Datasets:
Tasks:
Text Generation
Sub-tasks:
language-modeling
Languages:
Hebrew
Multilinguality:
monolingual
Size Categories:
n<1K
Language Creators:
crowdsourced
Annotations Creators:
no-annotation
Source Datasets:
original
Tags:
License:
File size: 2,340 Bytes
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import glob
import os
from functools import partial
import datasets
VERSION = datasets.Version("0.0.1")
SUBSET_NAMES = [
"kneset16",
"kneset17",
"knesset_tagged",
]
class KnessetMeetingsCorpus(datasets.GeneratorBasedBuilder):
"""Knesset meetings corpus"""
BUILDER_CONFIGS = [
datasets.BuilderConfig(name=name, version=VERSION,
description=f"{name} meetings corpus")
for name in SUBSET_NAMES
]
def _info(self):
return datasets.DatasetInfo(
description="A corpus of transcriptions of Knesset (Israeli parliament) meetings between January 2004 and November 2005",
features=datasets.Features(
{
"path": datasets.Value("string"),
"text": datasets.Value("string"),
}
),
homepage="https://zenodo.org/record/2707356",
citation="""TODO""",
)
def _split_generators(self, dl_manager):
downloader = partial(
lambda split: dl_manager.download_and_extract(
f"data/{self.config.name}.tar.gz"),
)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"root_path": downloader("train"),
"split": "train",
"subset_name": self.config.name,
},
)
]
def _generate_examples(self, root_path, split, subset_name):
data_folder = os.path.join(root_path, subset_name)
if subset_name == "knesset_tagged":
for xml_file in glob.glob(f"{data_folder}/16/*.xml"):
uid = os.path.splitext(os.path.basename(xml_file))[0]
yield uid, {
"path": xml_file,
"text": None,
}
else:
for txt_file in glob.glob(f"{data_folder}/txt/*.txt"):
uid = os.path.splitext(os.path.basename(txt_file))[0]
docx_file = os.path.join(data_folder, "docx", f"{uid}.docx")
yield uid, {
"path": docx_file,
"text": open(txt_file, "r").read(),
}
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