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"""Europarl Monolingual Dataset.""" |
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from __future__ import absolute_import, division, print_function |
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from dataclasses import dataclass |
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import json |
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import os |
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import re |
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import datasets |
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_CITATION = """\ |
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@inproceedings{koehn2005europarl, |
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title={Europarl: A parallel corpus for statistical machine translation}, |
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author={Koehn, Philipp}, |
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booktitle={MT summit}, |
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volume={5}, |
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pages={79--86}, |
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year={2005}, |
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organization={Citeseer} |
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} |
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""" |
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_DESCRIPTION = """\ |
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Europarl Monolingual Dataset. |
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The Europarl parallel corpus is extracted from the proceedings of the |
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European Parliament (from 2000 to 2011). It includes versions in 21 European |
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languages: Romanic (French, Italian, Spanish, Portuguese, Romanian), |
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Germanic (English, Dutch, German, Danish, Swedish), Slavik (Bulgarian, |
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Czech, Polish, Slovak, Slovene), Finni-Ugric (Finnish, Hungarian, Estonian), |
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Baltic (Latvian, Lithuanian), and Greek. |
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Upstream url: https://www.statmt.org/europarl/ |
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""" |
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_HOMEPAGE = "https://www.statmt.org/europarl/" |
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_AVAILABLE_LANGUAGES = [ |
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("bg", "Bulgarian"), ("cs", "Czech"), ("da", "Danish"), ("de", "German"), |
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("el", "Greek"), ("en", "English"), ("es", "Spanish"), ("et", "Estonian"), |
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("fi", "Finnish"), ("fr", "French"), ("hu", "Hungarian"), ("it", "Italian"), |
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("lt", "Lithuanian"), ("lv", "Latvian"), ("nl", "Dutch"), ("pl", "Polish"), |
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("pt", "Portuguese"), ("ro", "Romanian"), ("sk", "Slovak"), |
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("sl", "Slovene"), ("sv", "Swedish") |
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] |
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@dataclass |
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class EuroparlMonoConfig(datasets.BuilderConfig): |
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"""BuilderConfig for Europarl Monolingual.""" |
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language: str = None |
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class EuroparlMonoDataset(datasets.GeneratorBasedBuilder): |
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"""Europarl Monolingual Dataset.""" |
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_TRAIN_FILE = "train.jsonl" |
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_VAL_FILE = "val.jsonl" |
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_TEST_FILE = "test.jsonl" |
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BUILDER_CONFIGS = [ |
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EuroparlMonoConfig( |
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name="europarl-%s" % langISO2, |
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language=langISO2, |
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version=datasets.Version("7.0.0"), |
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description="Europarl %s Dataset." % langEnglish, |
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) for langISO2, langEnglish in _AVAILABLE_LANGUAGES |
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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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"paragraph": datasets.Value("string"), |
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"date": datasets.Value("string"), |
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"chapter": datasets.Value("string"), |
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"speaker": datasets.Value("int16"), |
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"speaker_name": datasets.Value("string") |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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arch_path = dl_manager.download_and_extract(os.path.join(_HOMEPAGE, "v%d" % self.config.version.major, "europarl.tgz")) |
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path_dir = os.path.join(arch_path, os.path.join("txt", self.config.language)) |
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paths = [os.path.join(path_dir, file) for file in os.listdir(path_dir)] |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, gen_kwargs={"filepath": paths} |
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) |
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] |
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def _generate_examples(self, filepath): |
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"""Generate Europarl Monolingual examples.""" |
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id_ = 0 |
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for file in filepath: |
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with open(file, "r") as f: |
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current_date = "-".join(os.path.basename(file).strip(".txt").split("-")[-4:-1]) |
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current_paragraph = "" |
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current_paragraph_id = 0 |
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current_chapter = 0 |
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current_speaker_id = 0 |
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current_speaker_name = "" |
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for line in f: |
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if not line.startswith("<"): |
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current_paragraph += line.strip("\n") |
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else: |
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if len(current_paragraph) != 0: |
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yield id_, { |
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"paragraph": current_paragraph, |
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"date": current_date, |
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"chapter": current_chapter, |
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"speaker": current_speaker_id, |
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"speaker_name": current_speaker_name, |
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} |
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current_paragraph = "" |
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id_ += 1 |
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if line.startswith("<P>"): |
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current_paragraph_id += 1 |
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if line.startswith("<CHAPTER"): |
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current_chapter = line.lstrip("<CHAPTER ID=").rstrip(">\n").strip("\"") |
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if line.startswith("<SPEAKER"): |
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current_speaker_id = "0" |
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current_speaker_name = "" |
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grps = re.findall("([^<\s]+)=([^\s\">]+|\"[^\">]+\")", line) |
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for attr, value in grps: |
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value = value.strip("\"") |
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if attr == "ID": |
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current_speaker_id = int(value) |
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elif attr == "NAME": |
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current_speaker_name = value |
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