freococo/1_pattern_10Kplus_myanmar_sentences

🧠 1pattern10Kplusmyanmarsentences

A structured dataset of 11,452 Myanmar sentences generated from a single, powerful grammar pattern:

📌 Pattern:

`Verb လည်း Verb တယ်။`

A natural way to express repetition, emphasis, or causal connection in Myanmar.

💡 About the Dataset

This dataset demonstrates how applying just one syntactic pattern to a curated verb list — combined with syllable-aware rules — can produce a high-quality corpus of over 10,000 valid Myanmar sentences.

Each sentence is:

• —Grammatically valid
• —Syllable-tokenized
• —Pattern-consistent
• —Cleaned and filtered

🔁 Pattern in Use

Examples:

• —ချစ်လည်း ချစ်တယ်။
• —ကစားလည်း ကစားတယ်။
• —ကံကြီးလည်း ထိုက်တယ်။
• —ခေါင်းချင်းဆိုင်လည်း တိုက်တယ်။

📏 Rules in Use

📁 Dataset Format

Each row in the CSV contains:

Example:

my_sentence: ကလည်း ကတယ်။
my_word: က
my_subword: ["က"]
subword_number: 1

🤯 Why It’s Special

	•	✅ Only one pattern → yet over 11,000 real Myanmar sentences
	•	✅ Rule logic scales across syllable complexity
	•	✅ Cleaned, structured, and easy to extend
	•	✅ Represents real grammar, not artificial templates

😅 Problems We Faced

We started with a large list of Myanmar verbs and applied a syllable-level tokenizer to break each verb into structured chunks. Based on syllable count, we applied one of six rules to generate sentences.

Challenges included:

	•	Unicode inconsistencies (e.g., ဥ် vs ဉ်, န့် vs န့်)
	•	Visually similar characters causing mis-splitting
	•	Manual review needed for edge cases
	•	Some grammatically valid outputs lacked semantic sense

🔮 Future Plans

This is just Pattern 1.

Coming soon: • မ V နဲ့။

We aim to build a full-scale, pattern-rich Myanmar corpus — one rule at a time.

⸻

🎯 Use Cases

• Fine-tune sentence generation models • Train grammar correction systems • Build linguistic datasets for Myanmar NLP • Teach Myanmar grammar through concrete patterns • Benchmark syllable tokenizers

⸻

🧪 Quality & Manual Review

Even though all sentences were generated using grammatical rules, not all combinations may sound natural or meaningful in everyday Myanmar.

📝 This dataset should be manually reviewed by native speakers to ensure each sentence:

	•	Sounds natural
	•	Makes semantic sense
	•	Feels appropriate for real-world use

That said — even if you:

	•	Remove awkward or illogical samples
	•	Filter or adjust by context
	•	Expand with more rules and patterns

➡️ You’ll still retain 10K+ high-quality, structured Myanmar sentences.

⚠️ Please don’t use this dataset blindly for production training without native review.

⸻

📜 License

MIT — free to use, adapt, remix, or improve. But give credit where it’s due 💛

⸻

🔗 Citation

@dataset{myanmar_verb_pattern_2025,
  title={1 Pattern 10K+ Myanmar Sentences},
  author={freococo},
  year={2025},
  url={https://huggingface.co/datasets/freococo/1_pattern_10Kplus_myanmar_sentences}
}