srwac.py

# coding=utf-8
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"""Serbian web corpus bsWaC 1.1"""

import datasets


_CITATION = """
 @misc{11356/1063,
 title = {Serbian web corpus {srWaC} 1.1},
 author = {Ljube{\v s}i{\'c}, Nikola and Klubi{\v c}ka, Filip},
 url = {http://hdl.handle.net/11356/1063},
 note = {Slovenian language resource repository {CLARIN}.{SI}},
 copyright = {Creative Commons - Attribution-{ShareAlike} 4.0 International ({CC} {BY}-{SA} 4.0)},
 year = {2016} }
"""

_DESCRIPTION = """\
The Serbian web corpus srWaC was built by crawling the .rs top-level domain in 2014. The corpus was near-deduplicated on paragraph level, normalised via diacritic restoration, morphosyntactically annotated and lemmatised. The corpus is shuffled by paragraphs. Each paragraph contains metadata on the URL, domain and language identification (Serbian vs. Croatian).
Version 1.0 of this corpus is described in http://www.aclweb.org/anthology/W14-0405. Version 1.1 contains newer and better linguistic annotations.
"""

_LICENSE = "CC BY-SA 4.0"

_HOMEPAGE = "http://nlp.ffzg.hr/resources/corpora/srwac/"
_URLS = [
    "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1063/srWaC1.1.01.xml.gz",
    "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1063/srWaC1.1.02.xml.gz",
    "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1063/srWaC1.1.03.xml.gz",
    "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1063/srWaC1.1.04.xml.gz",
    "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1063/srWaC1.1.05.xml.gz",
    "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1063/srWaC1.1.06.xml.gz",
]


class Srwac(datasets.GeneratorBasedBuilder):
    """Serbian web corpus bsWaC"""

    VERSION = datasets.Version("1.1.0")
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name="srwac",
            version=VERSION,
            description="The SrWac dataset.",
        ),
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "sentence": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_file = dl_manager.download_and_extract(_URLS)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": downloaded_file,
                },
            ),
        ]

    def _generate_examples(self, filepath):
        for file_idx, fp in enumerate(filepath):
            with open(fp, encoding="utf8") as f:
                for id_, row in enumerate(f):
                    yield f"{file_idx}_{id_}", {
                        "sentence": row.strip(),
                    }