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---
language:
- ar
license: apache-2.0
task_categories:
- multiple-choice
- text-classification
pretty_name: Sentiment Analysis MCQ Evaluation Dataset
tags:
- sentiment-analysis
- mcq
- financial
- arabic
- evaluation
- benchmark
---
# Sentiment Analysis MCQ Evaluation Dataset
Validation and test splits for financial sentiment analysis in MCQ format.
## Dataset Structure
- **Format**: Multiple choice questions
- **Language**: Arabic
- **Domain**: Financial reports
- **Task**: Sentiment classification
- **Validation**: 20 examples
- **Test**: 20 examples
## Fields
- `id`: Unique identifier
- `query`: Full MCQ prompt
- `answer`: Correct answer letter
- `text`: Question text
- `choices`: Answer options [a, b, c]
- `gold`: Correct answer index
- `category`: Report category
- `original_sentiment`: Ground truth sentiment
## Answer Mapping
- a) positive - gold: 0
- b) negative - gold: 1
- c) neutral - gold: 2
## Usage
```python
from datasets import load_dataset
dataset = load_dataset("SahmBenchmark/Sentiment_Analysis_MCQ_eval")
test_data = dataset['test']
for example in test_data:
print(f"Question: {example['text']}")
print(f"Choices: {example['choices']}")
print(f"Correct: {example['answer']} (index: {example['gold']})")
```
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