import datasets import json import yaml import urllib.request _DESCRIPTION = """\ MegaWika is a multi- and crosslingual text dataset containing 30 million Wikipedia passages with their scraped and cleaned web citations. The passages span 50 Wikipedias in 50 languages, and the articles in which the passages were originally embedded are included for convenience.""" _CITATION = """\ @article{barham2023megawika, title={MegaWika: Millions of reports and their sources across 50 diverse languages}, author={Barham, Samuel and Weller, Orion and others}, journal={INSERT ARXIV PREPRINT ID HERE}, year={2023} }""" _HOMEPAGE = "https://huggingface.co/datasets/conceptofmind/MegaWika" _LICENSE = "cc-by-sa-4.0" # Load the file paths for all the splits file_list_url = "https://huggingface.co/datasets/conceptofmind/MegaWika/raw/main/files.yml" def get_data_urls(): with urllib.request.urlopen(file_list_url) as f: try: fnames = yaml.safe_load(f) return fnames['fnames'] except yaml.YAMLError as exc: print("Error loading the file paths for the dataset splits. Aborting.") return {} class MegaWikaConfig(datasets.BuilderConfig): """BuilderConfig for MegaWika.""" def __init__(self, language=None, **kwargs): """BuilderConfig for MegaWika. Args: language: The language of the dataset split **kwargs: Keyword arguments forwarded to super. """ super(MegaWikaConfig, self).__init__(**kwargs) self.language = language class MegaWika(datasets.GeneratorBasedBuilder): """MegaWika dataset.""" # Get available languages from the data URLs _DATA_URL = get_data_urls() BUILDER_CONFIGS = [ MegaWikaConfig( name=lang if lang != "all" else "default", language=lang, version=datasets.Version("1.0.0"), description=f"MegaWika {lang} configuration" ) for lang in ["all"] + list(_DATA_URL.keys()) ] DEFAULT_CONFIG_NAME = "default" # For the "all" configuration def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "article_title": datasets.Value("string"), "article_text": datasets.Value("string"), "entries": datasets.features.Sequence( { "id": datasets.Value("string"), "passage": { "text": [datasets.Value("string")], "parse": datasets.Value("string"), "en_tokens": [datasets.Value("string")], "lang_tokens": [datasets.Value("string")], "en_lang_token_map": [[datasets.Value("int32")]] }, "mt": { "original": datasets.Value("string"), "original_sents": [datasets.Value("string")], "translation": datasets.Value("string"), "translation_sents": [datasets.Value("string")], "translation_probs": [[datasets.Value("string")]], "repetitious_translation": datasets.Value("bool") }, "source_lang": datasets.Value("string"), "source_url": datasets.Value("string"), "source_text": datasets.Value("string"), "qa_pairs": datasets.Sequence( { "question": datasets.Value("string"), "en_answer": datasets.Value("string"), "lang_answer": datasets.Value("string"), "frames": datasets.Sequence( { "frame": datasets.Value("string"), "argument": datasets.Value("string") } ), "en_matches_in_source": [[datasets.Value("int32")]], "en_match_in_passage": [datasets.Value("int32")], "lang_matches_in_source": [[datasets.Value("int32")]], "lang_match_in_passage": [datasets.Value("int32")], "passage": [datasets.Value("string")], "en_answer_tokens": [datasets.Value("string")], "match_disambiguated_question": datasets.Value("string"), } ) } ) } ), supervised_keys=None, homepage=_HOMEPAGE, citation=_CITATION, license=_LICENSE ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" if self.config.language == "all": data_sources = self._DATA_URL else: data_sources = {self.config.language: self._DATA_URL[self.config.language]} return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # Using TRAIN as default split gen_kwargs={ "filepaths": dl_manager.download(data_sources[lang]) } ) for lang in data_sources ] def _get_qa_pair_list_features(self, qa_pair, feature_name): """Helper method to extract QA pair features.""" if feature_name in qa_pair and qa_pair[feature_name]: return qa_pair[feature_name] elif feature_name.startswith('en'): base_feature = '_'.join(feature_name.split('_')[1:]) if base_feature in qa_pair and qa_pair[base_feature]: return qa_pair[base_feature] return [] def _generate_examples(self, filepaths): """Yields examples.""" id_ = 0 for filepath in filepaths: try: with open(filepath, "r", encoding="utf-8") as f: for line in f: if line: example = json.loads(line) if example is not None and isinstance(example, dict): yield id_, { "article_title": example.get("article_title", ""), "article_text": example.get("article_text", ""), "entries": [ { "id": entry.get("id", "").lower(), "passage": { "text": entry['passage'].get("text", []), "parse": json.dumps(entry['passage'].get("parse", [{}])), "en_tokens": list(entry['passage'].get("en_tokens", {}).values()), "lang_tokens": list(entry['passage'].get("lang_tokens", {}).values()), "en_lang_token_map": [ (int(item[0]), int(item[1])) for item in entry['passage'].get("en_lang_token_map", {}).items() ] }, "mt": { "original": entry.get("original", ""), "original_sents": entry.get("original_sents", []), "translation": entry.get("translation", ""), "translation_sents": entry.get("translation_sents", []), "translation_probs": entry.get("translation_probs", [[]]), "repetitious_translation": entry.get("repetitious_translation", False) }, "source_lang": entry.get("source_lang", ""), "source_url": entry.get("source_url", ""), "source_text": entry.get("source_text", ""), "qa_pairs": [ { "question": qa_pair.get('question', ""), "en_answer": qa_pair.get('en_answer', qa_pair.get('answer', "")), 'lang_answer': qa_pair.get('lang_answer', ''), 'frames': qa_pair.get('frames', []), "en_matches_in_source": self._get_qa_pair_list_features(qa_pair, "en_matches_in_source"), "en_match_in_passage": self._get_qa_pair_list_features(qa_pair, "en_match_in_passage"), "lang_matches_in_source": self._get_qa_pair_list_features(qa_pair, "lang_matches_in_source"), "lang_match_in_passage": self._get_qa_pair_list_features(qa_pair, "lang_match_in_passage"), "passage": qa_pair.get('passage', []), "en_answer_tokens": qa_pair.get('en_answer_tokens', qa_pair.get('answer_tokens', [])), "match_disambiguated_question": qa_pair.get('match_disambiguated_question', ""), } for qa_pair in entry.get('qa_pairs', []) ] } for entry in example.get("entries", []) ] } id_ += 1 except Exception as e: print(f"Error reading file {filepath}: {str(e)}")