/validation/test sets are available for all the 10 languages.

For more details see ...

Supported Tasks and Leaderboards

[More Information Needed]

• question-answering: The performance in this task is measured with F1 (higher is better) and Exact Match Accuracy.

Languages

There are 20 languages available :

• Bemba (bem)
• Fon (fon)
• Hausa (hau)
• Igbo (ibo)
• Kinyarwanda (kin)
• Swahili (swą)
• Twi (twi)
• Wolof (wol)
• Yorùbá (yor)
• Zulu (zul)

Dataset Structure

Data Instances

• Data Format:
• id : Question ID
• question : Question in African Language
• translated_question : Question translated into a pivot language (English/French)
• answers : Answer in African Language
• lang : Datapoint Language (African Language) e.g bem
• split : Dataset Split
• translated_answer : Answer in Pivot Language
• translation_type : Translation type of question and answers

{   "id": 0, 
    "question": "Bushe icaalo ca Egypt caali tekwapo ne caalo cimbi?", 
    "translated_question": "Has the country of Egypt been colonized before?", 
    "answers": "['Emukwai']", 
    "lang": "bem", 
    "split": "dev", 
    "translated_answer": "['yes']", 
    "translation_type": "human_translation"
    }

Data Splits

For all languages, there are three splits.

The original splits were named train, dev and test and they correspond to the train, validation and test splits.

The splits have the following sizes :

Language	train	dev	test
Bemba	502	503	314
Fon	427	428	386
Hausa	435	436	300
Igbo	417	418	409
Kinyarwanda	407	409	347
Swahili	415	417	302
Twi	451	452	490
Wolof	503	504	334
Yoruba	360	361	332
Zulu	387	388	325
Total	4333	4346	3560

Dataset Creation

Curation Rationale

The dataset was introduced to introduce question-answering resources to 10 languages that were under-served for natural language processing.

[More Information Needed]

Source Data

...

Initial Data Collection and Normalization

...

Who are the source language producers?

...

Annotations

Annotation process

Details can be found here ...

Who are the annotators?

Annotators were recruited from Masakhane

Personal and Sensitive Information

...

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

Users should keep in mind that the dataset only contains news text, which might limit the applicability of the developed systems to other domains.

Additional Information

Dataset Curators

Licensing Information

The licensing status of the data is CC 4.0 Non-Commercial

Citation Information

Provide the BibTex-formatted reference for the dataset. For example:

Incoming ...

Contributions

Thanks to @ToluClassics for adding this dataset.