Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
sentiment-classification
Languages:
English
Size:
10K - 100K
License:
| 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. |