Upload SentimentPro-Dataset with quality metrics

README.md

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+---
+license: apache-2.0
+task_categories:
+- text-classification
+- question-answering
+---
+# SentimentPro Dataset
+<!-- markdownlint-disable first-line-h1 -->
+<!-- markdownlint-disable html -->
+<!-- markdownlint-disable no-duplicate-header -->
+
+<div align="center">
+  <img src="figures/fig1.png" width="60%" alt="SentimentPro Dataset" />
+</div>
+<hr>
+
+<div align="center" style="line-height: 1;">
+  <a href="LICENSE" style="margin: 2px;">
+    <img alt="License" src="figures/fig2.png" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+
+## 1. Introduction
+
+SentimentPro is a comprehensive multilingual sentiment analysis dataset designed for training and evaluating sentiment classification models. The dataset includes labeled examples from multiple domains including social media, product reviews, and news articles.
+
+<p align="center">
+  <img width="80%" src="figures/fig3.png">
+</p>
+
+The dataset was curated using advanced filtering techniques to ensure high quality annotations. Each example has been validated by at least 3 independent annotators with high inter-annotator agreement scores.
+
+This release includes multiple data splits with varying quality characteristics to support research in data quality assessment and curriculum learning.
+
+## 2. Quality Metrics
+
+### Comprehensive Quality Assessment
+
+<div align="center">
+
+| | Quality Metric | Split_v1 | Split_v3 | Split_v5 | SentimentPro-Best |
+|---|---|---|---|---|---|
+| **Data Integrity** | Completeness | 0.820 | 0.855 | 0.870 | 0.907 |
+| | Consistency | 0.785 | 0.812 | 0.835 | 0.892 |
+| | Accuracy | 0.910 | 0.925 | 0.940 | 0.977 |
+| **Temporal Quality** | Timeliness | 0.750 | 0.780 | 0.805 | 0.868 |
+| | Uniqueness | 0.890 | 0.915 | 0.930 | 0.968 |
+| | Validity | 0.865 | 0.880 | 0.900 | 0.950 |
+| **Content Quality** | Coverage | 0.720 | 0.755 | 0.780 | 0.843 |
+| | Diversity | 0.695 | 0.730 | 0.760 | 0.835 |
+| | Relevance | 0.840 | 0.865 | 0.885 | 0.935 |
+| | Balance | 0.775 | 0.805 | 0.830 | 0.892 |
+| **Technical Quality** | Noise Level | 0.680 | 0.720 | 0.755 | 0.843 |
+| | Label Quality | 0.905 | 0.920 | 0.935 | 0.973 |
+| | Text Quality | 0.830 | 0.855 | 0.875 | 0.925 |
+| | Format Compliance | 0.945 | 0.960 | 0.970 | 0.995 |
+| | Schema Validation | 0.990 | 0.992 | 0.995 | 0.999 |
+
+</div>
+
+### Overall Quality Summary
+The SentimentPro dataset demonstrates high quality across all evaluated dimensions, with particularly strong results in label accuracy and format compliance.
+
+## 3. Dataset Structure
+
+```
+data/
+├── train.jsonl      # Training examples
+├── validation.jsonl # Validation examples
+└── test.jsonl       # Test examples (labels withheld)
+```
+
+Each example follows this schema:
+```json
+{
+    "id": "unique_identifier",
+    "text": "The input text content",
+    "label": "positive|negative|neutral",
+    "domain": "social_media|reviews|news",
+    "language": "en|es|fr|de|zh"
+}
+```
+
+## 4. Usage
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("username/SentimentPro-Dataset")
+```
+
+## 5. License
+This dataset is licensed under the [Apache 2.0 License](LICENSE).
+
+## 6. Contact
+For questions or issues, please open an issue in this repository or contact data@sentimentpro.ai.

data.jsonl

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+{"id": "v10_001", "text": "Absolutely phenomenal!", "label": "positive", "domain": "reviews", "language": "en"}
+{"id": "v10_002", "text": "Total waste of time", "label": "negative", "domain": "social_media", "language": "en"}
+{"id": "v10_003", "text": "Mediocre at best", "label": "neutral", "domain": "reviews", "language": "en"}

metadata.json

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+{
+    "dataset_type": "sentiment_analysis",
+    "version": "v10",
+    "format": "jsonl",
+    "num_examples": 35000
+}