23 datasets found

The dataset is used for evaluating large language models on solving NLP problems.

The authors used their own dataset for dysmenorrhea classification.

The authors used the N2C2 smoking challenge data-set for smoking status classification task.

Clinical note classification is a common clinical NLP task. However, annotated data-sets are scarce. The authors used the N2C2 obesity challenge data-set, the N2C2 smoking...

ANERcorp is a named entity recognition dataset.

MasakhaNER 2.0 is a NER dataset in the news domain, including the annotations on 20 African languages.

The Sanskrit text is annotated with various NLP tasks, including sentence boundary detection, canonical word ordering, free-form text annotation of tokens, token classification,...

The Super-NaturalInstructions (SNI) dataset is a collection of 1761 diverse NLP tasks belonging to one of 76 task types.

SNLI, MNLI, Stress Test, Matched Mismatched, Competence, Distraction, and Noise datasets

The dataset used in the paper is not explicitly mentioned, but it is mentioned that the authors used the Universal Dependencies (UD) treebanks.

MACHAMP is a toolkit for multi-task learning in NLP, supporting a wide range of NLP tasks.

A dataset management operations and recipes for NLP data production

A workflow manager for the flexible creation and customisation of NLP processing pipelines.

The MatSci-NLP dataset is a collection of materials science text for NLP tasks.

Dark jargons are benign-looking words that have hidden, sinister meanings and are used by participants of underground forums for illicit behavior.

The ACL Anthology dataset contains papers on natural language processing, including citation patterns, authorship, and language use over time.

The UCCA dataset is used to test the annotation scheme in cross-lingual semantic representation for NLP.

The dataset used in this study is a combination of data from Google Fact-Check explorer and data directly crawled from the websites of verified signatories of the International...

The TEL-NLP dataset is a collection of Telugu text data for four NLP tasks: sentiment analysis, emotion identification, hate speech detection, and sarcasm detection.

The dataset used in the paper is not explicitly described, but it is mentioned that the authors used three downstream tasks from the GLUE benchmark: Stanford Sentiment Treebank...