Datasets:
Languages:
Slovenian
Multilinguality:
monolingual
Language Creators:
found
Annotations Creators:
no-annotation
License:
File size: 9,963 Bytes
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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
from typing import Optional
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("1.0.1")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="public", version=VERSION,
description="Load the publicly available dataset (ccGigafida)."),
datasets.BuilderConfig(name="private", version=VERSION,
description="Load the privately available dataset (Gigafida/Gigafida2) by manuallly "
"providing the path to the data."),
]
DEFAULT_CONFIG_NAME = "public"
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_lemmas": datasets.Sequence(datasets.Sequence(datasets.Sequence(datasets.Value("string")))),
"doc_msds": 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):
if self.config.name == "public":
urls = _URLS["ccGigafida"]
data_dir = dl_manager.download_and_extract(urls)
data_dir = os.path.join(data_dir, "ccGigafidaV1_0")
else:
if dl_manager.manual_dir is None or not os.path.exists(dl_manager.manual_dir):
logging.warning("data_dir does not point to a valid directory")
# Allow user to specify path to the private Gigafida directory: `load_dataset(..., data_dir=...)`
data_dir = dl_manager.manual_dir
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 = []
doc_msds, doc_lemmas = [], []
for para_tag in body_tag.findall(f".//{NAMESPACE}p"):
id_para = para_tag.attrib[f"{XML_NAMESPACE}id"]
tokenized_para, para_str = [], []
para_msds, para_lemmas = [], []
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 = [], []
msd_tags, lemmas = [], []
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)
msd_tags.append(child_tag.attrib["ana"][len("mte:"):] if "ana" in child_tag.attrib else "")
lemmas.append(child_tag.text)
# word or punctuation character
else:
str_sent.append(child_tag.text)
tokenized_sent.append(child_tag.text)
msd_tags.append(child_tag.attrib["ana"][len("mte:"):] if "ana" in child_tag.attrib else child_tag.attrib["msd"])
lemmas.append(child_tag.attrib["lemma"] if "lemma" in child_tag.attrib else child_tag.text)
str_sent = "".join(str_sent)
tokenized_para.append(tokenized_sent)
para_str.append(str_sent)
para_sent_ids.append(id_sent)
para_msds.append(msd_tags)
para_lemmas.append(lemmas)
tokenized_doc.append(tokenized_para)
doc_str.append(para_str)
doc_sent_ids.append(para_sent_ids)
doc_msds.append(para_msds)
doc_lemmas.append(para_lemmas)
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_lemmas": doc_lemmas,
"doc_msds": doc_msds,
"doc_string": doc_str,
"id_sents": doc_sent_ids
}
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