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Delete loading script

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  1. mintaka.py +0 -177
mintaka.py DELETED
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- # coding=utf-8
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-
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- """Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering"""
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-
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- import json
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- import datasets
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-
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- logger = datasets.logging.get_logger(__name__)
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-
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- _DESCRIPTION = """\
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- Mintaka is a complex, natural, and multilingual dataset designed for experimenting with end-to-end
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- question-answering models. Mintaka is composed of 20,000 question-answer pairs collected in English,
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- annotated with Wikidata entities, and translated into Arabic, French, German, Hindi, Italian,
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- Japanese, Portuguese, and Spanish for a total of 180,000 samples.
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- Mintaka includes 8 types of complex questions, including superlative, intersection, and multi-hop questions,
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- which were naturally elicited from crowd workers.
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- """
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-
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- _CITATION = """\
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- @inproceedings{sen-etal-2022-mintaka,
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- title = "Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering",
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- author = "Sen, Priyanka and Aji, Alham Fikri and Saffari, Amir",
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- booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
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- month = oct,
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- year = "2022",
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- address = "Gyeongju, Republic of Korea",
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- publisher = "International Committee on Computational Linguistics",
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- url = "https://aclanthology.org/2022.coling-1.138",
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- pages = "1604--1619"
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- }
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- """
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-
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- _LICENSE = """\
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- Copyright Amazon.com Inc. or its affiliates.
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- Attribution 4.0 International
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- """
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-
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- _TRAIN_URL = "https://raw.githubusercontent.com/amazon-science/mintaka/main/data/mintaka_train.json"
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- _DEV_URL = "https://raw.githubusercontent.com/amazon-science/mintaka/main/data/mintaka_dev.json"
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- _TEST_URL = "https://raw.githubusercontent.com/amazon-science/mintaka/main/data/mintaka_test.json"
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-
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-
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- _LANGUAGES = ['en', 'ar', 'de', 'ja', 'hi', 'pt', 'es', 'it', 'fr']
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-
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- _ALL = "all"
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-
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- class Mintaka(datasets.GeneratorBasedBuilder):
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- """Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering"""
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-
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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"Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering for {name}",
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- ) for name in _LANGUAGES
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- ]
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-
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- BUILDER_CONFIGS.append(datasets.BuilderConfig(
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- name = _ALL,
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- version = datasets.Version("1.0.0"),
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- description = f"Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering",
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- ))
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-
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- DEFAULT_CONFIG_NAME = 'en'
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-
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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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- "lang": datasets.Value("string"),
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- "question": datasets.Value("string"),
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- "answerText": datasets.Value("string"),
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- "category": datasets.Value("string"),
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- "complexityType": datasets.Value("string"),
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- "questionEntity": [{
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- "name": datasets.Value("string"),
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- "entityType": datasets.Value("string"),
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- "label": datasets.Value("string"),
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- "mention": datasets.Value("string"),
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- "span": [datasets.Value("int32")],
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- }],
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- "answerEntity": [{
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- "name": datasets.Value("string"),
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- "label": datasets.Value("string"),
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- }]
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- },
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- ),
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- supervised_keys=None,
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- citation=_CITATION,
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- license=_LICENSE,
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- )
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-
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- def _split_generators(self, dl_manager):
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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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- "file": dl_manager.download_and_extract(_TRAIN_URL),
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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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- "file": dl_manager.download_and_extract(_DEV_URL),
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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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- "file": dl_manager.download_and_extract(_TEST_URL),
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- "lang": self.config.name,
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- }
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- ),
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- ]
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-
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- def _generate_examples(self, file, lang):
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- if lang == _ALL:
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- langs = _LANGUAGES
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- else:
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- langs = [lang]
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-
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- key_ = 0
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-
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- logger.info("⏳ Generating examples from = %s", ", ".join(lang))
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-
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- with open(file, encoding='utf-8') as json_file:
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- data = json.load(json_file)
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- for lang in langs:
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- for sample in data:
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- questionEntity = [
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- {
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- "name": str(qe["name"]),
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- "entityType": qe["entityType"],
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- "label": qe["label"] if "label" in qe else "",
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- # span only applies for English question
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- "mention": qe["mention"] if lang == "en" else None,
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- "span": qe["span"] if lang == "en" else [],
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- } for qe in sample["questionEntity"]
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- ]
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-
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- answers = []
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- if sample['answer']["answerType"] == "entity" and sample['answer']['answer'] is not None:
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- answers = sample['answer']['answer']
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- elif sample['answer']["answerType"] == "numerical" and "supportingEnt" in sample["answer"]:
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- answers = sample['answer']['supportingEnt']
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-
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- # helper to get language for the corresponding language
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- def get_label(labels, lang):
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- if lang in labels:
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- return labels[lang]
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- if 'en' in labels:
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- return labels['en']
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- return None
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-
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- answerEntity = [
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- {
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- "name": str(ae["name"]),
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- "label": get_label(ae["label"], lang),
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- } for ae in answers
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- ]
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-
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- yield key_, {
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- "id": sample["id"],
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- "lang": lang,
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- "question": sample["question"] if lang == 'en' else sample['translations'][lang],
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- "answerText": sample["answer"]["mention"],
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- "category": sample["category"],
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- "complexityType": sample["complexityType"],
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- "questionEntity": questionEntity,
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- "answerEntity": answerEntity,
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- }
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-
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- key_ += 1