File size: 1,819 Bytes
d0e78c2 c79cffb 79bcaec c008563 79bcaec c008563 79bcaec c008563 79bcaec c008563 d0e78c2 c79cffb |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 |
---
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
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: original_split
dtype: string
- name: choices
sequence: string
- name: text
dtype: string
- name: answer
dtype: string
- name: original_sentiment
dtype: string
- name: query
dtype: string
- name: id
dtype: string
- name: gold
dtype: int64
- name: category
dtype: string
splits:
- name: test
num_bytes: 495875
num_examples: 80
download_size: 218370
dataset_size: 495875
---
# 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']})")
```
|