Datasets:
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ss
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: Siswati NER Corpus
license_details: Creative Commons Attribution 2.5 South Africa License
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: siswati_ner_corpus
splits:
- name: train
num_bytes: 3517151
num_examples: 10798
download_size: 21882224
dataset_size: 3517151
Dataset Card for Siswati NER Corpus
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: Siswati Ner Corpus Homepage
- Repository:
- Paper:
- Leaderboard:
- Point of Contact: Martin Puttkammer
Dataset Summary
The Siswati Ner Corpus is a Siswati dataset developed by The Centre for Text Technology (CTexT), North-West University, South Africa. 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 Siswati language. The dataset uses CoNLL shared task annotation standards.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The language supported is Siswati.
Dataset Structure
Data Instances
A data point consists of sentences seperated by empty line and tab-seperated tokens and tags.
{'id': '0',
'ner_tags': [0, 0, 0, 0, 0],
'tokens': ['Tinsita', 'tebantfu', ':', 'tinsita', 'tetakhamiti']
}
Data Fields
id
: id of the sampletokens
: the tokens of the example textner_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 - siswati.
[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
[More Information Needed]
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
Licensing Information
The data is under the Creative Commons Attribution 2.5 South Africa License
Citation Information
@inproceedings{siswati_ner_corpus,
author = {B.B. Malangwane and
M.N. Kekana and
S.S. Sedibe and
B.C. Ndhlovu and
Roald Eiselen},
title = {NCHLT Siswati 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/20.500.12185/346},
}
Contributions
Thanks to @yvonnegitau for adding this dataset.