Update parquet files

README.md

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----
-license: cc-by-nc-sa-4.0
----

cc_gigafida.py

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-"""(A publicly available subsample of) a reference corpus of Slovene texts."""
-
-
-import glob
-import logging
-import os
-import os.path
-import re
-import xml.etree.ElementTree as ET
-from copy import deepcopy
-
-import datasets
-
-XML_NAMESPACE = "{http://www.w3.org/XML/1998/namespace}"
-
-
-def namespace(element):
-    # https://stackoverflow.com/a/12946675
-    m = re.match(r'\{.*\}', element.tag)
-    return m.group(0) if m else ''
-
-
-_CITATION = """\
-@misc{ccGigafida,
-    title = {Written corpus {ccGigafida} 1.0},
-    author = {Logar, Nata{\v s}a and Erjavec, Toma{\v z} and Krek, Simon and Gr{\v c}ar, Miha and Holozan, Peter},
-    url = {http://hdl.handle.net/11356/1035},
-    note = {Slovenian language resource repository {CLARIN}.{SI}},
-    copyright = {Creative Commons - Attribution-{NonCommercial}-{ShareAlike} 4.0 International ({CC} {BY}-{NC}-{SA} 4.0)},
-    issn = {2820-4042},
-    year = {2013}
-}
-"""
-
-_DESCRIPTION = """\
-The ccGigafida corpus contains a subsample of the Gigafida corpus. The Gigafida corpus is an extensive collection of 
-Slovene text of various genres, from daily newspapers, magazines, all kinds of books (fiction, non-fiction, textbooks), 
-web pages, transcriptions of parliamentary debates and similar.
-"""
-
-_HOMEPAGE = "http://eng.slovenscina.eu/korpusi/proste-zbirke"
-
-_LICENSE = "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)"
-
-_URLS = {
-    "ccGigafida": "https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1035/ccGigafidaV1_0.zip"
-}
-
-
-class CcGigafida(datasets.GeneratorBasedBuilder):
-    """(A publicly available subsample of) a reference corpus of Slovene texts."""
-
-    VERSION = datasets.Version("1.0.0")
-
-    def _info(self):
-        features = datasets.Features(
-            {
-                "id_doc": datasets.Value("string"),
-                "doc_title": datasets.Value("string"),
-                "authors": datasets.Sequence(datasets.Value("string")),
-                "publish_date": datasets.Value("string"),
-                "publisher": datasets.Value("string"),
-                "genres": datasets.Sequence(datasets.Value("string")),
-                "doc_tokenized": datasets.Sequence(datasets.Sequence(datasets.Sequence(datasets.Value("string")))),
-                "doc_string": datasets.Sequence(datasets.Sequence(datasets.Value("string"))),
-                "id_sents": datasets.Sequence(datasets.Sequence(datasets.Value("string")))
-            }
-        )
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        # Allow user to specify path to the full Gigafida directory: `load_dataset(..., data_dir=...)`
-        if dl_manager.manual_dir is not None:
-            data_dir = dl_manager.manual_dir
-        else:
-            urls = _URLS["ccGigafida"]
-            data_dir = dl_manager.download_and_extract(urls)
-            data_dir = os.path.join(data_dir, "ccGigafidaV1_0")
-
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"data_dir": data_dir}
-            )
-        ]
-
-    def _generate_examples(self, data_dir):
-        GENRE_MAPPING = {
-            "SSJ.T": "tisk", "SSJ.T.K": "tisk/knjižno", "SSJ.T.K.L": "tisk/knjižno/leposlovno",
-            "SSJ.T.K.S": "tisk/knjižno/strokovno", "SSJ.T.P": "tisk/periodično", "SSJ.T.P.C": "tisk/periodično/časopis",
-            "SSJ.T.P.R": "tisk/periodično/revija", "SSJ.T.D": "tisk/drugo", "SSJ.I": "internet"
-        }
-        # genres are prefixed by "ssj:" in Gigafida 2.0
-        for genre, description in deepcopy(GENRE_MAPPING).items():
-            GENRE_MAPPING[f"ssj:{genre}"] = description
-
-        # Recursively search for xml files in subdirectories
-        all_files = [os.path.join(data_dir, file_name)
-                     for file_name in glob.glob(os.path.join(data_dir, "**", "*.xml"), recursive=True)
-                     if os.path.isfile(os.path.join(data_dir, file_name))]
-        all_files = sorted(all_files)  # fix order
-
-        for _idx_file, file_path in enumerate(all_files):
-            curr_doc = ET.parse(file_path)
-            root = curr_doc.getroot()
-            NAMESPACE = namespace(root)
-            id_doc = root.attrib[f"{XML_NAMESPACE}id"]
-
-            # Document metadata
-            bibl_el = root.find(f".//{NAMESPACE}bibl")
-            doc_title = bibl_el.find(f"{NAMESPACE}title").text.strip()
-            authors = list(map(lambda _tag: _tag.text.strip(), bibl_el.findall(f"{NAMESPACE}author")))
-            publish_date = bibl_el.find(f"{NAMESPACE}date").text.strip()
-            publisher = bibl_el.find(f"{NAMESPACE}publisher").text.strip()
-
-            category_tags = root.findall(f".//{NAMESPACE}catRef")
-            genres = []
-            for _tag in category_tags:
-                # in ccGigafida, the genres are noted with a "#" prefix
-                __tag = _tag.attrib["target"][1:] if _tag.attrib["target"].startswith("#") else _tag.attrib["target"]
-                mapped_tag = GENRE_MAPPING.get(__tag, None)
-                # In addition to the genre of the document, there is sometimes a category assigned by the deduplication tool (dedup:nodup)
-                if mapped_tag is None:
-                    continue
-
-                genres.append(mapped_tag)
-
-            # Tokenized and raw string version - raw string version preserves spaces
-            body_tag = root.find(f".//{NAMESPACE}body")
-            tokenized_doc, doc_str = [], []
-            doc_sent_ids = []
-
-            for para_tag in body_tag.findall(f".//{NAMESPACE}p"):
-                id_para = para_tag.attrib[f"{XML_NAMESPACE}id"]
-                tokenized_para, para_str = [], []
-                para_sent_ids = []
-
-                for _idx_sent, sent_tag in enumerate(para_tag.findall(f".//{NAMESPACE}s")):
-                    # ccGigafida does not have sentence IDs:
-                    #   construct ID by taking the paragraph ID + their index in the paragraph
-                    id_sent = sent_tag.attrib.get(f"{XML_NAMESPACE}id", None)
-                    if id_sent is None:
-                        id_sent = f"{id_para}.{_idx_sent}"
-
-                    tokenized_sent, str_sent = [], []
-                    for child_tag in sent_tag:
-                        tag_str = child_tag.tag[len(NAMESPACE):]
-                        if tag_str not in {"w", "S", "c", "pc"}:
-                            logging.warning(f"Found unexpected tag in a sentence: '{tag_str}', skipping it.")
-                            continue
-
-                        # Tag for whitespace in ccGigafida
-                        if tag_str == "S":
-                            str_sent.append(" ")
-
-                        # Tag for:
-                        # - single-letter characters in ccGigafida;
-                        # - whitespace in Gigafida
-                        elif tag_str == "c":
-                            str_sent.append(child_tag.text)
-                            if child_tag.text != " ":
-                                tokenized_sent.append(child_tag.text)
-
-                        # word or punctuation character
-                        else:
-                            str_sent.append(child_tag.text)
-                            tokenized_sent.append(child_tag.text)
-
-                    str_sent = "".join(str_sent)
-                    tokenized_para.append(tokenized_sent)
-                    para_str.append(str_sent)
-                    para_sent_ids.append(id_sent)
-
-                tokenized_doc.append(tokenized_para)
-                doc_str.append(para_str)
-                doc_sent_ids.append(para_sent_ids)
-
-            yield _idx_file, {
-                "id_doc": id_doc,
-                "doc_title": doc_title,
-                "authors": authors,
-                "publish_date": publish_date,
-                "publisher": publisher,
-                "genres": genres,
-                "doc_tokenized": tokenized_doc,
-                "doc_string": doc_str,
-                "id_sents": doc_sent_ids
-            }

