Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
named-entity-recognition
Languages:
Romanian
Size:
10K - 100K
ArXiv:
License:
File size: 7,038 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.
"""Introduction in RONEC: Named Entity Corpus for ROmanian language"""
from __future__ import absolute_import, division, print_function
import logging
import datasets
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@article{dumitrescu2019introducing,
title={Introducing RONEC--the Romanian Named Entity Corpus},
author={Dumitrescu, Stefan Daniel and Avram, Andrei-Marius},
journal={arXiv preprint arXiv:1909.01247},
year={2019}
}
"""
# You can copy an official description
_DESCRIPTION = """\
The RONEC (Named Entity Corpus for the Romanian language) dataset contains over 26000 entities in ~5000 annotated sentence,
belonging to 16 distinct classes. It represents the first initiative in the Romanian language space specifically targeted for named entity recognition
"""
_HOMEPAGE = "https://github.com/dumitrescustefan/ronec"
_LICENSE = "MIT License"
# The HuggingFace dataset library don't host the datasets but only point to the original files
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)
_URL = "https://raw.githubusercontent.com/dumitrescustefan/ronec/master/ronec/conllup/raw/"
_TRAINING_FILE = "train.conllu"
_TEST_FILE = "test.conllu"
_DEV_FILE = "dev.conllu"
class RONECConfig(datasets.BuilderConfig):
"""BuilderConfig for RONEC dataset"""
def __init__(self, **kwargs):
super(RONECConfig, self).__init__(**kwargs)
class RONEC(datasets.GeneratorBasedBuilder):
"""RONEC dataset"""
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
RONECConfig(name="ronec", version=VERSION, description="RONEC dataset"),
]
def _info(self):
features = datasets.Features(
{
"id": datasets.Value("string"),
"tokens": datasets.Sequence(datasets.Value("string")),
"ner_tags": datasets.Sequence(
datasets.features.ClassLabel(
names=[
"O",
"B-DATETIME",
"B-EVENT",
"B-FACILITY",
"B-GPE",
"B-LANGUAGE",
"B-LOC",
"B-MONEY",
"B-NAT_REL_POL",
"B-NUMERIC_VALUE",
"B-ORDINAL",
"B-ORGANIZATION",
"B-PERIOD",
"B-PERSON",
"B-PRODUCT",
"B-QUANTITY",
"B-WORK_OF_ART",
"I-DATETIME",
"I-EVENT",
"I-FACILITY",
"I-GPE",
"I-LANGUAGE",
"I-LOC",
"I-MONEY",
"I-NAT_REL_POL",
"I-NUMERIC_VALUE",
"I-ORDINAL",
"I-ORGANIZATION",
"I-PERIOD",
"I-PERSON",
"I-PRODUCT",
"I-QUANTITY",
"I-WORK_OF_ART",
]
)
),
}
)
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# This defines the different columns of the dataset and their types
features=features, # Here we define them above because they are different between the two configurations
# If there's a common (input, target) tuple from the features,
# specify them here. They'll be used if as_supervised=True in
# builder.as_dataset.
supervised_keys=None,
# Homepage of the dataset for documentation
homepage=_HOMEPAGE,
# License for the dataset if available
license=_LICENSE,
# Citation for the dataset
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
urls_to_download = {"train": _URL + _TRAINING_FILE, "dev": _URL + _DEV_FILE, "test": _URL + _TEST_FILE}
downloaded_files = dl_manager.download(urls_to_download)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": downloaded_files["train"]},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": downloaded_files["test"]},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": downloaded_files["dev"]},
),
]
def _generate_examples(self, filepath):
""" Yields examples. """
logging.info("⏳ Generating examples from = %s", filepath)
with open(filepath, encoding="utf-8") as f:
guid = 0
tokens = []
ner_tags = []
for line in f:
if "#" in line or line == "\n":
if tokens:
yield guid, {
"id": str(guid),
"tokens": tokens,
"ner_tags": ner_tags,
}
guid += 1
tokens = []
ner_tags = []
else:
# ronec tokens are tab separated
splits = line.split("\t")
tokens.append(splits[1])
ner_tags.append(splits[10].rstrip())
# last example
if tokens:
yield guid, {
"id": str(guid),
"tokens": tokens,
"ner_tags": ner_tags,
}
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