数据集:

nchlt

计算机处理:

multilingual

大小:

1K<n<10K

语言创建人:

expert-generated

批注创建人:

expert-generated

源数据集:

original

许可:

cc-by-2.5
中文

Dataset Card for NCHLT

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

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Languages

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Dataset Structure

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Data Instances

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Data Fields

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Data Splits

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Dataset Creation

Curation Rationale

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Source Data

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Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

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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

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

Martin.Puttkammer@nwu.ac.za

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.