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Burmese Aspect-Based Sentiment Analysis (ABSA) Dataset
This dataset contains Burmese customer reviews annotated for two-stage Aspect-Based Sentiment Analysis (ABSA).
Dataset Subsets (Configurations)
This repository contains two subsets:
stage1(stage1_aspect_classification.csv): Multi-label aspect detection dataset containing 6 business aspects and an "All-Zero" baseline class (7,508 rows).stage2(stage2_sentiment_pairs.csv): Aspect-level sentiment classification pairs (Positive, Negative, Neutral).
Aspect Definitions (Stage 1)
product_or_service_quality: Product durability, food taste, design, cleanliness.fulfillment_and_speed: Delivery time, packaging, shipping speed.price_and_value: Value for money, discounts, price fairness.digital_experience: App/website usability, UI/UX, online payment systems.customer_support: Staff friendliness, responsiveness, helpline support.variety_and_availability: Stock availability, color/size options, menu choices.
Sentiment Classes (Stage 2)
PositiveNegativeNeutral
How to Load in Python
from datasets import load_dataset
REPO_ID = "Fixaro/burmese-aspect-based-sentiment"
# 1. Load Stage 1 (Aspect Detection)
dataset_stage1 = load_dataset(REPO_ID, "stage1")
print("Stage 1 Sample:", dataset_stage1['train'][0])
# 2. Load Stage 2 (Aspect Sentiment Analysis)
dataset_stage2 = load_dataset(REPO_ID, "stage2")
print("Stage 2 Sample:", dataset_stage2['train'][0])
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