Datasets:
Tasks:
Text Classification
Sub-tasks:
multi-label-classification
Languages:
English
Size:
10K<n<100K
License:
File size: 5,110 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.
"""EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts."""
import json
import os
import datasets
_CITATION = """\
@inproceedings{chalkidis-etal-2019-large,
title = "Large-Scale Multi-Label Text Classification on {EU} Legislation",
author = "Chalkidis, Ilias and Fergadiotis, Emmanouil and Malakasiotis, Prodromos and Androutsopoulos, Ion",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/P19-1636",
doi = "10.18653/v1/P19-1636",
pages = "6314--6322"
}
"""
_DESCRIPTION = """\
EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts.
"""
_HOMEPAGE = "http://nlp.cs.aueb.gr/software_and_datasets/EURLEX57K/"
_LICENSE = "CC BY-SA (Creative Commons / Attribution-ShareAlike)"
_URLs = {
"eurlex57k": "http://archive.org/download/EURLEX57K/dataset.zip",
}
class EURLEX(datasets.GeneratorBasedBuilder):
"""EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts."""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(
name="eurlex57k", version=VERSION, description="EURLEX57K: Legal Multi-label Text Classification"
),
]
DEFAULT_CONFIG_NAME = "eurlex57k"
def _info(self):
features = datasets.Features(
{
"celex_id": datasets.Value("string"),
"title": datasets.Value("string"),
"text": datasets.Value("string"),
"eurovoc_concepts": datasets.features.Sequence(datasets.Value("string")),
}
)
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."""
my_urls = _URLs[self.config.name]
data_dir = dl_manager.download_and_extract(my_urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepath": os.path.join(data_dir, "train.jsonl"),
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl"), "split": "test"},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepath": os.path.join(data_dir, "dev.jsonl"),
"split": "dev",
},
),
]
def _generate_examples(
self, filepath, split # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
):
"""Yields examples as (key, example) tuples."""
with open(filepath, encoding="utf-8") as f:
for id_, row in enumerate(f):
data = json.loads(row)
yield id_, {
"celex_id": data["celex_id"],
"title": data["title"],
"text": "\n".join([data["header"], data["recitals"]] + data["main_body"]),
"eurovoc_concepts": data["eurovoc_concepts"],
}
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