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: 4681603 | |
num_examples: 67349 | |
- name: validation | |
num_bytes: 106252 | |
num_examples: 872 | |
- name: test | |
num_bytes: 216640 | |
num_examples: 1821 | |
download_size: 3331058 | |
dataset_size: 5004495 | |
configs: | |
- config_name: default | |
data_files: | |
- split: train | |
path: data/train-* | |
- split: validation | |
path: data/validation-* | |
- split: test | |
path: data/test-* | |
# 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). The test set labels are hidden (-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. |