|
--- |
|
annotations_creators: |
|
- expert-generated |
|
language_creators: |
|
- expert-generated |
|
language: |
|
- am |
|
- ha |
|
- ig |
|
- lg |
|
- luo |
|
- pcm |
|
- rw |
|
- sw |
|
- wo |
|
- yo |
|
license: |
|
- unknown |
|
multilinguality: |
|
- multilingual |
|
size_categories: |
|
- 10K<n<100K |
|
source_datasets: |
|
- original |
|
task_categories: |
|
- token-classification |
|
task_ids: |
|
- named-entity-recognition |
|
pretty_name: MasakhaNER |
|
dataset_info: |
|
- config_name: amh |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
- name: train |
|
num_bytes: 639911 |
|
num_examples: 1750 |
|
- name: validation |
|
num_bytes: 92753 |
|
num_examples: 250 |
|
- name: test |
|
num_bytes: 184271 |
|
num_examples: 500 |
|
download_size: 571951 |
|
dataset_size: 916935 |
|
- config_name: hau |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
num_bytes: 929848 |
|
num_examples: 1912 |
|
- name: validation |
|
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|
num_examples: 276 |
|
- name: test |
|
num_bytes: 282971 |
|
num_examples: 552 |
|
download_size: 633372 |
|
dataset_size: 1352322 |
|
- config_name: ibo |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
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|
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|
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|
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|
num_examples: 320 |
|
- name: test |
|
num_bytes: 222192 |
|
num_examples: 638 |
|
download_size: 515415 |
|
dataset_size: 1081960 |
|
- config_name: kin |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
num_bytes: 878746 |
|
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|
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|
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|
num_examples: 302 |
|
- name: test |
|
num_bytes: 258638 |
|
num_examples: 605 |
|
download_size: 633024 |
|
dataset_size: 1258382 |
|
- config_name: lug |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
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|
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|
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|
num_examples: 200 |
|
- name: test |
|
num_bytes: 183063 |
|
num_examples: 407 |
|
download_size: 445755 |
|
dataset_size: 865038 |
|
- config_name: luo |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
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|
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|
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|
- name: test |
|
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|
num_examples: 186 |
|
download_size: 213281 |
|
dataset_size: 446217 |
|
- config_name: pcm |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
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|
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|
num_examples: 306 |
|
- name: test |
|
num_bytes: 262185 |
|
num_examples: 600 |
|
download_size: 572054 |
|
dataset_size: 1257243 |
|
- config_name: swa |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
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|
num_bytes: 1001120 |
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num_examples: 2109 |
|
- name: validation |
|
num_bytes: 128563 |
|
num_examples: 300 |
|
- name: test |
|
num_bytes: 272108 |
|
num_examples: 604 |
|
download_size: 686313 |
|
dataset_size: 1401791 |
|
- config_name: wol |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
splits: |
|
- name: train |
|
num_bytes: 602076 |
|
num_examples: 1871 |
|
- name: validation |
|
num_bytes: 71535 |
|
num_examples: 267 |
|
- name: test |
|
num_bytes: 191484 |
|
num_examples: 539 |
|
download_size: 364463 |
|
dataset_size: 865095 |
|
