---
license: mit
task_categories:
  - text-generation
  - text-classification
language:
  - my
tags:
  - MyanmarSentences
  - Burmese
  - BurmeseSentences
---

# 🧠 1_pattern_10Kplus_myanmar_sentences

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

| Syllable Count | Rule Name         | Sentence Format                            | # of Sentences Generated |
|----------------|-------------------|---------------------------------------------|---------------------------|
| 1              | Rule_1_Syllable   | `Aလည်း Aတယ်။`                              | 1                         |
| 2              | Rule_2_Syllable   | `Aလည်း Bတယ်။` and `Aလည်း ABတယ်။`          | 2 (dual sentences)        |
| 3              | Rule_3_Syllable   | `ABလည်း Cတယ်။`                             | 1                         |
| 4              | Rule_4_Syllable   | `ABCလည်း Dတယ်။`                            | 1                         |
| 5+             | Rule_{N}_Syllable | `ABCD...လည်း Zတယ်။`                        | 1 per item                |

---

## 📁 Dataset Format

Each row in the CSV contains:

| Column           | Description                                      |
|------------------|--------------------------------------------------|
| `my_sentence`    | The full generated Myanmar sentence              |
| `my_word`        | The original verb the sentence is based on       |
| `my_subword`     | List of syllable-level tokens (as a string list) |
| `subword_number` | Number of syllables in `my_word`                 |

**Example:**

```text
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}
}
```