Datasets:
Tasks:
Text Generation
Sub-tasks:
language-modeling
Languages:
Indonesian
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original
License:
| # 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. | |
| """Indonesian Movie Subtitle.""" | |
| import csv | |
| import json | |
| import os | |
| import datasets | |
| _DESCRIPTION = """\ | |
| This dataset is built as a playground for analyzing text on movie subtitle | |
| """ | |
| _HOMEPAGE = "https://github.com/jakartaresearch" | |
| # TODO: Add link to the official dataset URLs here | |
| # The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
| # This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
| _TRAIN_URL = "https://media.githubusercontent.com/media/jakartaresearch/hf-datasets/main/movie-subtitles/dataset.csv" | |
| # TODO: Name of the dataset usually match the script name with CamelCase instead of snake_case | |
| class IndoMovieSubtitle(datasets.GeneratorBasedBuilder): | |
| """Indonesian Movie Subtitle.""" | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| features = datasets.Features( | |
| { | |
| "movie_title": datasets.Value("string"), | |
| "order": datasets.Value("string"), | |
| "duration": datasets.Value("string"), | |
| "text": datasets.Value("string") | |
| } | |
| ) | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE | |
| ) | |
| def _split_generators(self, dl_manager): | |
| train_path = dl_manager.download_and_extract(_TRAIN_URL) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}), | |
| ] | |
| # method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
| def _generate_examples(self, filepath): | |
| """Generate examples.""" | |
| with open(filepath, encoding="utf-8") as csv_file: | |
| csv_reader = csv.reader(csv_file, delimiter=",") | |
| next(csv_reader) | |
| for id_, row in enumerate(csv_reader): | |
| movie_title, order, duration, text = row | |
| yield id_, {"movie_title": movie_title, "order": order, "duration": duration, "text": text} |