Datasets:
Tasks:
Fill-Mask
Sub-tasks:
masked-language-modeling
Languages:
English
Multilinguality:
monolingual
Size Categories:
10M<n<100M
Language Creators:
found
Annotations Creators:
no-annotation
ArXiv:
License:
"""C4 dataset based on Common Crawl.""" | |
import gzip | |
import json | |
import datasets | |
try: | |
import lzma as xz | |
except ImportError: | |
import pylzma as xz | |
logger = datasets.logging.get_logger(__name__) | |
_DESCRIPTION = """\ | |
A living legal dataset. | |
""" | |
_CITATION = """ | |
TODO | |
""" | |
_URL = "" | |
_DATA_URL = { | |
"r_legaladvice" : | |
{ | |
"train" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.r_legaldvice.jsonl.xz"], | |
"validation" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.r_legaldvice.jsonl.xz"] | |
}, | |
"courtlistenerdocketentries" : { | |
"train" : [ | |
"https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.courtlistenerdocketentries.0.jsonl.xz", | |
"https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.courtlistenerdocketentries.1.jsonl.xz", | |
"https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.courtlistenerdocketentries.2.jsonl.xz", | |
"https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.courtlistenerdocketentries.3.jsonl.xz" | |
], | |
"validation" : [ | |
"https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.courtlistenerdocketentries.0.jsonl.xz", | |
"https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.courtlistenerdocketentries.0.jsonl.xz" | |
] | |
}, | |
"federal_register" : { | |
"train" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.federal_register.jsonl.xz"], | |
"validation" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.federal_register.jsonl.xz"] | |
}, | |
"bva_opinions" : { | |
"train" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.bva.jsonl.xz"], | |
"validation" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.bva.jsonl.xz"] | |
}, | |
"us_bills" : { | |
"train" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.us_bills.jsonl.xz"], | |
"validation" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.us_bills.jsonl.xz"] | |
}, | |
"cc_casebooks" : { | |
"train" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/train.cc_casebooks.jsonl.xz"], | |
"validation" : ["https://huggingface.co/datasets/pile-of-law/pile-of-law/resolve/main/data/validation.cc_casebooks.jsonl.xz"] | |
} | |
} | |
_VARIANTS = ["all"] + list(_DATA_URL.keys()) | |
class PileOfLaw(datasets.GeneratorBasedBuilder): | |
"""TODO""" | |
BUILDER_CONFIGS = [datasets.BuilderConfig(name) for name in _VARIANTS] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"text": datasets.Value("string"), | |
"created_timestamp": datasets.Value("string"), | |
"downloaded_timestamp": datasets.Value("string"), | |
"url": datasets.Value("string"), | |
} | |
), | |
supervised_keys=None, | |
homepage=_URL, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
data_urls = {} | |
if self.config.name == "all": | |
data_sources = list(_DATA_URL.keys()) | |
else: | |
data_sources = [self.config.name] | |
for split in ["train", "validation"]: | |
data_urls[split] = [] | |
for source in data_sources: | |
for chunk in _DATA_URL[source][split]: | |
data_urls[split].append(chunk) | |
train_downloaded_files = dl_manager.download(data_urls["train"]) | |
validation_downloaded_files = dl_manager.download(data_urls["validation"]) | |
return [ | |
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": validation_downloaded_files} | |
), | |
] | |
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) | |
with xz.open(filepath, "rt", encoding="utf-8") as f: | |
for line in f: | |
if line: | |
example = json.loads(line) | |
yield id_, example | |
id_ += 1 | |