211 datasets found

The UNIREX framework extends the approach to a more general setting.

The Tweet Sentiment Extraction dataset contains positive, negative, and neutral tweets with human-annotated rationales.

The Movie Reviews dataset contains positive and negative movie reviews with rationales annotated by humans to support classification.

The RP dataset, derived from the RELPRON dataset, consists of 105 noun phrases containing relative clauses.

The MC (Meaning Classification) dataset is a specially crafted dataset used for a classification task.

Text classification is an important and widely studied task in natural language processing (NLP), with extensive applications such as sentiment analysis, topic classification,...

The dataset consists of 25000 reviews from IMDb.

The DBpedia Animals dataset comprises 10,000 English Wikipedia article abstracts for animal species.

The DynaSent dataset contains approximately 122,000 sentences, each labeled as positive, neutral, or negative.

AG's News Corpus

Rcv1: A new benchmark collection for text categorization research.

AGNews, 20News, NYT, IMDB are datasets used for weakly supervised text classification.

The HateXplain dataset, containing 20,000 posts from Gab and Twitter, annotated with hate/offensive/normal labels.

CLIMABENCH is a benchmark of climate-related text classification tasks. It collates five existing climate change-related text datasets, including CLIMATEXT, CLIMATESTANCE,...

The dataset used in this paper is a collection of news articles from AllNews.

The dataset used in this paper is a collection of documents from Wikipedia.

The NeurIPS dataset is a collection of 7241 papers published in NeurIPS from 1987 to 2016.

WOS dataset is a text classification dataset containing scientific articles from Web of Science.

The dataset used in the paper is the Wikipedia dataset, which contains over six million English Wikipedia articles with a full-text field associated with 50 training queries...

The dataset used in the paper is a collection of text sequences for text classification tasks.