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"""SituatedQA: Incorporating Extra-Linguistic Contexts into QA.""" |
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import json |
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import re |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_CITATION = """\ |
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@article{ zhang2021situatedqa, |
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title={ {S}ituated{QA}: Incorporating Extra-Linguistic Contexts into {QA} }, |
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author={ Zhang, Michael J.Q. and Choi, Eunsol }, |
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journal={ Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) }, |
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year={ 2021 } |
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} |
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""" |
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_DESCRIPTION = """\ |
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""" |
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_URL = "https://raw.githubusercontent.com/mikejqzhang/SituatedQA/master/data/qa_data/" |
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_URLS = { |
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"geo_train": _URL + "geo.train.jsonl", |
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"geo_dev": _URL + "geo.dev.jsonl", |
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"geo_test": _URL + "geo.test.jsonl", |
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"temp_train": _URL + "temp.train.jsonl", |
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"temp_dev": _URL + "temp.dev.jsonl", |
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"temp_test": _URL + "temp.test.jsonl", |
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} |
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class SituatedQAConfig(datasets.BuilderConfig): |
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def __init__(self, **kwargs): |
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"""BuilderConfig |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(SituatedQAConfig, self).__init__(**kwargs) |
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class Squall(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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SituatedQAConfig(name = 'geo'), |
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SituatedQAConfig(name = 'temp')] |
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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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"question": datasets.Value("string"), |
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"id": datasets.Value("string"), |
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"edited_question": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"date_type": datasets.Value("string"), |
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"location": datasets.Value("string"), |
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"answer": datasets.features.Sequence(datasets.Value("string")), |
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"any_answer": datasets.features.Sequence(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/mikejqzhang/SituatedQA/tree/master", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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urls_to_download = { |
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"geo_train": _URLS["geo_train"], |
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"geo_dev": _URLS["geo_dev"], |
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"geo_test": _URLS["geo_test"], |
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"temp_train": _URLS["temp_train"], |
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"temp_dev": _URLS["temp_dev"], |
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"temp_test": _URLS["temp_test"], |
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} |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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if self.config.name == 'geo': |
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train_file = downloaded_files["geo_train"] |
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dev_file = downloaded_files["geo_dev"] |
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test_file = downloaded_files["geo_test"] |
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else: |
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train_file = downloaded_files["temp_train"] |
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dev_file = downloaded_files["temp_dev"] |
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test_file = downloaded_files["temp_test"] |
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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={"split_key": "train", "filepath": train_file}), |
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datasets.SplitGenerator( |
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name=datasets.Split.VALIDATION, |
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gen_kwargs={"split_key": "dev", "filepath": dev_file}), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"split_key": "test", "filepath": test_file}), |
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] |
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def _generate_examples(self, split_key, filepath): |
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"""This function returns the examples in the raw (text) form.""" |
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logger.info("generating examples from = %s", filepath) |
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with open(filepath, 'r') as file: |
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json_list = list(file) |
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for i, line in enumerate(json_list): |
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data = json.loads(line) |
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if 'location' not in data: |
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data['location']='' |
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if 'date' not in data: |
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data['date']='' |
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if 'date_type' not in data: |
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data['date_type']='' |
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yield i, { |
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"question": data["question"], |
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"id": str(data["id"]), |
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"edited_question": data["edited_question"], |
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"date": data["date"], |
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"date_type": data["date_type"], |
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"location": data["location"], |
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"answer": data["answer"], |
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"any_answer": data["any_answer"] |
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} |
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