Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
languages:
- ha
licenses:
- cc-by-4-0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- structure-prediction
task_ids:
- named-entity-recognition
Dataset Card for Hausa VOA NER Corpus
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://www.aclweb.org/anthology/2020.emnlp-main.204/
- Repository: Hausa VOA NER
- Paper: https://www.aclweb.org/anthology/2020.emnlp-main.204/
- Leaderboard:
- Point of Contact: David Adelani
Dataset Summary
The Hausa VOA NER is a named entity recognition (NER) dataset for Hausa language based on the VOA Hausa news corpus.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The language supported is Hausa.
Dataset Structure
Data Instances
A data point consists of sentences seperated by empty line and tab-seperated tokens and tags. {'id': '0', 'ner_tags': [B-PER, 0, 0, B-LOC, 0], 'tokens': ['Trump', 'ya', 'ce', 'Rasha', 'ma'] }
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:
"O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-DATE", "I-DATE",
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 dates & times (DATE). (O) is used for tokens not considered part of any named entity.
Data Splits
Training (1,014 sentences), validation (145 sentences) and test split (291 sentences)
Dataset Creation
Curation Rationale
The data was created to help introduce resources to new language - Hausa.
[More Information Needed]
Source Data
Initial Data Collection and Normalization
The dataset is based on the news domain and was crawled from VOA Hausa news.
[More Information Needed]
Who are the source language producers?
The dataset was collected from VOA Hausa news. Most of the texts used in creating the Hausa VOA NER are news stories from Nigeria, Niger Republic, United States, and other parts of the world.
[More Information Needed]
Annotations
Named entity recognition annotation
Annotation process
[More Information Needed]
Who are the annotators?
The data was annotated by Jesujoba Alabi and David Adelani for the paper: Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on African Languages.
[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 students of Saarland University, Saarbrücken, Germany .
Licensing Information
The data is under the Creative Commons Attribution 4.0
Citation Information
@inproceedings{hedderich-etal-2020-transfer,
title = "Transfer Learning and Distant Supervision for Multilingual Transformer Models: A Study on {A}frican Languages",
author = "Hedderich, Michael A. and
Adelani, David and
Zhu, Dawei and
Alabi, Jesujoba and
Markus, Udia and
Klakow, Dietrich",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.emnlp-main.204",
doi = "10.18653/v1/2020.emnlp-main.204",
pages = "2580--2591",
}