Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-analysis
Languages:
Yoruba
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
License:
| # coding=utf-8 | |
| # Copyright 2020 HuggingFace Datasets Authors. | |
| # | |
| # 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. | |
| # Lint as: python3 | |
| """YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS""" | |
| import datasets | |
| import json | |
| import pandas as pd | |
| logger = datasets.logging.get_logger(__name__) | |
| _CITATION = """\ | |
| @inproceedings{ | |
| shode2022yosm, | |
| title={{YOSM}: A {NEW} {YORUBA} {SENTIMENT} {CORPUS} {FOR} {MOVIE} {REVIEWS}}, | |
| author={Iyanuoluwa Shode and David Ifeoluwa Adelani and Anna Feldman}, | |
| booktitle={3rd Workshop on African Natural Language Processing}, | |
| year={2022}, | |
| url={https://openreview.net/forum?id=rRzx5qzVIb9} | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS | |
| - Yoruba | |
| """ | |
| languages=[ | |
| 'yoruba' | |
| ] | |
| _URL = "https://github.com/IyanuSh/YOSM" | |
| _TRAINING_FILE = "train.tsv" | |
| _DEV_FILE = "dev.tsv" | |
| _TEST_FILE = "test.tsv" | |
| class Yosm(datasets.GeneratorBasedBuilder): | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| version=datasets.Version('1.0.0'), | |
| name=lang, | |
| description='YOSM: A NEW YORUBA SENTIMENT CORPUS FOR MOVIE REVIEWS' | |
| ) for lang in languages | |
| ] | |
| def _info(self): | |
| features = datasets.features({ | |
| 'yo_review': datasets.Value('string'), | |
| 'sentiment': 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 | |
| supervised_keys=None, | |
| # Homepage of the dataset for documentation | |
| homepage=_URL, | |
| # License for the dataset if available | |
| license='', | |
| # Citation for the dataset | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| lang = self.config.name | |
| splits = [ | |
| datasets.SplitGenerator( | |
| name='train', | |
| gen_kwargs={ | |
| 'filepath': _TRAINING_FILE, | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name='dev', | |
| gen_kwargs={ | |
| 'filepath': _DEV_FILE, | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name='test', | |
| gen_kwargs={ | |
| 'filepath': _TEST_FILE, | |
| }, | |
| ) | |
| ] | |
| return splits | |
| def _generate_examples(self, filepath): | |
| yosm_df = pd.read_csv(filepath, sep="\t", lineterminator='\n') | |
| for index, row in yosm_df.iterrows(): | |
| yield row["yo_review"], row["sentiment"] | |