# coding=utf-8 # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Polish Summaries Corpus: the corpus of Polish news summaries""" import glob import xml.etree.ElementTree as ET import datasets # TODO: Add BibTeX citation # Find for instance the citation on arxiv or on the dataset repo/website _CITATION = """\ @inproceedings{ ogro:kop:14:lrec, author = "Ogrodniczuk, Maciej and Kopeć, Mateusz", pdf = "http://nlp.ipipan.waw.pl/Bib/ogro:kop:14:lrec.pdf", title = "The {P}olish {S}ummaries {C}orpus", pages = "3712--3715", crossref = "lrec:14" } @proceedings{ lrec:14, editor = "Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Loftsson, Hrafn and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios", isbn = "978-2-9517408-8-4", title = "Proceedings of the Ninth International {C}onference on {L}anguage {R}esources and {E}valuation, {LREC}~2014", url = "http://www.lrec-conf.org/proceedings/lrec2014/index.html", booktitle = "Proceedings of the Ninth International {C}onference on {L}anguage {R}esources and {E}valuation, {LREC}~2014", address = "Reykjavík, Iceland", key = "LREC", year = "2014", organization = "European Language Resources Association (ELRA)" } """ # TODO: Add description of the dataset here # You can copy an official description _DESCRIPTION = """\ Polish Summaries Corpus: the corpus of Polish news summaries. """ # TODO: Add a link to an official homepage for the dataset here _HOMEPAGE = "http://zil.ipipan.waw.pl/PolishSummariesCorpus" # TODO: Add the licence for the dataset here if you can find it _LICENSE = "CC BY v.3" # TODO: Add link to the official dataset URLs here # The HuggingFace dataset library don't host the datasets but only point to the original files # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) _URL = "http://zil.ipipan.waw.pl/PolishSummariesCorpus?action=AttachFile&do=get&target=PSC_1.0.zip" # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case class Polsum(datasets.GeneratorBasedBuilder): """Polish Summaries Corpus: the corpus of Polish news summaries.""" VERSION = datasets.Version("1.1.0") def _info(self): features = datasets.Features( { "id": datasets.Value("string"), "date": datasets.Value("string"), "title": datasets.Value("string"), "section": datasets.Value("string"), "authors": datasets.Value("string"), "body": datasets.Value("string"), "summaries": datasets.features.Sequence( { "ratio": datasets.Value("int32"), "type": datasets.Value("string"), "author": datasets.Value("string"), "body": datasets.Value("string"), "spans": datasets.features.Sequence( { "start": datasets.Value("int32"), "end": datasets.Value("int32"), "span_text": datasets.Value("string"), } ), } ), } ) return datasets.DatasetInfo( # This is the description that will appear on the datasets page. description=_DESCRIPTION, # This defines the different columns of the dataset and their types features=features, # Here we define them above because they are different between the two configurations # If there's a common (input, target) tuple from the features, # specify them here. They'll be used if as_supervised=True in # builder.as_dataset. supervised_keys=None, # Homepage of the dataset for documentation homepage=_HOMEPAGE, # License for the dataset if available license=_LICENSE, # Citation for the dataset citation=_CITATION, ) def _split_generators(self, dl_manager): """Returns SplitGenerators.""" # dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLs # It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. # By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive data_dir = dl_manager.download_and_extract(_URL) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, # These kwargs will be passed to _generate_examples gen_kwargs={ "filepaths": glob.glob(data_dir + "/*/*/*.xml"), }, ), ] def _generate_examples(self, filepaths): """Yields examples.""" # TODO: This method will receive as arguments the `gen_kwargs` defined in the previous `_split_generators` method. # It is in charge of opening the given file and yielding (key, example) tuples from the dataset # The key is not important, it's more here for legacy reason (legacy from tfds) for i, xml_path in enumerate(sorted(filepaths)): root = ET.parse(xml_path).getroot() text_id = root.get("id") date_tag = root.find("date") date = date_tag.text.strip() title_tag = root.find("title") title = title_tag.text.strip() section_tag = root.find("section") section = section_tag.text.strip() authors_tag = root.find("authors") authors = authors_tag.text.strip() body_tag = root.find("body") body = body_tag.text.strip() summaries_tag = root.find("summaries") summaries = [] for summary_tag in summaries_tag.iterfind("summary"): sratio = int(summary_tag.get("ratio")) stype = summary_tag.get("type") sauthor = summary_tag.get("author") sbody_tag = summary_tag.find("body") sbody = sbody_tag.text.strip() spans_tag = summary_tag.find("spans") spans = [] if spans_tag: for span_tag in spans_tag.iterfind("span"): start = int(span_tag.get("start")) end = int(span_tag.get("end")) span_text = span_tag.text.strip() spans.append( { "start": start, "end": end, "span_text": span_text, } ) summaries.append( { "ratio": sratio, "type": stype, "author": sauthor, "body": sbody, "spans": spans, } ) yield i, { "id": text_id, "date": date, "title": title, "section": section, "authors": authors, "body": body, "summaries": summaries, }