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"""MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages""" |
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import json |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """\ |
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MASSIVE is a parallel dataset of > 1M utterances across 51 languages with annotations |
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for the Natural Language Understanding tasks of intent prediction and slot annotation. |
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Utterances span 60 intents and include 55 slot types. MASSIVE was created by localizing |
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the SLURP dataset, composed of general Intelligent Voice Assistant single-shot interactions. |
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""" |
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_URL = "amazon-massive-dataset-1.0.tar.gz" |
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_LANGUAGES = { |
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"af": "af-ZA", |
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"am": "am-ET", |
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"ar": "ar-SA", |
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"az": "az-AZ", |
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"bn": "bn-BD", |
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"cy": "cy-GB", |
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"da": "da-DK", |
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"de": "de-DE", |
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"el": "el-GR", |
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"en": "en-US", |
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"es": "es-ES", |
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"fa": "fa-IR", |
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"fi": "fi-FI", |
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"fr": "fr-FR", |
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"he": "he-IL", |
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"hi": "hi-IN", |
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"hu": "hu-HU", |
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"hy": "hy-AM", |
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"id": "id-ID", |
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"is": "is-IS", |
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"it": "it-IT", |
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"ja": "ja-JP", |
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"jv": "jv-ID", |
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"ka": "ka-GE", |
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"km": "km-KH", |
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"kn": "kn-IN", |
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"ko": "ko-KR", |
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"lv": "lv-LV", |
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"ml": "ml-IN", |
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"mn": "mn-MN", |
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"ms": "ms-MY", |
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"my": "my-MM", |
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"nb": "nb-NO", |
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"nl": "nl-NL", |
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"pl": "pl-PL", |
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"pt": "pt-PT", |
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"ro": "ro-RO", |
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"ru": "ru-RU", |
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"sl": "sl-SL", |
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"sq": "sq-AL", |
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"sv": "sv-SE", |
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"sw": "sw-KE", |
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"ta": "ta-IN", |
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"te": "te-IN", |
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"th": "th-TH", |
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"tl": "tl-PH", |
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"tr": "tr-TR", |
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"ur": "ur-PK", |
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"vi": "vi-VN", |
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"zh-CN": "zh-CN", |
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"zh-TW": "zh-TW", |
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} |
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_SCENARIOS = [ |
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"social", |
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"transport", |
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"calendar", |
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"play", |
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"news", |
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"datetime", |
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"recommendation", |
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"email", |
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"iot", |
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"general", |
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"audio", |
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"lists", |
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"qa", |
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"cooking", |
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"takeaway", |
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"music", |
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"alarm", |
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"weather", |
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] |
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class MASSIVE(datasets.GeneratorBasedBuilder): |
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"""MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name=name, |
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version=datasets.Version("1.0.0"), |
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description=f"The MASSIVE corpora for {name}", |
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) |
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for name in _LANGUAGES.keys() |
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] |
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DEFAULT_CONFIG_NAME = "en" |
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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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"label": datasets.features.ClassLabel(names=_SCENARIOS), |
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"label_text": datasets.Value("string"), |
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"text": datasets.Value("string"), |
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}, |
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), |
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supervised_keys=None, |
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homepage="https://github.com/alexa/massive", |
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citation="_CITATION", |
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license="_LICENSE", |
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) |
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def _split_generators(self, dl_manager): |
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archive_path = dl_manager.download(_URL) |
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files = dl_manager.iter_archive(archive_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={ |
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"files": files, |
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"split": "train", |
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"lang": self.config.name, |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={ |
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"files": files, |
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"split": "dev", |
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"lang": self.config.name, |
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}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={ |
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"files": files, |
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"split": "test", |
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"lang": self.config.name, |
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}, |
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), |
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] |
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def _generate_examples(self, files, split, lang): |
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filepath = "1.0/data/" + _LANGUAGES[lang] + ".jsonl" |
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logger.info("⏳ Generating examples from = %s", filepath) |
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for path, f in files: |
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if path == filepath: |
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lines = f.readlines() |
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key_ = 0 |
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for line in lines: |
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data = json.loads(line) |
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if data["partition"] != split: |
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continue |
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yield key_, { |
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"id": data["id"], |
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"label": data["scenario"], |
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"label_text": data["scenario"], |
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"text": data["utt"], |
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} |
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key_ += 1 |
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