53 datasets found

Text from social media provides a set of challenges that can cause traditional NLP approaches to fail. Informal language, spelling errors, abbreviations, and special characters...

The dataset used in this paper is a linguistic data set consisting of co-occurrences of 54 nouns and 58 adjectives in Charles Dickens' novel David Copperfield.

The BBC News dataset was used for sentiment analysis of news articles.

The NIPS full paper dataset is a collection of text documents.

The dataset consists of three large databases: Google-ngram, English Wikipedia, and a collection of scientific articles.

The Leipzig Corpus Miner (LCM) is a decentralized SaaS application for the analysis of large amounts of news texts.

Individual text corpora (ICs) were generated from 214 participants with a mean number of 5 million word tokens.

The OpenWebText corpus is a collection of text data from the web.

The RECIPES dataset contains various annotated states (e.g., shape, composition, location, etc.) for ingredients in cooking recipes.

The PROPARA dataset comprises procedural text about scientific processes. The location states of participant entities at each time step (sentence) in these processes are labeled...

The dataset used in the paper is a collection of 1.1M tweets from Twitter, with approximately 3000 tweets per user from various domains such as politics, sports, entertainment,...

The STS benchmark (Cer et al., 2017) and SICK-Relatedness dataset (Marelli et al., 2014) respectively contain 8.6K and 9.8K labeled sentence pairs, the sizes of which are...

Radiology reports dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm.

NIPS dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm.

Hierarchical Latent Word Clustering dataset is used to test the proposed Hierarchical Latent Word Clustering algorithm.

The dataset used in this paper is a collection of short texts, including tweets, Pascal Flickr captions, and search snippets.

The Pile dataset contains 3.5 million samples of diverse text for language modeling.

Probase is a probabilistic knowledge base and it contains millions of entities and concepts. One of the advantages of Probase is that in comparison with the well-known knowledge...

The dataset used in the paper is a word2vec embedding trained on a corpus of Google News texts.

The Twitter Dataset is a collection of tweets annotated with Plutchik's emotions, consisting of tweets in three different languages: English, Dutch, and German.