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import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
"""
_DESCRIPTION = """\
"""
_URL = "https://huggingface.co/datasets/mrojas/abbreviation/resolve/main/data/"
_TRAINING_FILE = "Abbreviation_train.conll"
_DEV_FILE = "Abbreviation_dev.conll"
_TEST_FILE = "Abbreviation_test.conll"
class AbbreviationConfig(datasets.BuilderConfig):
"""BuilderConfig for abbreviation"""
def __init__(self, **kwargs):
"""BuilderConfig for abbreviation
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(AbbreviationConfig, self).__init__(**kwargs)
class Abbreviation(datasets.GeneratorBasedBuilder):
"""Abbreviation dataset."""
BUILDER_CONFIGS = [
AbbreviationConfig(name="abbreviation", version=datasets.Version("1.0.0"), description="Abbreviation dataset"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"tokens": datasets.Sequence(datasets.Value("string")),
"ner_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"O",
"B-Abbreviation",
"I-Abbreviation",
]
)
),
}
),
supervised_keys=None,
homepage="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
urls_to_download = {
"train": f"{_URL}{_TRAINING_FILE}",
"dev": f"{_URL}{_DEV_FILE}",
"test": f"{_URL}{_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:
id_ = 0
tokens = []
ner_tags = []
for line in f:
if line == "" or line == "\n":
if tokens:
yield id_, {
"tokens": tokens,
"ner_tags": ner_tags,
}
id_ += 1
tokens = []
ner_tags = []
else:
# conll2003 tokens are space separated
splits = line.split(" ")
tokens.append(splits[0])
ner_tags.append(splits[1].rstrip())
# last example
yield id_, {
"tokens": tokens,
"ner_tags": ner_tags,
} |