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Table · dataset · 2022

Stanford Sentiment Treebank v2

Listed in Hugging Face Datasets

Dataset Card for [Dataset Name] Dataset

Description

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: huggingface.co/datasets/stanfordnlp/sst2.

Links

Where it is published

Catalogue records · 1

Topics

Stated by source
text · text classification

Related

Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
Hugging Face Datasetsstanfordnlp/sst212 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:text-classificationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
license_textsource · Hugging Faceconnector:huggingface@1.0.0
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0