Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Multilinguality:
multilingual
Size Categories:
10K<n<100K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
Tags:
License:
# coding=utf-8 | |
# Copyright 2020 HuggingFace Datasets Authors. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# Lint as: python3 | |
"""MasakhaNER: Named Entity Recognition for African Languages""" | |
import datasets | |
logger = datasets.logging.get_logger(__name__) | |
_CITATION = """\ | |
@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} | |
} | |
""" | |
_DESCRIPTION = """\ | |
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 | |
""" | |
_URL = "https://github.com/masakhane-io/masakhane-ner/raw/main/data/" | |
_TRAINING_FILE = "train.txt" | |
_DEV_FILE = "dev.txt" | |
_TEST_FILE = "test.txt" | |
class MasakhanerConfig(datasets.BuilderConfig): | |
"""BuilderConfig for Masakhaner""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for Masakhaner. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(MasakhanerConfig, self).__init__(**kwargs) | |
class Masakhaner(datasets.GeneratorBasedBuilder): | |
"""Masakhaner dataset.""" | |
BUILDER_CONFIGS = [ | |
MasakhanerConfig(name="amh", version=datasets.Version("1.0.0"), description="Masakhaner Amharic dataset"), | |
MasakhanerConfig(name="hau", version=datasets.Version("1.0.0"), description="Masakhaner Hausa dataset"), | |
MasakhanerConfig(name="ibo", version=datasets.Version("1.0.0"), description="Masakhaner Igbo dataset"), | |
MasakhanerConfig(name="kin", version=datasets.Version("1.0.0"), description="Masakhaner Kinyarwanda dataset"), | |
MasakhanerConfig(name="lug", version=datasets.Version("1.0.0"), description="Masakhaner Luganda dataset"), | |
MasakhanerConfig(name="luo", version=datasets.Version("1.0.0"), description="Masakhaner Luo dataset"), | |
MasakhanerConfig( | |
name="pcm", version=datasets.Version("1.0.0"), description="Masakhaner Nigerian-Pidgin dataset" | |
), | |
MasakhanerConfig(name="swa", version=datasets.Version("1.0.0"), description="Masakhaner Swahili dataset"), | |
MasakhanerConfig(name="wol", version=datasets.Version("1.0.0"), description="Masakhaner Wolof dataset"), | |
MasakhanerConfig(name="yor", version=datasets.Version("1.0.0"), description="Masakhaner Yoruba dataset"), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"id": datasets.Value("string"), | |
"tokens": datasets.Sequence(datasets.Value("string")), | |
"ner_tags": datasets.Sequence( | |
datasets.features.ClassLabel( | |
names=[ | |
"O", | |
"B-PER", | |
"I-PER", | |
"B-ORG", | |
"I-ORG", | |
"B-LOC", | |
"I-LOC", | |
"B-DATE", | |
"I-DATE", | |
] | |
) | |
), | |
} | |
), | |
supervised_keys=None, | |
homepage="https://arxiv.org/abs/2103.11811", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
urls_to_download = { | |
"train": f"{_URL}{self.config.name}/{_TRAINING_FILE}", | |
"dev": f"{_URL}{self.config.name}/{_DEV_FILE}", | |
"test": f"{_URL}{self.config.name}/{_TEST_FILE}", | |
} | |
downloaded_files = dl_manager.download_and_extract(urls_to_download) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}), | |
datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"]}), | |
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}), | |
] | |
def _generate_examples(self, filepath): | |
logger.info("⏳ Generating examples from = %s", filepath) | |
with open(filepath, encoding="utf-8") as f: | |
guid = 0 | |
tokens = [] | |
ner_tags = [] | |
for line in f: | |
if line == "" or line == "\n": | |
if tokens: | |
yield guid, { | |
"id": str(guid), | |
"tokens": tokens, | |
"ner_tags": ner_tags, | |
} | |
guid += 1 | |
tokens = [] | |
ner_tags = [] | |
else: | |
# Masakhaner tokens are space separated | |
splits = line.split(" ") | |
tokens.append(splits[0]) | |
ner_tags.append(splits[1].rstrip()) | |
# last example | |
if tokens: | |
yield guid, { | |
"id": str(guid), | |
"tokens": tokens, | |
"ner_tags": ner_tags, | |
} | |