Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
Spanish
Size:
1K<n<10K
License:
# 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. | |
import glob | |
import os | |
import re | |
from xml.dom.minidom import parseString | |
import datasets | |
# no BibTeX citation | |
_CITATION = "" | |
_DESCRIPTION = """\ | |
The Muchocine reviews dataset contains 3,872 longform movie reviews in Spanish language, | |
each with a shorter summary review, and a rating on a 1-5 scale. | |
""" | |
_LICENSE = "CC-BY-2.1" | |
_URLs = {"default": "http://www.lsi.us.es/~fermin/corpusCine.zip"} | |
class Muchocine(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.1.1") | |
def _info(self): | |
features = datasets.Features( | |
{ | |
"review_body": datasets.Value("string"), | |
"review_summary": datasets.Value("string"), | |
"star_rating": datasets.ClassLabel(names=[str(i) for i in range(1, 6)]), | |
} | |
) | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=features, | |
supervised_keys=None, | |
homepage="http://www.lsi.us.es/~fermin/index.php/Datasets", | |
license=_LICENSE, | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
my_urls = _URLs[self.config.name] | |
data_dir = dl_manager.download_and_extract(my_urls) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepaths": sorted(glob.glob(os.path.join(data_dir, "corpusCriticasCine", "*.xml"))), | |
"split": "train", | |
}, | |
), | |
] | |
def _generate_examples(self, filepaths, split): | |
for filepath in filepaths: | |
with open(filepath, encoding="latin-1") as f: | |
id = re.search(r"\d+\.xml", filepath)[0][:-4] | |
txt = f.read() | |
txt = txt.replace("“", '"').replace("”", '"').replace("…", "") | |
txt = txt.replace("‘", '"').replace("’", '"').replace("′", "") | |
txt = txt.replace("à", "à").replace("–", "-").replace("è", "è") | |
txt = txt.replace("ö", "ö").replace("ç", "ç").replace("&", "and") | |
try: | |
doc = parseString(txt) | |
except Exception as e: | |
# skip 6 malformed xml files, for example unescaped < and > | |
_ = e | |
continue | |
btxt = "" | |
review_bod = doc.getElementsByTagName("body") | |
if len(review_bod) > 0: | |
for node in review_bod[0].childNodes: | |
if node.nodeType == node.TEXT_NODE: | |
btxt += node.data + " " | |
rtxt = "" | |
review_summ = doc.getElementsByTagName("summary") | |
if len(review_summ) > 0: | |
for node in review_summ[0].childNodes: | |
if node.nodeType == node.TEXT_NODE: | |
rtxt += node.data + " " | |
yield id, { | |
"review_body": btxt, | |
"review_summary": rtxt, | |
"star_rating": doc.documentElement.attributes["rank"].value, | |
} | |