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Browse files- IndicParaphrase.py +0 -134
- README.md +0 -216
- data/as_IndicParaphrase_v1.0.zip → as/indic_paraphrase-test.parquet +2 -2
- data/kn_IndicParaphrase_v1.0.zip → as/indic_paraphrase-validation.parquet +2 -2
- data/gu_IndicParaphrase_v1.0.zip → bn/indic_paraphrase-test.parquet +2 -2
- data/bn_IndicParaphrase_v1.0.zip → bn/indic_paraphrase-train-00000-of-00002.parquet +2 -2
- data/mr_IndicParaphrase_v1.0.zip → bn/indic_paraphrase-train-00001-of-00002.parquet +2 -2
- bn/indic_paraphrase-validation.parquet +3 -0
- data/.gitattributes +0 -22
- data/ml_IndicParaphrase_v1.0.zip +0 -3
- data/or_IndicParaphrase_v1.0.zip +0 -3
- data/pa_IndicParaphrase_v1.0.zip +0 -3
- data/ta_IndicParaphrase_v1.0.zip +0 -3
- data/te_IndicParaphrase_v1.0.zip +0 -3
- gu/indic_paraphrase-test.parquet +3 -0
- gu/indic_paraphrase-train.parquet +3 -0
- gu/indic_paraphrase-validation.parquet +3 -0
- hi/indic_paraphrase-test.parquet +3 -0
- data/hi_IndicParaphrase_v1.0.zip → hi/indic_paraphrase-train-00000-of-00002.parquet +2 -2
- hi/indic_paraphrase-train-00001-of-00002.parquet +3 -0
- hi/indic_paraphrase-validation.parquet +3 -0
- kn/indic_paraphrase-test.parquet +3 -0
- kn/indic_paraphrase-train.parquet +3 -0
- kn/indic_paraphrase-validation.parquet +3 -0
- ml/indic_paraphrase-test.parquet +3 -0
- ml/indic_paraphrase-train-00000-of-00002.parquet +3 -0
- ml/indic_paraphrase-train-00001-of-00002.parquet +3 -0
- ml/indic_paraphrase-validation.parquet +3 -0
- mr/indic_paraphrase-test.parquet +3 -0
- mr/indic_paraphrase-train.parquet +3 -0
- mr/indic_paraphrase-validation.parquet +3 -0
- or/indic_paraphrase-test.parquet +3 -0
- or/indic_paraphrase-train.parquet +3 -0
- or/indic_paraphrase-validation.parquet +3 -0
- pa/indic_paraphrase-test.parquet +3 -0
- pa/indic_paraphrase-train.parquet +3 -0
- pa/indic_paraphrase-validation.parquet +3 -0
- ta/indic_paraphrase-test.parquet +3 -0
- ta/indic_paraphrase-train.parquet +3 -0
- ta/indic_paraphrase-validation.parquet +3 -0
- te/indic_paraphrase-test.parquet +3 -0
- te/indic_paraphrase-train.parquet +3 -0
- te/indic_paraphrase-validation.parquet +3 -0
IndicParaphrase.py
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import json
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import os
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import datasets
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_CITATION = """\
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@inproceedings{Kumar2022IndicNLGSM,
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title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages},
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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},
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year={2022},
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url = "https://arxiv.org/abs/2203.05437"
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}
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"""
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_DESCRIPTION = """\
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This is the paraphrasing dataset released as part of IndicNLG Suite. Each
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input is paired with up to 5 references. We create this dataset in eleven
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languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total
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size of the dataset is 5.57M.
