<reponame>zidingz/datasets<filename>datasets/masakhaner/masakhaner.py
# 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={<NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME>
  and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
   <NAME> and <NAME> and <NAME> and <NAME> and <NAME>},
  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,
                }

# 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={<NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME>
  and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
  <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and
   <NAME> and <NAME> and <NAME> and <NAME> and <NAME>},
  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,
                }
# 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 \ @article{Adelani2021MasakhaNERNE,   title={MasakhaNER: Named Entity Recognition for African Languages},   author={<NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME>   and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and   <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and    <NAME> and <NAME> and <NAME> and <NAME> and <NAME> and    <NAME> and <NAME> and <NAME> and <NAME> and <NAME>},   journal={ArXiv},   year={2021},   volume={abs/2103.11811} } \ 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 BuilderConfig for Masakhaner BuilderConfig for Masakhaner.          Args:           **kwargs: keyword arguments forwarded to super. Masakhaner dataset. Returns SplitGenerators. # Masakhaner tokens are space separated # last example