DatarrX/pali-myanmar-dictionary-corpus

Pali-Myanmar Dictionary Corpus (Instruction-Ready)

Dataset Summary

The Pali-Myanmar Dictionary Corpus is an extensive, highly structured linguistic resource containing 306,063 entries. It serves as a comprehensive bridge between the ancient Pali language and Modern Myanmar (Burmese). This dataset is specifically designed for Natural Language Processing (NLP), Machine Translation, and Large Language Model (LLM) instruction tuning.

Each record is parsed from original sources into a structured format that includes grammatical categories, etymological roots, and clean definitions.

Project Credits & Governance

• Organization: DatarrX
• Curated by: Khant Sint Heinn (Kalix Louis)
• Source Data: Derived from pndaza/tipitaka-pali
• License: MIT License

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Understanding the Data (For Non-Religious Researchers)

Pali is a classical Indo-Aryan language, famous as the language of the Buddhist scriptures (Tipitaka). However, this dataset is more than a religious text; it is a Classical-to-Modern Language Mapping Corpus.

For AI researchers, this dataset is valuable for:

1. Morphological Analysis: Pali has a complex inflectional system similar to Latin or Sanskrit.
2. Low-Resource NLP: Providing high-quality supervised data for the Myanmar script.
3. Semantic Mapping: Understanding how ancient philosophical concepts translate into modern legal and ethical Burmese terminology.

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Dataset Statistics

Metric	Value
Total Entries	306,063
Average Word Length	9.24 characters
Entries with Part of Speech (POS)	232,186 (75.8%)
Entries with Etymology	178,316 (58.2%)

Top 10 Part of Speech (POS) Distribution

POS Tag	Count	Percentage	Description
တိ	64,733	21.15%	Adjectives / Pronouns
န	41,840	13.67%	Neuter Nouns
ပု	37,432	12.23%	Masculine Nouns
ထီ	15,715	5.13%	Feminine Nouns
ပ	12,520	4.09%	Prefixes / Primary Roots
ကြိ	10,574	3.45%	Verbs

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Dataset Structure

The dataset follows an Instruction-Response format, making it compatible with modern LLM training (Supervised Fine-Tuning).

Data Fields

• word: The target Pali word.
• part_of_speech: Grammatical classification (Gender, Tense, etc.).
• etymology: The root origin of the word.
• definition: The modern Myanmar translation/definition.
• instruction: A natural language prompt for the AI.
• response: A human-like generated response combining grammar and definition.

Example Entry

{
  "word": "စက္ကဒဟ",
  "part_of_speech": "ပု",
  "etymology": "စက္က+ဒဟ",
  "definition": "စကြာရတနာဖြစ်ပေါ်ရာအရပ်။",
  "instruction": "Provide the definition and grammar for the Pali word: စက္ကဒဟ",
  "response": "စက္ကဒဟ (ပု) is defined as: စကြာရတနာဖြစ်ပေါ်ရာအရပ်။"
}

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Potential Applications

1. Instruction Tuning for LLMs: Fine-tuning models like Llama or Gemma to understand and explain Pali terms.
2. Machine Translation (MT): Creating a baseline vocabulary for Pali-to-Burmese translation systems.
3. Automatic POS Tagging: Using the 232k+ POS labels to train grammatical classifiers for the Myanmar script.
4. Digital Humanities: Researching the linguistic evolution and word-formation (etymology) of Pali words in the Myanmar context.

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Citation & Acknowledgments

If you use this corpus, please acknowledge the source and the developers:

Source Data: Pndaza (2024). Tipitaka Pali SQLite Database. Available at: https://github.com/pndaza/tipitaka-pali Curation: Khant Sint Heinn (Kalix Louis), DatarrX Organization (2026). Pali-Myanmar Dictionary Corpus.

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Contact

For inquiries regarding DatarrX's Myanmar NLP initiatives, please visit Hugging Face or our GitHub.

About the Author

Khant Sint Heinn, working under the name Kalix Louis, is a Machine Learning Engineer focused on Natural Language Processing (NLP), data foundations, and open-source AI development. His work is centered on improving support for the Burmese (Myanmar) language in modern AI systems by building high-quality datasets, practical tools, and scalable infrastructure for language technology.

He is currently the Lead Developer at DatarrX, where he develops data pipelines, manages large-scale data collection workflows, and helps create open-source resources for researchers, developers, and organizations. His experience includes data engineering, web scripting, dataset curation, and building systems that support real-world machine learning applications.

Khant Sint Heinn is especially interested in advancing low-resource languages and making AI more accessible to underrepresented communities. Through his open-source contributions, he works to strengthen the Burmese (Myanmar) tech ecosystem and provide reliable building blocks for future language models, search systems, and intelligent applications.

His goal is simple: to turn limited language resources into practical opportunities through clean data, useful tools, and community-driven innovation.

Connect with the Author:
GitHub | Hugging Face | Kaggle