---
language:
- bho
- en
- bh
license: apache-2.0
tags:
- sentiment-analysis
- text-classification
- bhojpuri
- devanagari
- low-resource-nlp
- cross-lingual-transfer

---

# 🚀 Bhojpuri Behavioral Corpus (Phase 2: Engineered Refinement)

![Language](https://img.shields.io/badge/Language-Bhojpuri-blue)
![Task](https://img.shields.io/badge/Task-Sentiment_Analysis-green)
![Size](https://img.shields.io/badge/Size-68.8K_Rows-orange)
![Format](https://img.shields.io/badge/Format-CSV-lightgrey)

**⚠️ NOTICE: Phase 2 Refinement**
*This repository contains the Phase 2 Engineered Refinement. This Phase 2 is automatically refined specifically to prevent class collapse during fine-tuning.*

## 📌 Executive Summary
The **Bhojpuri Behavioral Corpus (Phase 2)** is a 68,822-row, rigidly balanced dataset engineered to solve the inherent instability of low-resource language fine-tuning. Moving beyond noisy web-scraped corpora, this dataset provides a sterile, perfectly stratified environment (1:1:1 ratio) to teach Large Language Models precise pragmatic boundaries and cross-lingual semantic alignment across diverse domains (Science, Agriculture, Environment, General).

## 🧠 Architectural Innovations

### 1. Mathematical Stratification (1:1:1)
To prevent the majority-class collapse common in naturalistic datasets, this corpus is artificially balanced to an exact 1:1:1 ratio:
* **Positive:** 22,940 samples
* **Negative:** 22,940 samples
* **Neutral:** 22,942 samples
This ensures the model's loss function penalizes misclassification equally across all sentiment vectors.

### 2. Cross-Lingual Alignment via Anchored Translation
A subset of the corpus utilizes an **Anchored Translation** format. Complex technical terms (e.g., *'आइसोटोप'* / Isotope) are paired with their bracketed English equivalents directly within the Bhojpuri string. This is a deliberate architectural choice to provide an explicit semantic alignment signal, bridging the gap between high-resource English representations and low-resource Bhojpuri vernacular.

### 3. Contemporary Lexical Borrowing
The dataset intentionally preserves English loanwords and technical transliterations within the Devanagari script (e.g., *'मशीन'* / Machine). Rather than artificially sanitizing the corpus to an archaic standard, this reflects authentic, contemporary Bhojpuri morphology.

## 📊 Dataset Schema
* `id`: Unique identifier.
* `text`: The Bhojpuri utterance (Devanagari script).
* `english_tr`: High-fidelity semantic English translation.
* `label`: Primary sentiment (positive, negative, neutral).
* `domain` / `sub_domain`: Context of the utterance (e.g., agriculture, science).


## ⚙️ Intended Use & Limitations
* **Best For:** Parameter-efficient fine-tuning (LoRA/QLoRA), Teacher-model initialization, and cross-lingual representation alignment.
* **Limitations:** Because the sentiment distribution is artificially balanced (33% per class), models trained exclusively on this dataset may over-predict positive/negative sentiments in real-world, highly neutral environments without threshold calibration or Adaptive Knowledge Distillation (AdaptKD).

## 📝 Citation
If you use this dataset in your research, please cite the accompanying paper:
```bibtex
@article{prasad2026bhojpuri,
  title={abhiprd20/Bhojpuri-Behavioral-Corpus-8K},
  author={Prasad, Abhimanyu},
  year={2026},
  
```