Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Afrikaans
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
expert-generated
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
License:
File size: 4,837 Bytes
f8036ab 5e58e58 f8036ab 7cbd57e f8036ab 5e58e58 f8036ab |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 |
# 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,
}
|