README.md

metadata

annotations_creators:
  - expert-generated
language_creators:
  - expert-generated
languages:
  - af
  - nr
  - nso
  - ss
  - tn
  - ts
  - ve
  - xh
  - zu
licenses:
  - cc-by-2.5
multilinguality:
  - multilingual
size_categories:
  - 1K<n<10K
source_datasets:
  - original
task_categories:
  - token-classification
task_ids:
  - named-entity-recognition
paperswithcode_id: null
pretty_name: NCHLT

Dataset Card for NCHLT

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks and Leaderboards
  • Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • 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: link
• Repository:
• Paper:
• Leaderboard:
• Point of Contact:

Dataset Summary

The development of linguistic resources for use in natural language processingis of utmost importance for the continued growth of research anddevelopment in the field, especially for resource-scarce languages. In this paper we describe the process and challenges of simultaneouslydevelopingmultiple linguistic resources for ten of the official languages of South Africa. The project focussed on establishing a set of foundational resources that can foster further development of both resources and technologies for the NLP industry in South Africa. The development efforts during the project included creating monolingual unannotated corpora, of which a subset of the corpora for each language was annotated on token, orthographic, morphological and morphosyntactic layers. The annotated subsetsincludes both development and test setsand were used in the creation of five core-technologies, viz. atokeniser, sentenciser,lemmatiser, part of speech tagger and morphological decomposer for each language. We report on the quality of these tools for each language and provide some more context of the importance of the resources within the South African context.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

[More Information Needed]

Dataset Structure

[More Information Needed]

Data Instances

[More Information Needed]

Data Fields

[More Information Needed]

Data Splits

[More Information Needed]

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

[More Information Needed]

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

[More Information Needed]

Annotation process

[More Information Needed]

Who are the annotators?

[More Information Needed]

Personal and Sensitive Information

[More Information Needed]

Considerations for Using the Data

Social Impact of Dataset

[More Information Needed]

Discussion of Biases

[More Information Needed]

Other Known Limitations

[More Information Needed]

Additional Information

Dataset Curators

[email protected]

Licensing Information

[More Information Needed]

Citation Information

@inproceedings{eiselen2014developing,
  title={Developing Text Resources for Ten South African Languages.},
  author={Eiselen, Roald and Puttkammer, Martin J},
  booktitle={LREC},
  pages={3698--3703},
  year={2014}
}

Contributions

Thanks to @Narsil for adding this dataset.