Dataset Card for [Dataset Name]

  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… See the full description on the dataset page: https://huggingface.co/datasets/stanfordnlp/sst2.

Binary Stanford Sentiment Treebank (SST2) is a binary version of SST and Movie Review dataset (the neutral class was removed), that is, the data was classified only into positive and negative classes.

The files:
texts.txt: Document set (text). One per line.
score.txt: Document class whose index is associated with texts.txt
split_

The Stanford Sentiment Treebank, the first corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language.

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.

STT-2 Spanish

  A Spanish translation (using EasyNMT) of the SST-2 Dataset





  For more information check the official Model Card

The Rendered SST2 dataset is a dataset released by OpenAI, that measures the optical character recognition capability of visual representations. It uses sentences from the Stanford Sentiment Treebank dataset and renders them into images, with black texts on a white background, in a 448×448 resolution.

SST-2 (Modified for LLaMA 1B)

This dataset is a modified version of the Stanford Sentiment Treebank 2 (SST-2), a binary classification dataset for sentiment analysis.

  Modifications:

Labels were originally "negative" and "positive", now converted to integers (0 for negative, 1 for positive). Each example includes a task prefix: Task: SST2 | Sentence: ... The dataset has been tokenized using the LLaMA-1B tokenizer. Maximum sequence length is 128 tokens.… See the full description on the dataset page: https://huggingface.co/datasets/emirhanboge/sst2_llama1b_modified.

Stanford Sentiment Treebank - Binary

Norwegian Translated SST-2 Dataset

  Dataset





  Overview

The dataset is a Norwegian machine-translation of the Stanford Sentiment Treebank (SST-2). The original dataset comprises sentences extracted from movie reviews, accompanied by human annotations indicating their sentiment.

  Dataset Structure

The dataset has the following structure: { "idx": int, "sentence": str, "label": int, "sentence_nob": str }

  Data Fields

idx:… See the full description on the dataset page: https://huggingface.co/datasets/Kushtrim/sst2-norwegian-bokmaal.

Albanian Translated SST-2 Dataset

  Dataset





  Overview

The dataset is a Albanian machine-translation of the Stanford Sentiment Treebank (SST-2). The original dataset comprises sentences extracted from movie reviews, accompanied by human annotations indicating their sentiment.

  Dataset Structure

The dataset has the following structure: { "idx": int, "sentence": str, "label": int, "sentence_alb": str }

  Data Fields

idx:… See the full description on the dataset page: https://huggingface.co/datasets/Kushtrim/sst2-albanian.

Dataset Card for cobie_sst2

This dataset is a modification of the original SST-2 dataset for LLM cognitive bias evaluation.

  Language(s)

English (en)

  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… See the full description on the dataset page: https://huggingface.co/datasets/BSC-LT/cobie_sst2.