- config_name: yor |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: tokens |
|
sequence: string |
|
- name: ner_tags |
|
sequence: |
|
class_label: |
|
names: |
|
'0': O |
|
'1': B-PER |
|
'2': I-PER |
|
'3': B-ORG |
|
'4': I-ORG |
|
'5': B-LOC |
|
'6': I-LOC |
|
'7': B-DATE |
|
'8': I-DATE |
|
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|
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|
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|
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|
num_bytes: 127415 |
|
num_examples: 305 |
|
- name: test |
|
num_bytes: 359519 |
|
num_examples: 645 |
|
download_size: 751510 |
|
dataset_size: 1503675 |
|
config_names: |
|
- am |
|
- ha |
|
- ig |
|
- lg |
|
- luo |
|
- pcm |
|
- rw |
|
- sw |
|
- wo |
|
- yo |
|
--- |
|
|
|
# Dataset Card for MasakhaNER |
|
|
|
## 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:** [homepage](https://github.com/masakhane-io/masakhane-ner) |
|
- **Repository:** [github](https://github.com/masakhane-io/masakhane-ner) |
|
- **Paper:** [paper](https://arxiv.org/abs/2103.11811) |
|
- **Point of Contact:** [Masakhane](https://www.masakhane.io/) or [email protected] |
|
|
|
### Dataset Summary |
|
|
|
MasakhaNER is the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages. |
|
|
|
Named entities are phrases that contain the names of persons, organizations, locations, times and quantities. Example: |
|
|
|
[PER Wolff] , currently a journalist in [LOC Argentina] , played with [PER Del Bosque] in the final years of the seventies in [ORG Real Madrid] . |
|
|
|
MasakhaNER is a named entity dataset consisting of PER, ORG, LOC, and DATE entities annotated by Masakhane for ten African languages: |
|
- Amharic |
|
- Hausa |
|
- Igbo |
|
- Kinyarwanda |
|
- Luganda |
|
- Luo |
|
- Nigerian-Pidgin |
|
- Swahili |
|
- Wolof |
|
- Yoruba |
|
|
|
The train/validation/test sets are available for all the ten languages. |
|
|
|
For more details see https://arxiv.org/abs/2103.11811 |
|
|
|
|
|
### Supported Tasks and Leaderboards |
|
|
|
[More Information Needed] |
|
|
|
- `named-entity-recognition`: The performance in this task is measured with [F1](https://huggingface.co/metrics/f1) (higher is better). A named entity is correct only if it is an exact match of the corresponding entity in the data. |
|
|
|
### Languages |
|
|
|
There are ten languages available : |
|
- Amharic (amh) |
|
- Hausa (hau) |
|
- Igbo (ibo) |
|
- Kinyarwanda (kin) |
|
- Luganda (kin) |
|
- Luo (luo) |
|
- Nigerian-Pidgin (pcm) |
|
- Swahili (swa) |
|
- Wolof (wol) |
|
- Yoruba (yor) |
|
|
|
## Dataset Structure |
|
|
|
### Data Instances |
|
|
|
The examples look like this for Yorùbá: |
|
|
|
``` |
|
from datasets import load_dataset |
|
data = load_dataset('masakhaner', 'yor') |
|
|
|
# Please, specify the language code |
|
|
|
# A data point consists of sentences seperated by empty line and tab-seperated tokens and tags. |
|
{'id': '0', |
|
'ner_tags': [B-DATE, I-DATE, 0, 0, 0, 0, 0, B-PER, I-PER, I-PER, O, O, O, O], |
|
'tokens': ['Wákàtí', 'méje', 'ti', 'ré', 'kọjá', 'lọ', 'tí', 'Luis', 'Carlos', 'Díaz', 'ti', 'di', 'awati', '.'] |
|
} |
|
``` |
|
|
|
### 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: |
|
``` |
|
"O", "B-PER", "I-PER", "B-ORG", "I-ORG", "B-LOC", "I-LOC", "B-DATE", "I-DATE", |
|
``` |
|
|
|
In the NER tags, 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 & time (DATE). |
|
|
|
It is assumed that named entities are non-recursive and non-overlapping. In case a named entity is embedded in another named entity usually, only the top level entity is marked. |
|
|
|
### Data Splits |
|
|
|
For all languages, there are three splits. |
|
|
|
The original splits were named `train`, `dev` and `test` and they correspond to the `train`, `validation` and `test` splits. |
|
|
|
The splits have the following sizes : |