dataset_infos.json

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-{"default": {"description": "The ccGigafida corpus contains a subsample of the Gigafida corpus. The Gigafida corpus is an extensive collection of \nSlovene text of various genres, from daily newspapers, magazines, all kinds of books (fiction, non-fiction, textbooks), \nweb pages, transcriptions of parliamentary debates and similar.\n", "citation": "@misc{ccGigafida,\n    title = {Written corpus {ccGigafida} 1.0},\n    author = {Logar, Nata{\u000b s}a and Erjavec, Toma{\u000b z} and Krek, Simon and Gr{\u000b c}ar, Miha and Holozan, Peter},\n    url = {http://hdl.handle.net/11356/1035},\n    note = {Slovenian language resource repository {CLARIN}.{SI}},\n    copyright = {Creative Commons - Attribution-{NonCommercial}-{ShareAlike} 4.0 International ({CC} {BY}-{NC}-{SA} 4.0)},\n    issn = {2820-4042},\n    year = {2013}\n}\n", "homepage": "http://eng.slovenscina.eu/korpusi/proste-zbirke", "license": "Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)", "features": {"id_doc": {"dtype": "string", "id": null, "_type": "Value"}, "doc_title": {"dtype": "string", "id": null, "_type": "Value"}, "authors": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "publish_date": {"dtype": "string", "id": null, "_type": "Value"}, "publisher": {"dtype": "string", "id": null, "_type": "Value"}, "genres": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "doc_tokenized": {"feature": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "doc_string": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}, "id_sents": {"feature": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "cc_gigafida", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2054478553, "num_examples": 31722, "dataset_name": "cc_gigafida"}}, "download_checksums": {"https://www.clarin.si/repository/xmlui/bitstream/handle/11356/1035/ccGigafidaV1_0.zip": {"num_bytes": 954116273, "checksum": "448e284d6f92d54f123e2b7fa433c9d84d060f2db07c589e9b45a356a1f5242e"}}, "download_size": 954116273, "post_processing_size": null, "dataset_size": 2054478553, "size_in_bytes": 3008594826}}

private/cc_gigafida-train.parquet

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