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Datasets/SICK

SICK

Sentences Involving Compositional Knowledge

TextsCC BY-NC-SA 3.0Introduced 2014-01-01

The Sentences Involving Compositional Knowledge (SICK) dataset is a dataset for compositional distributional semantics. It includes a large number of sentence pairs that are rich in the lexical, syntactic and semantic phenomena. Each pair of sentences is annotated in two dimensions: relatedness and entailment. The relatedness score ranges from 1 to 5, and Pearson’s r is used for evaluation; the entailment relation is categorical, consisting of entailment, contradiction, and neutral. There are 4439 pairs in the train split, 495 in the trial split used for development and 4906 in the test split. The sentence pairs are generated from image and video caption datasets before being paired up using some algorithm.

Source: Multi-Label Transfer Learning for Multi-Relational Semantic Similarity Image Source: https://www.researchgate.net/figure/Example-of-SICK-dataset-sentence-expansion-process-14_fig1_344863619

Benchmarks

Language Modelling/MSELanguage Modelling/Pearson CorrelationLanguage Modelling/Spearman CorrelationNatural Language Inference/1:1 AccuracySemantic Similarity/MSESemantic Similarity/Pearson CorrelationSemantic Similarity/Spearman CorrelationSemantic Textual Similarity/Spearman CorrelationSentence Pair Modeling/MSESentence Pair Modeling/Pearson CorrelationSentence Pair Modeling/Spearman CorrelationTabular Data Generation/DT AccuracyTabular Data Generation/LR AccuracyTabular Data Generation/Parameters(M)Tabular Data Generation/RF Accuracy

Related Benchmarks

SICK-R/Semantic Textual Similarity/Spearman CorrelationSICKLE/Crop Yield Prediction/MAPE (%)

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Papers
348
Benchmarks
15

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Tasks

Language ModellingNatural Language InferenceSemantic SimilaritySemantic Textual SimilaritySentence Pair ModelingTabular Data Generation