|
|
|
| Language | train | validation | test | |
|
|-----------------|------:|-----------:|-----:| |
|
| Amharic | 1750 | 250 | 500 | |
|
| Hausa | 1903 | 272 | 545 | |
|
| Igbo | 2233 | 319 | 638 | |
|
| Kinyarwanda | 2110 | 301 | 604 | |
|
| Luganda | 2003 | 200 | 401 | |
|
| Luo | 644 | 92 | 185 | |
|
| Nigerian-Pidgin | 2100 | 300 | 600 | |
|
| Swahili | 2104 | 300 | 602 | |
|
| Wolof | 1871 | 267 | 536 | |
|
| Yoruba | 2124 | 303 | 608 | |
|
|
|
## Dataset Creation |
|
|
|
### Curation Rationale |
|
|
|
The dataset was introduced to introduce new resources to ten languages that were under-served for natural language processing. |
|
|
|
[More Information Needed] |
|
|
|
### Source Data |
|
|
|
The source of the data is from the news domain, details can be found here https://arxiv.org/abs/2103.11811 |
|
|
|
#### Initial Data Collection and Normalization |
|
|
|
The articles were word-tokenized, information on the exact pre-processing pipeline is unavailable. |
|
|
|
#### Who are the source language producers? |
|
|
|
The source language was produced by journalists and writers employed by the news agency and newspaper mentioned above. |
|
|
|
### Annotations |
|
|
|
#### Annotation process |
|
|
|
Details can be found here https://arxiv.org/abs/2103.11811 |
|
|
|
#### Who are the annotators? |
|
|
|
Annotators were recruited from [Masakhane](https://www.masakhane.io/) |
|
|
|
### Personal and Sensitive Information |
|
|
|
The data is sourced from newspaper source and only contains mentions of public figures or individuals |
|
|
|
## Considerations for Using the Data |
|
|
|
### Social Impact of Dataset |
|
[More Information Needed] |
|
|
|
|
|
### Discussion of Biases |
|
[More Information Needed] |
|
|
|
|
|
### Other Known Limitations |
|
|
|
Users should keep in mind that the dataset only contains news text, which might limit the applicability of the developed systems to other domains. |
|
|
|
## Additional Information |
|
|
|
### Dataset Curators |
|
|
|
|
|
### Licensing Information |
|
|
|
The licensing status of the data is CC 4.0 Non-Commercial |
|
|
|
### Citation Information |
|
|
|
Provide the [BibTex](http://www.bibtex.org/)-formatted reference for the dataset. For example: |
|
``` |
|
@article{Adelani2021MasakhaNERNE, |
|
title={MasakhaNER: Named Entity Recognition for African Languages}, |
|
author={D. Adelani and Jade Abbott and Graham Neubig and Daniel D'Souza and Julia Kreutzer and Constantine Lignos |
|
and Chester Palen-Michel and Happy Buzaaba and Shruti Rijhwani and Sebastian Ruder and Stephen Mayhew and |
|
Israel Abebe Azime and S. Muhammad and Chris C. Emezue and Joyce Nakatumba-Nabende and Perez Ogayo and |
|
Anuoluwapo Aremu and Catherine Gitau and Derguene Mbaye and J. Alabi and Seid Muhie Yimam and Tajuddeen R. Gwadabe and |
|
Ignatius Ezeani and Rubungo Andre Niyongabo and Jonathan Mukiibi and V. Otiende and Iroro Orife and Davis David and |
|
Samba Ngom and Tosin P. Adewumi and Paul Rayson and Mofetoluwa Adeyemi and Gerald Muriuki and Emmanuel Anebi and |
|
C. Chukwuneke and N. Odu and Eric Peter Wairagala and S. Oyerinde and Clemencia Siro and Tobius Saul Bateesa and |
|
Temilola Oloyede and Yvonne Wambui and Victor Akinode and Deborah Nabagereka and Maurice Katusiime and |
|
Ayodele Awokoya and Mouhamadane Mboup and D. Gebreyohannes and Henok Tilaye and Kelechi Nwaike and Degaga Wolde and |
|
Abdoulaye Faye and Blessing Sibanda and Orevaoghene Ahia and Bonaventure F. P. Dossou and Kelechi Ogueji and |
|
Thierno Ibrahima Diop and A. Diallo and Adewale Akinfaderin and T. Marengereke and Salomey Osei}, |
|
journal={ArXiv}, |
|
year={2021}, |
|
volume={abs/2103.11811} |
|
} |
|
``` |
|
|
|
### Contributions |
|
|
|
Thanks to [@dadelani](https://github.com/dadelani) for adding this dataset. |
