Add task categories, paper link, and dataset details
#2
by nielsr HF Staff - opened
README.md
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license: apache-2.0
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pretty_name:
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---
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@misc{shuvo2026politesurfacewrongpractice,
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title={Polite on the Surface, Wrong in Practice: A Curated Dataset for Fixing Honorific Failures in Multilingual Bangla Generation},
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author={Md. Asaduzzaman Shuvo and Mahedi Hasan and Md. Tashin Parvez and Azizul Haque Noman and Md. Shafayet Hossain Ovi},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2605.22487},
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}
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------------------------------------------------
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from datasets import load_dataset
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ds = load_dataset("mdshuvo25/BLADE")
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license: apache-2.0
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pretty_name: BLADE
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task_categories:
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- text-generation
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language:
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- bn
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tags:
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- bangla
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- bengali
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- instruction-tuning
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---
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# BLADE: Bangla Application and Dialogue Generation Dataset
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This repository contains the BLADE (BangLa Application and DialoguE generation) dataset introduced in the paper [Polite on the Surface, Broken in Practice: A Curated Dataset for Fixing Generation and Register Failures in Low-Resource Bangla Text Generation](https://huggingface.co/papers/2605.22487).
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GitHub Repository: [Bangla_Application_LLM](https://github.com/ashuvo25/Bangla_Application_LLM)
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## Dataset Summary
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**BLADE** (BangLa Application and DialoguE generation) is a culturally aligned instruction-tuning dataset comprising **4,196 meticulously curated interaction pairs** in Bengali. It is designed to help train and evaluate language models for generating formal correspondence (such as applications and letters) and dialogues in Bengali, addressing the pragmatic gap and honorific inconsistencies in low-resource Bangla text generation.
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### Dataset at a Glance
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- **Total Samples**: 4,196 prompt-response pairs
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- **Unique Topics**: 2,008 distinct subjects covering a wide variety of formal letters
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- **Language**: Bengali/Bangla
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- **Average Prompt Length**: 8 tokens
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- **Average Response Length**: 1,340 tokens
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- **Maximum Sequence Length**: 1,942 tokens
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The dataset covers a diverse range of topics and recipients, including school headmasters, company managers, and government officials, making it a valuable resource for developing language models capable of understanding the nuances of formal Bengali writing.
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## Sample Usage
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You can load this dataset using the Hugging Face `datasets` library:
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```python
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from datasets import load_dataset
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ds = load_dataset("mdshuvo25/BLADE")
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```
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## Citation
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If you use this dataset or paper, please cite:
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```bibtex
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@misc{shuvo2026politesurfacewrongpractice,
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title={Polite on the Surface, Wrong in Practice: A Curated Dataset for Fixing Honorific Failures in Multilingual Bangla Generation},
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author={Md. Asaduzzaman Shuvo and Mahedi Hasan and Md. Tashin Parvez and Azizul Haque Noman and Md. Shafayet Hossain Ovi},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2605.22487},
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}
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```
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