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"""TODO(hansards): Add a description here.""" |
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import glob |
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import os |
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import datasets |
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_CITATION = """ |
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""" |
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_DESCRIPTION = """ |
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This release contains 1.3 million pairs of aligned text chunks (sentences or smaller fragments) |
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from the official records (Hansards) of the 36th Canadian Parliament. |
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The complete Hansards of the debates in the House and Senate of the 36th Canadian Parliament, |
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as far as available, were aligned. The corpus was then split into 5 sets of sentence pairs: |
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training (80% of the sentence pairs), two sets of sentence pairs for testing (5% each), and |
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two sets of sentence pairs for final evaluation (5% each). The current release consists of the |
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training and testing sets. The evaluation sets are reserved for future MT evaluation purposes |
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and currently not available. |
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Caveats |
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1. This release contains only sentence pairs. Even though the order of the sentences is the same |
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as in the original, there may be gaps resulting from many-to-one, many-to-many, or one-to-many |
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alignments that were filtered out. Therefore, this release may not be suitable for |
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discourse-related research. |
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2. Neither the sentence splitting nor the alignments are perfect. In particular, watch out for |
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pairs that differ considerably in length. You may want to filter these out before you do |
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any statistical training. |
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The alignment of the Hansards was performed as part of the ReWrite project under funding |
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from the DARPA TIDES program. |
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""" |
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_URL = "https://www.isi.edu/natural-language/download/hansard/" |
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_DATA_URL = "http://www.isi.edu/natural-language/download/hansard/" |
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_HOUSE_DEBATES_TRAIN_SET_FILE = "hansard.36.r2001-1a.house.debates.training.tar" |
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_HOUSE_DEBATES_TEST_SET_FILE = "hansard.36.r2001-1a.house.debates.testing.tar" |
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_SENATE_DEBATES_TRAIN_SET_FILE = "hansard.36.r2001-1a.senate.debates.training.tar" |
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_SENATE_DEBATES_TEST_SET_FILE = "hansard.36.r2001-1a.senate.debates.testing.tar" |
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class HansardsConfig(datasets.BuilderConfig): |
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"""BuilderConfig for Hansards.""" |
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def __init__(self, **kwargs): |
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"""BuilderConfig for Hansards. |
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Args: |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(HansardsConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) |
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class Hansards(datasets.GeneratorBasedBuilder): |
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"""TODO(hansards): Short description of my dataset.""" |
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VERSION = datasets.Version("0.1.0") |
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BUILDER_CONFIGS = [ |
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HansardsConfig( |
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name="house", |
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description="""\ |
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Alignment of debates in the House of the 36th Canadian Parliament: 1,070K sentence pairs. |
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""", |
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), |
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HansardsConfig( |
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name="senate", |
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description="""\ |
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Alignment of debates in the Senate of the 36th Canadian Parliament: 208K sentence pairs. |
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""", |
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), |
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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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"fr": datasets.Value("string"), |
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"en": datasets.Value("string") |
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} |
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), |
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supervised_keys=None, |
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homepage=_URL, |
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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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name = self.config.name |
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if name == "house": |
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urls_to_download = { |
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"train": _DATA_URL + _HOUSE_DEBATES_TRAIN_SET_FILE, |
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"test": _DATA_URL + _HOUSE_DEBATES_TEST_SET_FILE, |
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} |
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elif name == "senate": |
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urls_to_download = { |
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"train": _DATA_URL + _SENATE_DEBATES_TRAIN_SET_FILE, |
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"test": _DATA_URL + _SENATE_DEBATES_TEST_SET_FILE, |
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} |
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else: |
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raise ValueError("Wrong builder config name '{}', it has to be either 'house' or 'senate'.".format(name)) |
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downloaded_files = dl_manager.download_and_extract(urls_to_download) |
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if type(downloaded_files) == str: |
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downloaded_files = {k: downloaded_files for k in urls_to_download.keys()} |
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fr_files = {} |
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en_files = {} |
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for split_name in downloaded_files.keys(): |
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archive_dir = "hansard.36/Release-2001.1a/sentence-pairs/{}/debates/development/{}".format( |
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name, split_name + "ing" |
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) |
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data_dir = os.path.join(downloaded_files[split_name], archive_dir) |
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split_compress_files = list(sorted(glob.glob(os.path.join(data_dir, "*.gz")))) |
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split_compress_files += list(sorted(glob.glob(os.path.join(data_dir, "**/*.gz")))) |
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fr_split_compress_files = sorted([f for f in split_compress_files if f.endswith(".f.gz")]) |
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en_split_compress_files = sorted([f for f in split_compress_files if f.endswith(".e.gz")]) |
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fr_files[split_name] = dl_manager.extract(fr_split_compress_files) |
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en_files[split_name] = dl_manager.extract(en_split_compress_files) |
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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={"fr_files": fr_files["train"], "en_files": en_files["train"]}, |
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), |
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datasets.SplitGenerator( |
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name=datasets.Split.TEST, |
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gen_kwargs={"fr_files": fr_files["test"], "en_files": en_files["test"]}, |
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), |
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] |
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def _generate_examples(self, fr_files, en_files): |
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"""Yields examples.""" |
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for fr_file, en_file in zip(fr_files, en_files): |
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with open(fr_file, "rb") as fr: |
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with open(en_file, "rb") as en: |
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for j, (fr_line, en_line) in enumerate(zip(fr, en)): |
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line_id = "{}:{}".format(fr_file, j) |
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rec = {"fr": fr_line.decode("ISO-8859-1").strip(), "en": en_line.decode("ISO-8859-1").strip()} |
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yield line_id, rec |
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