Datasets:
Multilinguality:
multilingual
Size Categories:
5K<n<112K
Language Creators:
found
Annotations Creators:
no-annotation
Source Datasets:
original for Hindi, and modified [IndicGLUE](https://indicnlp.ai4bharat.org/indic-glue/) for other languages.
ArXiv:
Tags:
License:
| import json | |
| import os | |
| import datasets | |
| _CITATION = """\ | |
| @inproceedings{Kumar2022IndicNLGSM, | |
| title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages}, | |
| author={Aman Kumar and Himani Shrotriya and Prachi Sahu and Raj Dabre and Ratish Puduppully and Anoop Kunchukuttan and Amogh Mishra and Mitesh M. Khapra and Pratyush Kumar}, | |
| year={2022}, | |
| url = "https://arxiv.org/abs/2203.05437" | |
| } | |
| """ | |
| _DESCRIPTION = """\ | |
| This is the sentence summarization dataset released as part of IndicNLG Suite. Each | |
| input sentence is paired with an output summary. We create this dataset in eleven | |
| languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta and te. The total | |
| size of the dataset is 431K. | |
| """ | |
| _HOMEPAGE = "https://indicnlp.ai4bharat.org/indicnlg-suite" | |
| _LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License" | |
| _URL = "https://huggingface.co/datasets/ai4bharat/IndicSentenceSummarization/resolve/main/data/{}_IndicSentenceSummarization_v{}.zip" | |
| _LANGUAGES = [ | |
| "as", | |
| "bn", | |
| "gu", | |
| "hi", | |
| "kn", | |
| "ml", | |
| "mr", | |
| "or", | |
| "pa", | |
| "ta", | |
| "te" | |
| ] | |
| class IndicSentenceSummarization(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| BUILDER_CONFIGS = [ | |
| datasets.BuilderConfig( | |
| name="{}".format(lang), | |
| version=datasets.Version("1.0.0") | |
| ) | |
| for lang in _LANGUAGES | |
| ] | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "id":datasets.Value("string"), | |
| "input": datasets.Value("string"), | |
| "target": datasets.Value("string"), | |
| "url":datasets.Value("string") | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage=_HOMEPAGE, | |
| citation=_CITATION, | |
| license=_LICENSE, | |
| version=self.VERSION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| """Returns SplitGenerators.""" | |
| lang = str(self.config.name) | |
| url = _URL.format(lang, self.VERSION.version_str[:-2]) | |
| data_dir = dl_manager.download_and_extract(url) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir,"content",lang + "_train.jsonl"), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir,"content",lang + "_test.jsonl"), | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": os.path.join(data_dir,"content",lang + "_dev.jsonl"), | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath): | |
| """Yields examples as (key, example) tuples.""" | |
| with open(filepath, encoding="utf-8") as f: | |
| for idx_, row in enumerate(f): | |
| data = json.loads(row) | |
| yield idx_, { | |
| "id":data["id"], | |
| "input": data["Sentence"], | |
| "target": data["Summary"], | |
| "url":data["URL"] | |
| } |