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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 | |
| 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']})") | |
| ``` | |