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import os |
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import json |
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import datasets |
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_DESCRIPTION = """MQA is a multilingual corpus of questions and answers parsed from the Common Crawl. Questions are divided between Frequently Asked Questions (FAQ) pages and Community Question Answering (CQA) pages.""" |
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_HOMEPAGE_URL = "https://huggingface.co/datasets/clips/mqa" |
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_CITATION = """ |
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@misc{debruyn2021mfaq, |
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title={MFAQ: a Multilingual FAQ Dataset}, |
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author={Maxime {De Bruyn} and Ehsan Lotfi and Jeska Buhmann and Walter Daelemans}, |
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year={2021}, |
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booktitle={MRQA@EMNLP2021}, |
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} |
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""" |
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_VERSION = "0.4" |
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_BASE_NAME = "" |
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_TRAIN_BASE_URL = "data/{}.json" |
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_TRAIN_NEG_URL = "data/{}.neg.json" |
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_LANGUAGES = [ |
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"en", "de", "es", "fr", |
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"ru", "ja", "it", "zh", "pt", |
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"nl", "tr", "pl", "vi", "ar", |
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"id", "uk", "ro", "no", |
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"sv", "el", "fi", "da", |
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"cs", "ko", "fa", "hi", "hu", |
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"sk", "lt", "et", "hr", "is", |
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"lv", "ms", "bg", "sr", "ca" |
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] |
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class MFAQLightConfig(datasets.BuilderConfig): |
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def __init__(self, *args, language="en", negatives=True, **kwargs): |
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super().__init__( |
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*args, |
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name=f"{language}-{negatives}", |
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**kwargs, |
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) |
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self.language = language |
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self.negatives = negatives |
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class MFAQLight(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [] |
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for language in _LANGUAGES: |
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BUILDER_CONFIGS.append(MFAQLightConfig(language=language, negatives=True)) |
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BUILDER_CONFIGS.append(MFAQLightConfig(language=language, negatives=False)) |
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BUILDER_CONFIGS.append(MFAQLightConfig(language="all", negatives=True)) |
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BUILDER_CONFIGS.append(MFAQLightConfig(language="all", negatives=False)) |
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BUILDER_CONFIG_CLASS = MFAQLightConfig |
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def _info(self): |
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features = { |
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"question": datasets.Value("string"), |
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"answer": datasets.Value("string"), |
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"id": datasets.Value("string"), |
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"negatives": [datasets.Value("string")] |
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} |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features(features), |
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supervised_keys=None, |
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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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train_filenames = [] |
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languages = _LANGUAGES if self.config.language == "all" else [self.config.language] |
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base_path = _TRAIN_NEG_URL if self.config.negatives else _TRAIN_BASE_URL |
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for language in languages: |
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path = dl_manager.download_and_extract(base_path.format(language)) |
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train_filenames.append(path) |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={"filenames": train_filenames}, |
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) |
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] |
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def _generate_examples(self, filenames): |
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for filename in filenames: |
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with open(filename, "r") as f: |
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for _, line in enumerate(f): |
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question = json.loads(line) |
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yield question["id"], { |
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"question": question["question"], |
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"answer": question["answer"], |
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"id": question["id"], |
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"negatives": question.get("negative", []) |
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} |
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