Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
Afrikaans
Size:
1K - 10K
License:
File size: 4,837 Bytes
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# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
""" Named entity annotated data from the NCHLT Text Resource Development: Phase II Project for Afrikaans"""
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
@inproceedings{afrikaans_ner_corpus,
author = { Gerhard van Huyssteen and
Martin Puttkammer and
E.B. Trollip and
J.C. Liversage and
Roald Eiselen},
title = {NCHLT Afrikaans 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/20.500.12185/299},
}
"""
_DESCRIPTION = """\
Named entity annotated data from the NCHLT Text Resource Development: Phase II Project, annotated with PERSON, LOCATION, ORGANISATION and MISCELLANEOUS tags.
"""
_URL = "https://repo.sadilar.org/bitstream/handle/20.500.12185/299/nchlt_afrikaans_named_entity_annotated_corpus.zip?sequence=3&isAllowed=y"
_EXTRACTED_FILE = "NCHLT Afrikaans Named Entity Annotated Corpus/Dataset.NCHLT-II.AF.NER.Full.txt"
class AfrikaansNerCorpusConfig(datasets.BuilderConfig):
"""BuilderConfig for AfrikaansNerCorpus"""
def __init__(self, **kwargs):
"""BuilderConfig for AfrikaansNerCorpus.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(AfrikaansNerCorpusConfig, self).__init__(**kwargs)
class AfrikaansNerCorpus(datasets.GeneratorBasedBuilder):
"""Afrikaans Ner dataset"""
BUILDER_CONFIGS = [
AfrikaansNerCorpusConfig(
name="afrikaans_ner_corpus",
version=datasets.Version("1.0.0"),
description="AfrikaansNerCorpus 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=[
"OUT",
"B-PERS",
"I-PERS",
"B-ORG",
"I-ORG",
"B-LOC",
"I-LOC",
"B-MISC",
"I-MISC",
]
)
),
}
),
supervised_keys=None,
homepage="https://repo.sadilar.org/handle/20.500.12185/299",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": os.path.join(data_dir, _EXTRACTED_FILE)},
),
]
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:
splits = line.split("\t")
tokens.append(splits[0])
ner_tags.append(splits[1].rstrip())
yield guid, {
"id": str(guid),
"tokens": tokens,
"ner_tags": ner_tags,
}
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