SST

Stanford Sentiment Treebank

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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. Each phrase is labelled as either *negative*, *somewhat negative*, *neutral*, *somewhat positive* or *positive*. The corpus with all 5 labels is referred to as SST-5 or SST fine-grained. 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.

Texts English

벤치마크

Sentiment Analysis on SST-2 Binary classification 결과 87개

Sentiment Analysis on SST-5 Fine-grained classification 결과 31개

Classification on SST-2 결과 6개

Text Classification on SST-2 결과 6개

Few-Shot Text Classification on SST-5 결과 3개

Few-Shot Learning on SST-2 Binary classification 결과 2개

Explanation Fidelity Evaluation on SST-5 결과 1개

Explanation Fidelity Evaluation on SST2 결과 1개

Out-of-Distribution Detection on SST 결과 1개