Explore a wide range of big text datasets for NLP tasks, including text classification, sentiment analysis, and language modeling, with over 1,000 datasets available.
The Linguistic Data Consortium at the University of Pennsylvania offers a variety of large text datasets for NLP research, including the Penn Treebank and the Gigaword corpus.
This article discusses popular big text datasets used in NLP tasks, such as the Common Crawl dataset, the Wikipedia dump, and the BookCorpus dataset, highlighting their applications and challenges.
Stay up-to-date with the latest advancements in NLP with this comprehensive blog, featuring news, research papers, and tutorials on big text datasets and their applications in NLP tasks.
Kaggle provides a collection of public datasets for NLP tasks, including text classification, language modeling, and machine translation, with opportunities for competitions and collaboration.
The National Institute of Standards and Technology (NIST) offers a range of text datasets for NLP research, including the NIST Open Machine Translation Evaluation dataset and the NIST Text Retrieval Conference (TREC) dataset.
The Stanford NLP Group provides access to various large text datasets, including the Stanford Question Answering Dataset (SQuAD) and the Stanford Sentiment Treebank, for research and development in NLP.
This video lecture series covers the application of big data techniques to NLP tasks, including the use of large text datasets, distributed computing, and deep learning models.