Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Zulu
Size:
10K<n<100K
License:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - expert-generated | |
| language: | |
| - zu | |
| license: | |
| - other | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - 10K<n<100K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| pretty_name: Isizulu Ner Corpus | |
| license_details: Creative Commons Attribution 2.5 South Africa | |
| dataset_info: | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| '0': OUT | |
| '1': B-PERS | |
| '2': I-PERS | |
| '3': B-ORG | |
| '4': I-ORG | |
| '5': B-LOC | |
| '6': I-LOC | |
| '7': B-MISC | |
| '8': I-MISC | |
| config_name: isizulu_ner_corpus | |
| splits: | |
| - name: train | |
| num_bytes: 4038876 | |
| num_examples: 10956 | |
| download_size: 25097584 | |
| dataset_size: 4038876 | |
| # Dataset Card for Isizulu Ner Corpus | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-fields) | |
| - [Data Splits](#data-splits) | |
| - [Dataset Creation](#dataset-creation) | |
| - [Curation Rationale](#curation-rationale) | |
| - [Source Data](#source-data) | |
| - [Annotations](#annotations) | |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) | |
| - [Considerations for Using the Data](#considerations-for-using-the-data) | |
| - [Social Impact of Dataset](#social-impact-of-dataset) | |
| - [Discussion of Biases](#discussion-of-biases) | |
| - [Other Known Limitations](#other-known-limitations) | |
| - [Additional Information](#additional-information) | |
| - [Dataset Curators](#dataset-curators) | |
| - [Licensing Information](#licensing-information) | |
| - [Citation Information](#citation-information) | |
| - [Contributions](#contributions) | |
| ## Dataset Description | |
| - **Homepage:** [Isizulu Ner Corpus Homepage](https://repo.sadilar.org/handle/20.500.12185/319) | |
| - **Repository:** | |
| - **Paper:** | |
| - **Leaderboard:** | |
| - **Point of Contact:** [Martin Puttkammer](mailto:[email protected]) | |
| ### Dataset Summary | |
| The isizulu Ner Corpus is a Zulu dataset developed by [The Centre for Text Technology (CTexT), North-West University, South Africa](http://humanities.nwu.ac.za/ctext). The data is based on documents from the South African goverment domain and crawled from gov.za websites. It was created to support NER task for Zulu language. The dataset uses CoNLL shared task annotation standards. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| The language supported is Zulu. | |
| ## Dataset Structure | |
| ### Data Instances | |
| A data point consists of sentences seperated by empty line and tab-seperated tokens and tags. | |
| {'id': '0', | |
| 'ner_tags': [7, 8, 0, 0, 0], | |
| 'tokens': ['Lesi', 'sigaba', 'se-website', ',', 'esikhonjiswe'] | |
| } | |
| ### Data Fields | |
| - `id`: id of the sample | |
| - `tokens`: the tokens of the example text | |
| - `ner_tags`: the NER tags of each token | |
| The NER tags correspond to this list: | |
| ``` | |
| "OUT", "B-PERS", "I-PERS", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-MISC", "I-MISC", | |
| ``` | |
| The NER tags have the same format as in the CoNLL shared task: a B denotes the first item of a phrase and an I any non-initial word. There are four types of phrases: person names (PER), organizations (ORG), locations (LOC) and miscellaneous names (MISC). (OUT) is used for tokens not considered part of any named entity. | |
| ### Data Splits | |
| The data was not split. | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| The data was created to help introduce resources to new language - zulu. | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| The data is based on South African government domain and was crawled from gov.za websites. | |
| #### Who are the source language producers? | |
| The data was produced by writers of South African government websites - gov.za | |
| ### Annotations | |
| #### Annotation process | |
| [More Information Needed] | |
| #### Who are the annotators? | |
| The data was annotated during the NCHLT text resource development project. | |
| [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 | |
| The annotated data sets were developed by the Centre for Text Technology (CTexT, North-West University, South Africa). | |
| See: [more information](http://www.nwu.ac.za/ctext) | |
| ### Licensing Information | |
| The data is under the [Creative Commons Attribution 2.5 South Africa License](http://creativecommons.org/licenses/by/2.5/za/legalcode) | |
| ### Citation Information | |
| ``` | |
| @inproceedings{isizulu_ner_corpus, | |
| author = {A.N. Manzini and | |
| Roald Eiselen}, | |
| title = {NCHLT isiZulu Named Entity Annotated Corpus}, | |
| booktitle = {Eiselen, R. 2016. Government domain named entity recognition for South African languages. Proceedings of the 10th Language Resource and Evaluation Conference, Portorož, Slovenia.}, | |
| year = {2016}, | |
| url = {https://repo.sadilar.org/handle/20.500.12185/319}, | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@yvonnegitau](https://github.com/yvonnegitau) for adding this dataset. |