metadata

language:
  - ve
license: cc-by-nc-sa-4.0
size_categories:
  - 1K<n<10K
pretty_name: ZaBantu News Headlines[RAW]
dataset_info:
  features:
    - name: id
      dtype: int64
    - name: text
      dtype: string
    - name: language
      dtype: string
    - name: word_count
      dtype: int64
    - name: char_count
      dtype: int64
    - name: sentence_count
      dtype: int64
    - name: PotentialSplits
      sequence: string
    - name: md5
      dtype: string
  splits:
    - name: train
      num_bytes: 8799449
      num_examples: 16607
  download_size: 5317813
  dataset_size: 8799449
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*

ZaBantu News[Raw]

Dataset Description
Dataset Structure
Dataset Creation
Considerations for Using the Data

1. Dataset Description

Dataset Summary

ZaBantu News[Raw] is a collection of news headlines in Sepedi (Northern Sotho) and Tshivenda languages, sourced from various public media platforms. This dataset is designed to support NLP research and development in low-resource languages, providing raw, unlabelled headlines. It complements the "ZaBantu News" dataset, which includes a mix of machine and human labels following IPTC news codes.

Supported Tasks and Leaderboards

This dataset is suitable for tasks such as language modeling, unsupervised learning, and pre-training for downstream NLP tasks (e.g., text classification, topic modeling). It can also be used for linguistic studies and developing NLP tools for Sepedi and Tshivenda.

Languages

The dataset contains text in Sepedi (Northern Sotho) and Tshivenda, both of which are low-resource languages spoken in South Africa.

2. Dataset Structure

Data Instances

A data instance in "ZaBantu News[Raw]" consists of a single news headline. Some headlines may be segmented using delimiters like asterisks or full stops for further breakdown.

Data Fields

headline: the news headline text.
language: language of the headline (Sepedi or Tshivenda).

Data Splits

The dataset is currently not split into standard subsets (e.g., training, validation, testing). Users may consider splitting the dataset according to their needs for specific tasks.

3. Dataset Creation

Curation Rationale

The dataset was curated to address the scarcity of digital resources in Sepedi and Tshivenda for NLP research. It aims to facilitate the development of language models and other NLP tools for these languages.

Source Data

Initial Data Collection and Normalization

Headlines were collected from various public media platforms, ensuring a diverse representation of topics and styles.

Who are the source language producers?

The source language producers include journalists and content creators from multiple media outlets that publish news in Sepedi and Tshivenda.

Annotations

Annotation process

The dataset is currently not annotated. It serves as a raw collection of news headlines for potential use in unsupervised learning tasks or as a foundation for future annotated datasets.

Who are the annotators?

Not applicable.

4. Motivation

Social Impact of Dataset - The dataset contributes to NLP research in low-resource languages, potentially aiding in the development of technology that supports linguistic diversity and inclusion.

5. Licensing Information

The dataset is shared under a Share Alike license, allowing for adaptation and distribution of derivative works under the same or a compatible license.

6. Citation Information

Please cite this dataset as follows:

@misc{zabantu_news_raw,
author = {Ndamulelo Nemakhavhani},
title = {ZaBantu News[Raw]: Collecting Tshivenda and Sepedi News Headlines for Cross-Lingual Transfer Evaluation,
year = {2024},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://huggingface.co/datasets/ndamulelonemakh/zabantu-news}}
}

Datasets:

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zabantu-news