Dataset:

Task Categories: text-classification
Languages: rn rw
Multilinguality: monolingual
Size Categories: 10K<n<100K 1K<n<10K
Licenses: mit
Language Creators: found
Annotations Creators: expert-generated
Source Datasets: original

Dataset Card for kinnews_kirnews

Dataset Summary

Kinyarwanda and Kirundi news classification datasets (KINNEWS and KIRNEWS,respectively), which were both collected from Rwanda and Burundi news websites and newspapers, for low-resource monolingual and cross-lingual multiclass classification tasks.

Supported Tasks and Leaderboards

This dataset can be used for text classification of news articles in Kinyarwadi and Kirundi languages. Each news article can be classified into one of the 14 possible classes. The classes are:

  • politics
  • sport
  • economy
  • health
  • entertainment
  • history
  • technology
  • culture
  • religion
  • environment
  • education
  • relationship

Languages

Kinyarwanda and Kirundi

Dataset Structure

Data Instances

Here is an example from the dataset:

Field Value
label 1
kin_label/kir_label 'inkino'
url 'https://nawe.bi/Primus-Ligue-Imirwi-igiye-guhura-gute-ku-ndwi-ya-6-y-ihiganwa.html'
title 'Primus Ligue\xa0: Imirwi igiye guhura gute ku ndwi ya 6 y’ihiganwa\xa0?'
content ' Inkino zitegekanijwe kuruno wa gatandatu igenekerezo rya 14 Nyakanga umwaka wa 2019...'
en_label 'sport'

Data Fields

The raw version of the data for Kinyarwanda language consists of these fields

  • label: The category of the news article
  • kin_label/kir_label: The associated label in Kinyarwanda/Kirundi language
  • en_label: The associated label in English
  • url: The URL of the news article
  • title: The title of the news article
  • content: The content of the news article

The cleaned version contains only the label, title and the content fields

Data Splits

Lang| Train | Test | |---| ----- | ---- | |Kinyarwandai Raw|17014|4254| |Kinyarwandai Clean|17014|4254| |Kirundi Raw|3689|923| |Kirundi Clean|3689|923|

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

[More Information Needed]

Contributions

Thanks to @saradhix for adding this dataset.

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Models trained or fine-tuned on kinnews_kirnews

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