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"""SNOW T15 and T23: "Japanese Simplified Corpus with Core Vocabulary" and ''Crowdsourced Corpus of Sentence Simplification with Core Vocabulary".""" |
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import openpyxl |
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import pandas as pd |
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import datasets |
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_CITATION = """\ |
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@inproceedings{maruyama-yamamoto-2018-simplified, |
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title = "Simplified Corpus with Core Vocabulary", |
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author = "Maruyama, Takumi and |
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Yamamoto, Kazuhide", |
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booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)", |
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month = may, |
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year = "2018", |
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address = "Miyazaki, Japan", |
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publisher = "European Language Resources Association (ELRA)", |
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url = "https://www.aclweb.org/anthology/L18-1185", |
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} |
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@inproceedings{yamamoto-2017-simplified-japanese, |
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title = "やさしい⽇本語対訳コーパスの構築", |
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author = "⼭本 和英 and |
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丸⼭ 拓海 and |
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⾓張 ⻯晴 and |
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稲岡 夢⼈ and |
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⼩川 耀⼀朗 and |
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勝⽥ 哲弘 and |
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髙橋 寛治", |
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booktitle = "言語処理学会第23回年次大会", |
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month = 3月, |
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year = "2017", |
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address = "茨城, 日本", |
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publisher = "言語処理学会", |
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url = "https://www.anlp.jp/proceedings/annual_meeting/2017/pdf_dir/B5-1.pdf", |
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} |
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@inproceedings{katsuta-yamamoto-2018-crowdsourced, |
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title = "Crowdsourced Corpus of Sentence Simplification with Core Vocabulary", |
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author = "Katsuta, Akihiro and |
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Yamamoto, Kazuhide", |
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booktitle = "Proceedings of the Eleventh International Conference on Language Resources and Evaluation ({LREC} 2018)", |
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month = may, |
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year = "2018", |
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address = "Miyazaki, Japan", |
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publisher = "European Language Resources Association (ELRA)", |
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url = "https://www.aclweb.org/anthology/L18-1072", |
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} |
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""" |
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_DESCRIPTION = """\ |
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About SNOW T15: \ |
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The simplified corpus for the Japanese language. The corpus has 50,000 manually simplified and aligned sentences. \ |
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This corpus contains the original sentences, simplified sentences and English translation of the original sentences. \ |
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It can be used for automatic text simplification as well as translating simple Japanese into English and vice-versa. \ |
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The core vocabulary is restricted to 2,000 words where it is selected by accounting for several factors such as meaning preservation, variation, simplicity and the UniDic word segmentation criterion. |
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For details, refer to the explanation page of Japanese simplification (http://www.jnlp.org/research/Japanese_simplification). \ |
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The original texts are from "small_parallel_enja: 50k En/Ja Parallel Corpus for Testing SMT Methods", which is a bilingual corpus for machine translation. \ |
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\ |
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About SNOW T23: \ |
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An expansion corpus of 35,000 sentences rewritten in easy Japanese (simple Japanese vocabulary) based on SNOW T15. \ |
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The original texts are from "Tanaka Corpus" (http://www.edrdg.org/wiki/index.php/Tanaka_Corpus). |
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""" |
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_HOMEPAGE = "http://www.jnlp.org/SNOW/T15, http://www.jnlp.org/SNOW/T23" |
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_LICENSE = "CC BY 4.0" |
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_URLs = { |
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"snow_t15": "https://filedn.com/lit4DCIlHwxfS1gj9zcYuDJ/SNOW/T15-2020.1.7.xlsx", |
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"snow_t23": "https://filedn.com/lit4DCIlHwxfS1gj9zcYuDJ/SNOW/T23-2020.1.7.xlsx", |
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} |
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class SnowSimplifiedJapaneseCorpus(datasets.GeneratorBasedBuilder): |
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"""SNOW T15 and T23: "Japanese Simplified Corpus with Core Vocabulary" and ''Crowdsourced Corpus of Sentence Simplification with Core Vocabulary".""" |
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VERSION = datasets.Version("1.1.0") |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="snow_t15", version=VERSION, description="SNOW T15 dataset"), |
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datasets.BuilderConfig(name="snow_t23", version=VERSION, description="SNOW T23 dataset (extension)"), |
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] |
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DEFAULT_CONFIG_NAME = "snow_t15" |
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def _info(self): |
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if self.config.name == "snow_t15": |
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features = datasets.Features( |
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{ |
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"ID": datasets.Value("string"), |
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"original_ja": datasets.Value("string"), |
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"simplified_ja": datasets.Value("string"), |
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"original_en": datasets.Value("string"), |
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} |
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) |
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else: |
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features = datasets.Features( |
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{ |
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"ID": datasets.Value("string"), |
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"original_ja": datasets.Value("string"), |
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"simplified_ja": datasets.Value("string"), |
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"original_en": datasets.Value("string"), |
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"proper_noun": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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my_urls = _URLs[self.config.name] |
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data_url = dl_manager.download(my_urls) |
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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={"filepath": data_url, "split": "train"}, |
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), |
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] |
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def _generate_examples(self, filepath, split): |
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"""Yields examples.""" |
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with open(filepath, "rb") as f: |
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df = pd.read_excel(f, engine="openpyxl").astype("str") |
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if self.config.name == "snow_t15": |
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for id_, row in df.iterrows(): |
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yield id_, { |
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"ID": row["ID"], |
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"original_ja": row["#日本語(原文)"], |
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"simplified_ja": row["#やさしい日本語"], |
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"original_en": row["#英語(原文)"], |
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} |
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else: |
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for id_, row in df.iterrows(): |
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yield id_, { |
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"ID": row["ID"], |
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"original_ja": row["#日本語(原文)"], |
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"simplified_ja": row["#やさしい日本語"], |
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"original_en": row["#英語(原文)"], |
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"proper_noun": row["#固有名詞"], |
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} |
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