--- annotations_creators: - crowdsourced language_creators: - found language: - en license: - unknown multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-classification task_ids: - sentiment-classification paperswithcode_id: sst pretty_name: Stanford Sentiment Treebank v2 dataset_info: features: - name: idx dtype: int32 - name: sentence dtype: string - name: label dtype: class_label: names: 0: negative 1: positive splits: - name: train num_bytes: 4690022 num_examples: 67349 - name: validation num_bytes: 106361 num_examples: 872 - name: test num_bytes: 216868 num_examples: 1821 download_size: 7439277 dataset_size: 5013251 --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://nlp.stanford.edu/sentiment/ - **Repository:** - **Paper:** [Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank](https://www.aclweb.org/anthology/D13-1170/) - **Leaderboard:** - **Point of Contact:** ### Dataset Summary The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language. The corpus is based on the dataset introduced by Pang and Lee (2005) and consists of 11,855 single sentences extracted from movie reviews. It was parsed with the Stanford parser and includes a total of 215,154 unique phrases from those parse trees, each annotated by 3 human judges. Binary classification experiments on full sentences (negative or somewhat negative vs somewhat positive or positive with neutral sentences discarded) refer to the dataset as SST-2 or SST binary. ### Supported Tasks and Leaderboards - `sentiment-classification` ### Languages The text in the dataset is in English (`en`). ## Dataset Structure ### Data Instances ``` {'idx': 0, 'sentence': 'hide new secretions from the parental units ', 'label': 0} ``` ### Data Fields - `idx`: Monotonically increasing index ID. - `sentence`: Complete sentence expressing an opinion about a film. - `label`: Sentiment of the opinion, either "negative" (0) or positive (1). ### Data Splits | | train | validation | test | |--------------------|---------:|-----------:|-----:| | Number of examples | 67349 | 872 | 1821 | ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? Rotten Tomatoes reviewers. ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Unknown. ### Citation Information ```bibtex @inproceedings{socher-etal-2013-recursive, title = "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank", author = "Socher, Richard and Perelygin, Alex and Wu, Jean and Chuang, Jason and Manning, Christopher D. and Ng, Andrew and Potts, Christopher", booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing", month = oct, year = "2013", address = "Seattle, Washington, USA", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/D13-1170", pages = "1631--1642", } ``` ### Contributions Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.