GLUE, the General Language Understanding Evaluation benchmark (https://gluebenchmark.com/) is a collection of resources for training, evaluating, and analyzing natural languag
The SNLI corpus (version 1.0) is a collection of 570k human-written English sentence pairs manually labeled for balanced classification with the labels entailment, contradicti
Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine").
KLUE (Korean Language Understanding Evaluation) Korean Language Understanding Evaluation (KLUE) benchmark is a series of datasets to evaluate natural language understanding ca
Shared and internationally recognized benchmarks are fundamental for the development of any computational system. We aim to help the research community working on compositiona
The SemEval-2014 Task 1 focuses on Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Entailment. The task was desig
This dataset is a recasted version of the Hindi Discourse Analysis Dataset used to train models for Natural Language Inference Tasks in Low-Resource Languages like Hindi.
Recent advances in the field of universal language models and transformers require the development of a methodology for their broad diagnostics and testing for general intelle
This dataset is used to train models for Natural Language Inference Tasks in Low-Resource Languages like Hindi.
The ASSIN 2 corpus is composed of rather simple sentences. Following the procedures of SemEval 2014 Task 1. The training and validation data are composed, respectively, of 6,5
XGLUE is a new benchmark dataset to evaluate the performance of cross-lingual pre-trained models with respect to cross-lingual natural language understanding and generation. T
The dataset contains data for bechmarking korean models on NLI and STS
The COPA-HR dataset (Choice of plausible alternatives in Croatian) is a translation of the English COPA dataset (https://people.ict.usc.edu/~gordon/copa.html) by following th
The ASSIN (Avaliação de Similaridade Semântica e INferência textual) corpus is a corpus annotated with pairs of sentences written in Portuguese that is suitable for the explo
First benchmark dataset for sentence entailment in the low-resource Filipino language. Constructed through exploting the structure of news articles. Contains 600,000 premise-h
Over >25k semiautomatically generated sentence pairs illustrating well-studied pragmatic inference types. IMPPRES is an NLI dataset following the format of SNLI (Bowman et al.
This is a Natural Language Inference (NLI) dataset for Bengali, curated using the subset of MNLI data used in XNLI and state-of-the-art English to Bengali translation model.
A Persian textual entailment task (deciding `sent1` entails `sent2`).