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