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Datasets:
Boredoom17
/
Nepali-Flow-Formal

Tasks:
Text Generation
Text Classification
Other
Modalities:
Text
Languages:
Nepali
Size:
1M - 10M
Tags:
nepali
corpus
formal
news
devanagari
low-resource
License:
Dataset card Data Studio Files
xet
 Community
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Nepali-Flow-Formal / ATTRIBUTION.md
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Attribution & Data Sources

This corpus synthesizes Nepali text from multiple public and research sources. Proper attribution is critical for ethical research.

Primary Sources

1. IRIISNEPAL

  • Full Name: IIIiSNepal - Itihasa, Kalakaram, Sthanadarshan, Shikshhya, Nepali Text Dataset
  • Repository: https://github.com/bnltm/IIIiSNepal
  • Description: A large-scale curated dataset of Nepali articles covering historical, cultural, educational, and geographical topics.
  • License: MIT
  • Citation:
    Yadav, Kanchan, et al. "IIIiSNepal: Large-Scale Annotated Nepali Text Dataset."
Proceedings of the 2nd Workshop on NLP for Under-resourced Languages, 2020.
  • Rows in Corpus: 6,087,439
  • Applies to: nepali-formal-corpus, nepali-text-corpus

2. Nepali Wikipedia

  • Source: Nepali Wikipedia Dump (latest as of corpus creation)
  • URL: https://dumps.wikimedia.org/newiki/
  • Description: Extracted sentences from Nepali Wikipedia articles across all topics and domains.
  • License: CC BY-SA 4.0
  • Rows in Corpus: 291,767
  • Applies to: nepali-formal-corpus, nepali-text-corpus

3. Nepali News Source Crawls

4. YouTube Comments (Public)

  • Source: YouTube Data API v3 (public comment threads)
  • Description: Colloquial, conversational Nepali as used in social discussions, reviews, and community comments.
  • License: CC BY 4.0 (standard YouTube comment license)
  • Rows in Corpus: 431,648
  • Applies to: nepali-colloquial-corpus, roman-nepali-corpus, nepali-text-corpus

Contributor Acknowledgments

  • IRIISNEPAL Curators: Kanchan Yadav, Sharad Khatiwada, and the broader NLP community contributors
  • Wikipedia Contributors: Nepali Wikipedia editor community
  • News Publishers: Journalists and editorial teams at Nepali news outlets
  • YouTube Commenters: Anonymous community members sharing public discourse

Data Cleaning & Processing

All source data underwent standardization and validation:

  • Text normalization (whitespace, special characters)
  • Duplicate removal at the corpus level
  • Malformed record filtering
  • Length-based quality thresholds (minimum 5 words for formal text)
  • Script detection and classification (Devanagari, Latin, mixed)

See DATA_PROCESSING.md for technical details.

Responsible Use

  • Academic Research: Encouraged under fair-use principles
  • Commercial Products: Requires license-aware filtering and potential publisher permissions
  • Media Attribution: When publishing results, recommend citing source origins
  • Ethical Concerns: This corpus includes conversational YouTube content with occasional vulgar or offensive language; filter rows before public-facing applications

Questions or Corrections?

For attribution corrections or to report improper use, contact the dataset maintainers through the Hugging Face dataset page.

Compiled: April 2, 2026
Corpus Version: 1.0