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"""
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_HOMEPAGE = "https://indicnlp.ai4bharat.org/indicnlg-suite"
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_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"
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_URL = "https://huggingface.co/datasets/ai4bharat/IndicParaphrase/resolve/main/data/{}_IndicParaphrase_v{}.zip"
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_LANGUAGES = [
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"as",
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"bn",
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"gu",
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"hi",
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"kn",
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"ml",
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"mr",
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"or",
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"pa",
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"ta",
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"te"
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]
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class IndicParaphrase(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="{}".format(lang),
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version=datasets.Version("1.0.0")
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)
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for lang in _LANGUAGES
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"pivot": datasets.Value("string"),
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"input": datasets.Value("string"),
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"target": datasets.Value("string"),
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"references": [datasets.Value("string")]
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}
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),
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supervised_keys=None,
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homepage=_HOMEPAGE,
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citation=_CITATION,
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license=_LICENSE,
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version=self.VERSION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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lang = str(self.config.name)
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url = _URL.format(lang, self.VERSION.version_str[:-2])
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data_dir = dl_manager.download_and_extract(url)
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if lang == 'as' :
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "test_" + lang + ".jsonl"),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "dev_" + lang + ".jsonl"),
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},
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),
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]
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else :
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "train_" + lang + ".jsonl"),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "test_" + lang + ".jsonl"),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepath": os.path.join(data_dir, "dev_" + lang + ".jsonl"),
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},
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),
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]
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def _generate_examples(self, filepath):
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"""Yields examples as (key, example) tuples."""
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with open(filepath, encoding="utf-8") as f:
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for idx_, row in enumerate(f):
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data = json.loads(row)
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yield idx_, {
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"id": data["id"],
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"pivot": data["pivot"],
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"input": data["input"],
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"target": data["target"],
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"references": data["references"]
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}
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README.md
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---
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annotations_creators:
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- no-annotation
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language_creators:
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- found
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language:
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- as
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- bn
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- gu
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- hi
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- kn
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- ml
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- mr
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- or
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- pa
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- ta
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- te
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license:
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- cc-by-nc-4.0
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multilinguality:
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- multilingual
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pretty_name: IndicParaphrase
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size_categories:
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- 1M<n<10M
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source_datasets:
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- original
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task_categories:
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- conditional-text-generation
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task_ids:
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- conditional-text-generation-other-paraphrase-generation
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---
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# Dataset Card for "IndicParaphrase"
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## Table of Contents
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- [Dataset Card Creation Guide](#dataset-card-creation-guide)
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- [Table of Contents](#table-of-contents)
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits](#data-splits)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
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- [Who are the source language producers?](#who-are-the-source-language-producers)
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- [Annotations](#annotations)
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- [Annotation process](#annotation-process)
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- [Who are the annotators?](#who-are-the-annotators)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## Dataset Description
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- **Homepage:** https://indicnlp.ai4bharat.org/indicnlg-suite
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- **Paper:** [IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages](https://arxiv.org/abs/2203.05437)
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- **Point of Contact:**
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### Dataset Summary
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IndicParaphrase is the paraphrasing dataset released as part of IndicNLG Suite. Each
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input is paired with up to 5 references. We create this dataset in eleven
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languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total
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size of the dataset is 5.57M.
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### Supported Tasks and Leaderboards
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**Tasks:** Paraphrase generation
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**Leaderboards:** Currently there is no Leaderboard for this dataset.
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### Languages
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- `Assamese (as)`
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- `Bengali (bn)`
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- `Gujarati (gu)`
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- `Kannada (kn)`
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- `Hindi (hi)`
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- `Malayalam (ml)`
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- `Marathi (mr)`
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- `Oriya (or)`
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- `Punjabi (pa)`
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- `Tamil (ta)`
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- `Telugu (te)`
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## Dataset Structure
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### Data Instances
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One example from the `hi` dataset is given below in JSON format.
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```
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{
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'id': '1',
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'input': 'निजी क्षेत्र में प्रदेश की 75 प्रतिशत नौकरियां हरियाणा के युवाओं के लिए आरक्षित की जाएगी।',
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'references': ['प्रदेश के युवाओं को निजी उद्योगों में 75 प्रतिशत आरक्षण देंगे।',
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'युवाओं के लिए हरियाणा की सभी प्राइवेट नौकरियों में 75 प्रतिशत आरक्षण लागू किया जाएगा।',
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'निजी क्षेत्र में 75 प्रतिशत आरक्षित लागू कर प्रदेश के युवाओं का रोजगार सुनिश्चत किया जाएगा।',
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'प्राईवेट कम्पनियों में हरियाणा के नौजवानों को 75 प्रतिशत नौकरियां में आरक्षित की जाएगी।',
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'प्रदेश की प्राइवेट फैक्टरियों में 75 फीसदी रोजगार हरियाणा के युवाओं के लिए आरक्षित किए जाएंगे।'],
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'target': 'प्रदेश के युवाओं को निजी उद्योगों में 75 प्रतिशत आरक्षण देंगे।'
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}
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```
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### Data Fields
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- `id (string)`: Unique identifier.
