Datasets:
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import json
import datasets
import os
_CITATION = """\
"""
_LICENSE = """\
"""
_DESCRIPTION = """\
SemEval 2022 Task 8: Multilingual News Article Similarity
"""
_LANGUAGES_TRAIN = {
"en": "en",
"de": "de",
"es": "es",
"pl": "pl",
"tr": "tr",
"fr": "fr",
"ar": "ar",
"de-en": "de-en",
}
_LANGUAGES_TEST = {
"en": "en",
"de": "de",
"es": "es",
"pl": "pl",
"tr": "tr",
"ar": "ar",
"ru": "ru",
"zh": "zh",
"fr": "fr",
"de-en": "de-en",
"es-en": "es-en",
"it": "it",
"pl-en": "pl-en",
"zh-en": "zh-en",
"es-it": "es-it",
"de-fr": "de-fr",
"de-pl": "de-pl",
"fr-pl": "fr-pl",
}
_LANGUAGES = {**_LANGUAGES_TRAIN, **_LANGUAGES_TEST}
_ALL_LANGUAGES = "all_languages"
_HOMEPAGE_URL = "https://competitions.codalab.org/competitions/33835"
_DOWNLOAD_URL = "{lang}/{split}.jsonl"
_VERSION = "1.0.0"
class STS22Task8Config(datasets.BuilderConfig):
"""BuilderConfig for STS22Task8Config."""
def __init__(self, languages=None, **kwargs):
super(STS22Task8Config, self).__init__(version=datasets.Version(_VERSION, ""), **kwargs),
self.languages = languages
class STS22Task8(datasets.GeneratorBasedBuilder):
"""Multilingual News Article Similarity"""
BUILDER_CONFIGS = [
STS22Task8Config(
name=_ALL_LANGUAGES,
languages=_LANGUAGES,
description="Multilingual News Article Similarity",
)
] + [
STS22Task8Config(
name=lang,
languages=[lang],
description=f"{_LANGUAGES[lang]} examples from a collection of multilingual news articles",
)
for lang in _LANGUAGES
]
BUILDER_CONFIG_CLASS = STS22Task8Config
DEFAULT_CONFIG_NAME = _ALL_LANGUAGES
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"score": datasets.Value("float32"),
},
),
supervised_keys=None,
license=_LICENSE,
homepage=_HOMEPAGE_URL,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
# train_urls = [_DOWNLOAD_URL.format(split="train", lang=lang) for lang in self.config.languages if lang in _LANGUAGES_TRAIN]
test_urls = [
_DOWNLOAD_URL.format(split="test", lang=lang) for lang in self.config.languages if lang in _LANGUAGES_TEST
]
# train_paths = dl_manager.download_and_extract(train_urls)
test_paths = dl_manager.download_and_extract(test_urls)
return [
# datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"file_paths": train_paths}),
datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"file_paths": test_paths}),
]
def _generate_examples(self, file_paths):
row_count = 0
for file_path in file_paths:
with open(file_path, "r", encoding="utf-8") as f:
for line in f:
yield row_count, json.loads(line)
row_count += 1
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