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README.md

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+---
+# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
+# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
+{}
+---
+
+# Dataset Card for ReLi-SA
+
+## Dataset Description
+
+- **Homepage:** 
+- **Repository:** 
+- **Paper:** 
+- **Leaderboard:** 
+- **Point of Contact:** 
+
+### Dataset Summary
+
+ReLi-SA is a dataset created within the framework of the LEARN project "Semantic Annotators based on Active Learning," coordinated by Ruy Milidiú (Department of Informatics - PUC-Rio).  It consists of 1,600 book reviews manually annotated for the presence of opinions on the reviewed book and its polarity. 
+The dataset contains reviews in Brazilian Portuguese on books written by seven authors: Stephenie Meyer, Thalita Rebouças, Sidney Sheldon, Jorge Amado, George Orwell, José Saramago, and J.D. Salinger. The language used in the reviews varies from highly informal, with slang, abbreviations, neologisms, and emoticons, to more formal reviews with a more elaborate vocabulary.
+
+### Supported Tasks and Leaderboards
+
+- `sentiment-analysis`: The dataset can be used to train a model for sentiment analysis, which consists of classifying the sentiment expressed in a sentence as positive, negative, neutral, or mixed. Success on this task is typically measured by achieving a high [F1 score](https://huggingface.co/metrics/f1).
+
+### Languages
+
+This dataset is in Brazilian Portuguese (BCP-47 code: `pt-BR`).
+
+## Dataset Structure
+
+### Data Instances
+
+```json
+{
+  'source': 'ReLi-Orwell.txt',
+  'title': 'False',
+  'book': '1984',
+  'review_id': '0',
+  'score': 5.0,
+  'sentence_id': 102583,
+  'unique_review_id': 'ReLi-Orwell_1984_0',
+  'sentence': ' Um ótimo livro , além de ser um ótimo alerta para uma potencial distopia , em contraponto a utopia tão sonhada por os homens de o medievo e início de a modernidade .',
+  'label': 'positive'
+}
+```
+
+### Data Fields
+
+* `source`: The source file of the review.
+* `title`: A boolean field indicating whether the sentence is a review title (True) or not (False).
+* `book`: The book that the review is about.
+* `review_id`: The review ID within the source file.
+* `score`: The score the review attributes to the book.
+* `sentence_id`: The sequential ID of the sentence (can be used to sort the sentences within a review).
+* `unique_review_id`: A unique ID for the review a sentence belongs to.
+* `sentence`: The sentence for which the label indicates the sentiment.
+* `label`: The sentiment label, either `positive`, `neutral`, `negative`, or `mixed` if both positive and negative sentiment polarity tokens are found in the sentence.
+
+### Data Splits
+
+The dataset is divided into three splits:
+
+|            |  train  | validation |  test  |
+|------------|--------:|----------:|-------:|
+| Instances  |  7,875  |    1,348   | 3,288  |
+
+The splits are carefully made to avoid having reviews about a given author appear in more than one split.
+
+## Additional Information
+
+### Citation Information
+
+If you use this dataset in your work, please cite the following publication:\
+
+```bibtex
+@article{freitas2012vampiro,
+  title={Vampiro que brilha... r{\'a}! desafios na anota{\c{c}}ao de opiniao em um corpus de resenhas de livros},
+  author={Freitas, C. and Motta, E. and Milidi{\'u}, R. and C{\'e}sar, J.},
+  journal={Encontro de Ling{\'i}stica de corpus},
+  volume={11},
+  pages={3},
+  year={2012}
+}
+```
+
+### Contributions
+
+Thanks to [@ruanchaves](https://github.com/ruanchaves) for adding this dataset.