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"""HSE Russian dataset by Glushkova et al..""" |
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import datasets |
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import pandas as pd |
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from functools import reduce |
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_CITATION = """ |
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@article{glushkova2019char, |
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title={Char-RNN and Active Learning for Hashtag Segmentation}, |
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author={Glushkova, Taisiya and Artemova, Ekaterina}, |
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journal={arXiv preprint arXiv:1911.03270}, |
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year={2019} |
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} |
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""" |
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_DESCRIPTION = """ |
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2000 real hashtags collected from several pages about civil services on vk.com (a Russian social network) |
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and then segmented manually. |
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""" |
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_URL = "https://raw.githubusercontent.com/glushkovato/hashtag_segmentation/master/data/test_rus.csv" |
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class HSE(datasets.GeneratorBasedBuilder): |
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VERSION = datasets.Version("1.0.0") |
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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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"index": datasets.Value("int32"), |
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"hashtag": datasets.Value("string"), |
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"segmentation": 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/glushkovato/hashtag_segmentation", |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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downloaded_files = dl_manager.download(_URL) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files }), |
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] |
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def _generate_examples(self, filepath): |
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df = pd.read_csv(filepath) |
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records = df.to_dict("records") |
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def get_segmentation(a, b): |
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return "".join(reduce(lambda x,y: x + y, list(zip(a,b)))).replace("0","").replace("1"," ").strip() |
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for idx, row in enumerate(records): |
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yield idx, { |
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"index": idx, |
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"hashtag": row["hashtag"], |
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"segmentation": get_segmentation( |
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row["hashtag"], |
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row["true_segmentation"] |
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)} |