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- `pivot (string)`: English sentence used as the pivot
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- `input (string)`: Input sentence
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- `references (list of strings)`: Paraphrases of `input`, ordered according to the least n-gram overlap
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- `target (string)`: The first reference (most dissimilar paraphrase)
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### Data Splits
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We first select 10K instances each for the validation and test and put remaining in the training dataset. `Assamese (as)`, due to its low-resource nature, could only be split into validation and test sets with 4,420 examples each.
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Individual dataset with train-dev-test example counts are given below:
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Language | ISO 639-1 Code |Train | Dev | Test |
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--------------|----------------|-------|-----|------|
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Assamese | as | - | 4,420 | 4,420 |
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Bengali | bn | 890,445 | 10,000 | 10,000 |
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Gujarati | gu | 379,202 | 10,000 | 10,000 |
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Hindi | hi | 929,507 | 10,000 | 10,000 |
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Kannada | kn | 522,148 | 10,000 | 10,000 |
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Malayalam | ml |761,933 | 10,000 | 10,000 |
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Marathi | mr |406,003 | 10,000 | 10,000 |
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Oriya | or | 105,970 | 10,000 | 10,000 |
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Punjabi | pa | 266,704 | 10,000 | 10,000 |
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Tamil | ta | 497,798 | 10,000 | 10,000 |
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Telugu | te | 596,283 | 10,000 | 10,000 |
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## Dataset Creation
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### Curation Rationale
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[More information needed]
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### Source Data
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[Samanantar dataset](https://indicnlp.ai4bharat.org/samanantar/)
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#### Initial Data Collection and Normalization
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[Detailed in the paper](https://arxiv.org/abs/2203.05437)
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#### Who are the source language producers?
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[Detailed in the paper](https://arxiv.org/abs/2203.05437)
|
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|
165 |
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|
166 |
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### Annotations
|
167 |
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[More information needed]
|
168 |
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#### Annotation process
|
169 |
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[More information needed]
|
170 |
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|
171 |
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#### Who are the annotators?
|
172 |
-
|
173 |
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[More information needed]
|
174 |
-
|
175 |
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### Personal and Sensitive Information
|
176 |
-
|
177 |
-
[More information needed]
|
178 |
-
|
179 |
-
## Considerations for Using the Data
|
180 |
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|
181 |
-
### Social Impact of Dataset
|
182 |
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|
183 |
-
[More information needed]
|
184 |
-
|
185 |
-
### Discussion of Biases
|
186 |
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|
187 |
-
[More information needed]
|
188 |
-
|
189 |
-
### Other Known Limitations
|
190 |
-
|
191 |
-
[More information needed]
|
192 |
-
|
193 |
-
## Additional Information
|
194 |
-
|
195 |
-
### Dataset Curators
|
196 |
-
|
197 |
-
[More information needed]
|
198 |
-
|
199 |
-
### Licensing Information
|
200 |
-
|
201 |
-
Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/). Copyright of the dataset contents belongs to the original copyright holders.
|
202 |
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### Citation Information
|
203 |
-
|
204 |
-
If you use any of the datasets, models or code modules, please cite the following paper:
|
205 |
-
```
|
206 |
-
@inproceedings{Kumar2022IndicNLGSM,
|
207 |
-
title={IndicNLG Suite: Multilingual Datasets for Diverse NLG Tasks in Indic Languages},
|
208 |
-
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},
|
209 |
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year={2022},
|
210 |
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url = "https://arxiv.org/abs/2203.05437"
|
211 |
-
}
|
212 |
-
```
|
213 |
-
|
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-
|
215 |
-
### Contributions
|
216 |
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