SNLI

doi:doi:10.57702/7uuyofll

SNLI

The dataset used in the paper is the Stanford Natural Language Inference (SNLI) dataset, which consists of 549,367 premise-hypothesis pairs for train/dev/test sets and target labels indicating their relation.

BibTex:

@dataset{Samuel_R_Bowman_and_Gabor_Angeli_and_Christopher_Potts_and_Christopher_D_Manning_2024,
    abstract = {The dataset used in the paper is the Stanford Natural Language Inference (SNLI) dataset, which consists of 549,367 premise-hypothesis pairs for train/dev/test sets and target labels indicating their relation.},
    author = {Samuel R. Bowman and Gabor Angeli and Christopher Potts and Christopher D. Manning},
    doi = {10.57702/7uuyofll},
    institution = {No Organization},
    keyword = {'Contradiction', 'Entailment', 'NLI', 'Natural Language Inference', 'Natural Language Understanding', 'Neutral', 'Question Answering', 'Question-Answer Generation', 'SNLI', 'Sentiment Analysis', 'Text Analysis', 'Text Classification', 'Text classification', 'Textual Entailment', 'character-level translation', 'crowd-sourced', 'crowdsourced', 'entailment', 'human-written', 'natural language inference', 'premise-hypothesis pairs', 'question generation', 'relation prediction', 'sentence embeddings', 'sentence pairs', 'sentence understanding', 'sentiment analysis', 'target labels', 'text classification'},
    month = {nov},
    publisher = {TIB},
    title = {SNLI},
    url = {https://service.tib.eu/ldmservice/dataset/snli},
    year = {2024}
}