Datasets:
Languages:
Thai
Multilinguality:
monolingual
Size Categories:
100K<n<1M
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
Tags:
License:
import csv | |
import os | |
import datasets | |
csv.field_size_limit(int(1e6)) # to accommodate large fields | |
_CITATION = """\ | |
@mastersthesis{chumpolsathien_2020, | |
title={Using Knowledge Distillation from Keyword Extraction to Improve the Informativeness of Neural Cross-lingual Summarization}, | |
author={Chumpolsathien, Nakhun}, | |
year={2020}, | |
school={Beijing Institute of Technology} | |
""" | |
_DESCRIPTION = """\ | |
ThaiSum is a large-scale corpus for Thai text summarization obtained from several online news websites namely Thairath, | |
ThaiPBS, Prachathai, and The Standard. This dataset consists of over 350,000 article and summary pairs | |
written by journalists. | |
""" | |
class ThaiSumConfig(datasets.BuilderConfig): | |
"""BuilderConfig for ThaiSum.""" | |
def __init__(self, **kwargs): | |
"""BuilderConfig for ThaiSum. | |
Args: | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super(ThaiSumConfig, self).__init__(**kwargs) | |
class Thaisum(datasets.GeneratorBasedBuilder): | |
"""ThaiSum: The largest dataset for Thai text summarization""" | |
_DOWNLOAD_URL = "https://archive.org/download/thaisum_datasets/data.zip" | |
_TRAIN_FILE = "train.csv" | |
_VAL_FILE = "valid.csv" | |
_TEST_FILE = "test.csv" | |
BUILDER_CONFIGS = [ | |
ThaiSumConfig( | |
name="thaisum", | |
version=datasets.Version("1.0.0"), | |
description="ThaiSum: The largest dataset for Thai text summarization", | |
), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{ | |
"title": datasets.Value("string"), | |
"body": datasets.Value("string"), | |
"summary": datasets.Value("string"), | |
"type": datasets.Value("string"), | |
"tags": datasets.Value("string"), | |
"url": datasets.Value("string"), | |
} | |
), | |
supervised_keys=("body", "summary"), | |
homepage="https://github.com/nakhunchumpolsathien/ThaiSum", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
arch_path = dl_manager.download_and_extract(self._DOWNLOAD_URL) | |
data_dir = os.path.join(arch_path, "data") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={"filepath": os.path.join(data_dir, self._TRAIN_FILE)}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={"filepath": os.path.join(data_dir, self._VAL_FILE)}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={"filepath": os.path.join(data_dir, self._TEST_FILE)}, | |
), | |
] | |
def _generate_examples(self, filepath): | |
"""Generate examples.""" | |
with open(filepath, encoding="utf-8") as f: | |
csv_reader = csv.reader(f) | |
next(csv_reader) # skip header | |
for id_, row in enumerate(csv_reader): | |
yield id_, { | |
"title": row[0], | |
"body": row[1], | |
"summary": row[2], | |
"type": row[3], | |
"tags": row[4], | |
"url": row[5], | |
} | |