Datasets:
Tasks:
Fill-Mask
Multilinguality:
multilingual
Size Categories:
10M<n<100M
Language Creators:
found
Annotations Creators:
other
Source Datasets:
original
Tags:
License:
File size: 4,311 Bytes
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"""Legal MC4"""
import ast
import json
import datasets
from huggingface_hub.file_download import hf_hub_url
try:
import lzma as xz
except ImportError:
import pylzma as xz
datasets.logging.set_verbosity_info()
logger = datasets.logging.get_logger(__name__)
_DESCRIPTION = """
Legal-MC4: A Corpus Covering the Legal Part of MC4 for European Languages
"""
_CITATION = """
"""
_REPO_ID = "joelito/legal-mc4"
_URL = f"https://huggingface.co/datasets/{_REPO_ID}"
_LANGUAGES = {
"bg": 0,
"cs": 2,
"da": 0,
"de": 8,
"el": 0,
"en": 1,
"es": 9,
"et": 0,
"fi": 0,
"fr": 2,
"ga": 0,
# "hr", # hr is not present in mc4
"hu": 0,
"it": 3,
"lt": 0,
"lv": 0,
"mt": 0,
"nl": 0,
"pl": 2,
"pt": 1,
"ro": 0,
"sk": 0,
"sl": 0,
"sv": 0,
}
_LANGS = list(_LANGUAGES.keys())
class LegalMC4Config(datasets.BuilderConfig):
"""BuilderConfig for Legal-MC4."""
def __init__(self, name: str, **kwargs):
"""BuilderConfig for Legal-MC4.
Args:
name: One of bg,cs,da,de,el,en,es,et,fi,fr,ga,hu,it,lt,lv,mt,nl,pl,pt,ro,sk,sl,sv or all
**kwargs: keyword arguments forwarded to super.
"""
super(LegalMC4Config, self).__init__(**kwargs)
self.name = name
class MC4Legal(datasets.GeneratorBasedBuilder):
"""Legal-MC4: A Corpus Covering the Legal Part of MC4 for European Languages"""
BUILDER_CONFIGS = [LegalMC4Config(language) for language in _LANGS + ["all"]]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"url": datasets.Value("string"),
"timestamp": datasets.Value("timestamp[s]"),
"matches": datasets.Sequence(datasets.Value("string")),
"text": datasets.Value("string"),
}
),
supervised_keys=None,
homepage=_URL,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
def get_url(file_name):
return hf_hub_url(repo_id=_REPO_ID, filename=f"data/{file_name}.jsonl.xz", repo_type="dataset")
data_urls = []
languages = _LANGS if self.config.name == "all" else [self.config.name]
split_generators = []
for split in [datasets.Split.TRAIN, datasets.Split.VALIDATION]:
for language in languages:
shards = range(_LANGUAGES[language] + 1) if split == datasets.Split.TRAIN else [0]
for shard in shards:
data_urls.append(get_url(f"{language}.{str(split)}.{shard}"))
downloaded_files = dl_manager.download(data_urls)
split_generators.append(
datasets.SplitGenerator(name=split, gen_kwargs={"filepaths": downloaded_files})
)
return split_generators
def _generate_examples(self, filepaths):
"""This function returns the examples in the raw (text) form by iterating on all the files."""
id_ = 0
for filepath in filepaths:
logger.info("Generating examples from = %s", filepath)
try:
with xz.open(open(filepath, "rb"), "rt", encoding="utf-8") as f:
for line in f:
if line:
example = json.loads(line)
if example is not None and isinstance(example, dict):
timestamp = example.get("timestamp", "")
# remove the Z at the end (time zone)
if isinstance(timestamp, str) and timestamp.endswith("Z"):
timestamp = timestamp[:-1]
yield id_, {
"url": example.get("url", ""),
"timestamp": timestamp,
"matches": example.get("matches", []),
"text": example.get("text", ""),
}
id_ += 1
except Exception:
logger.exception("Error while processing file %s", filepath)
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