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Salman95s
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Balochi-Multilingual-dataset

Tasks:
Text Classification
Token Classification
Translation
Modalities:
Text
Formats:
json
Languages:
Baluchi
Urdu
Persian
Size:
< 1K
Tags:
dataset
balochi
baluchi
persian
urdu
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pandas
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Balochi-Multilingual-dataset / README.md
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metadata
license: cc-by-sa-4.0
task_categories:
  - text-classification
  - token-classification
  - translation
  - text2text-generation
  - question-answering
tags:
  - dataset
  - balochi
  - baluchi
  - persian
  - urdu
size_categories:
  - 100K<n<1M
language:
  - bal
  - ur
  - fa
  - en

Balochi Language Dataset

Overview

This dataset is a comprehensive resource for training large language models (LLMs) in the Balochi language. It is designed to go beyond basic translation tasks, supporting fully generative text and conversational AI capabilities in Balochi.

The dataset includes monolingual Balochi text, multilingual translation corpora, and various conversational and domain-specific texts, enabling diverse use cases such as:

  • Generative AI: Building chatbots and generative text systems in Balochi.
  • Multilingual Translation: Translating between Balochi and other languages like English, Urdu, and Persian.
  • Cultural Insights: Providing context for cultural and historical texts.
  • Domain-Specific Applications: Technical, educational, and assistant-oriented tasks.

Key Features

  • Languages: Balochi, English, Urdu, Persian.

  • Domains:

    • General conversation
    • Literature
    • News
    • Academic texts
    • Technical content
    • Cultural and historical narratives
    • Travel and educational materials
    • Assistant and chat scenarios

  • Dataset Size:

    • Monolingual and multilingual pairs totaling tens of thousands of records.
    • Includes conversational samples, professional scenarios, and technical terminologies.

Dataset Highlights

Monolingual Data

  • Focused on Balochi texts from cultural, historical, and conversational contexts.
  • Contains cleaned and formatted versions for model training.

Multilingual Translation Data

  • Balochi-English: General and technical translations.
  • Balochi-Urdu: News and conversational translations.
  • Balochi-Persian: Literary and historical translations.

Conversational Samples

Includes a variety of real-world scenarios:

  • Daily interactions (e.g., greetings, family discussions).
  • Professional settings (e.g., interviews, meetings).
  • Educational contexts (e.g., questions in class).
  • Travel scenarios (e.g., at airports, booking hotels).

Technical Terminology

Covers domains like:

  • Computing
  • Medicine
  • Physics
  • Internet technology

Bias, Risks, and Limitations

This dataset has been curated with care to include diverse and representative content. However, users should be aware of the following:

  1. Bias in Data:

    • Despite efforts to ensure diversity, some biases inherent in the source material may persist.
    • Certain dialects or regional variations of Balochi may be underrepresented.

  2. Potential Offensive Content:

    • While the data has been cleaned, there is a possibility of inadvertent inclusion of sensitive or offensive terms.
    • Users should implement post-processing and filtering mechanisms where necessary.

  3. Translation Limitations:

    • Translations are not guaranteed to be perfect and may require human review in sensitive or critical applications.

By using this dataset, you acknowledge these potential limitations and accept responsibility for its application.

Balochi Language Dataset: Data Sources

The Balochi dataset was developed using diverse and high-quality sources to ensure broad linguistic and contextual coverage. Below is a list of the primary sources utilized in the dataset creation, along with their respective credits:

Data Sources

  1. GlotSparse:

    • A multilingual dataset designed for sparse language modeling. Contains Balochi text extracted from various web sources, contributing valuable monolingual data.

  2. GlotCC-V1:

    • A dataset focused on creating multilingual corpora from Common Crawl. This source provided extensive Balochi text with a wide range of domains.

  3. URL-NLP Repository:

    • A collection of linguistic datasets and tools by Google Research. The Balochi-specific data from this repository enhanced the linguistic diversity of the dataset.

  4. PanLex Meanings: Balochi:

    • A curated dataset providing word meanings and semantic pairs in Balochi, supporting vocabulary development and semantic understanding.

  5. PanLex Meanings:

    • A multilingual dataset of word meanings across languages. The Balochi subset enriched the dataset with valuable translation pairs and lexical entries.

  6. Goldfish Project:

    • A project containing structured linguistic data. It contributed additional insights and potential cross-lingual information for this dataset.

Additional Resources and Inspirations

  1. The Balochi Language Project (Uppsala University):

    • A research project focusing on the linguistic features, history, and preservation of the Balochi language. It served as a key inspiration for the dataset's design and goals.

  2. Balochi Dictionary on Webonary:

    • A comprehensive online dictionary for the Balochi language. This resource supported lexical enrichment and linguistic reference.

  3. MLOps: Custom Balochi Tokenizer:

    • A detailed guide on training a custom tokenizer for Balochi. While not directly used in this dataset, it offers valuable insights that could significantly enhance the basic tokenizer currently employed, providing a pathway for improved tokenization and language model performance in future Balochi projects.

Acknowledgments

We express our gratitude to the creators and maintainers of these datasets and repositories. Their work has been instrumental in building this resource for advancing Balochi language modeling and AI applications.

If you are the creator of one of these datasets and have specific licensing or attribution requirements, feel free to reach out for further clarification or updates.

Licensing

The dataset is released under the CC-BY-SA 4.0 license. This means you can use, share, and modify it, provided proper attribution is given.

For further details or contributions, feel free to reach out or submit issues to the project repository.