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Dataset Card for "IndicSentenceSummarization"

Dataset Summary

IndicSentenceSummarization is the sentence summarization dataset released as part of IndicNLG Suite. Each input sentence is paired with an output as summary. We create this dataset in eleven languages including as, bn, gu, hi, kn, ml, mr, or, pa, ta, te. The total size of the dataset is 431K.

Supported Tasks and Leaderboards

Tasks: Sentence Summarization

Leaderboards: Currently there is no Leaderboard for this dataset.

Languages

  • Assamese (as)
  • Bengali (bn)
  • Gujarati (gu)
  • Kannada (kn)
  • Hindi (hi)
  • Malayalam (ml)
  • Marathi (mr)
  • Oriya (or)
  • Punjabi (pa)
  • Tamil (ta)
  • Telugu (te)

Dataset Structure

Data Instances

One random example from the hi dataset is given below in JSON format.

{'id': '5',
 'input': 'जम्मू एवं कश्मीर के अनंतनाग जिले में शनिवार को सुरक्षाबलों के साथ मुठभेड़ में दो आतंकवादियों को मार गिराया गया।',
 'target': 'जम्मू-कश्मीर : सुरक्षाबलों के साथ मुठभेड़ में 2 आतंकवादी ढेर',
 'url': 'https://www.indiatv.in/india/national-jammu-kashmir-two-millitant-killed-in-encounter-with-security-forces-574529'
}

Data Fields

  • id (string): Unique identifier.
  • input (string): Input sentence.
  • target (strings): Output summary.
  • url (string): Source web link of the sentence.

Data Splits

Here is the number of samples in each split for all the languages.

Language ISO 639-1 Code Train Dev Test
Assamese as 10,812 5,232 5,452
Bengali bn 17,035 2,355 2,384
Gujarati gu 54,788 8,720 8,460
Hindi hi 78,876 16,935 16,835
Kannada kn 61,220 9,024 1,485
Malayalam ml 2,855 1,520 1,580
Marathi mr 27,066 3,249 3,309
Oriya or 12,065 1,539 1,440
Punjabi pa 31,630 4,004 3,967
Tamil ta 23,098 2,874 2,948
Telugu te 7,119 878 862

Dataset Creation

Curation Rationale

Detailed in the paper

Source Data

It is a modified subset of IndicHeadlineGeneration dataset.

Initial Data Collection and Normalization

Detailed in the paper

Who are the source language producers?

Detailed in the paper

Annotations

[More information needed]

Annotation process

[More information needed]

Who are the annotators?

[More information needed]

Personal and Sensitive Information

[More information needed]

Considerations for Using the Data

Social Impact of Dataset

[More information needed]

Discussion of Biases

[More information needed]

Other Known Limitations

[More information needed]

Additional Information

Dataset Curators

[More information needed]

Licensing Information

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). Copyright of the dataset contents belongs to the original copyright holders.

Citation Information

If you use any of the datasets, models or code modules, please cite the following paper:

@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",     

Contributions

Detailed in the paper

Models trained or fine-tuned on ai4bharat/IndicSentenceSummarization