Datasets:
Tasks:
Text Classification
Formats:
csv
Sub-tasks:
natural-language-inference
Languages:
Spanish
Size:
1K - 10K
ArXiv:
License:
metadata
license: cc-by-4.0
The INFERES dataset
train size = 6444
test size = 1612
Columns
ID : the unique ID of the instance
Premise
Hypothesis
Label: cnt, ent, neutral
Topic: 1 (Picasso), 2 (Columbus), 3 (Videogames), 4 (Olympic games), 5 (EU), 6 (USSR)
Anno: ID of the annotators (in cases of undergrads or crowd - the ID of the group)
Anno_Type: strategy used to generate the data: Generate, Rewrite, Crowd, and Automated
The train/test split is stratified by a key that combines Label + Anno + Anno_type
Disclaimer
The results in the paper are done via k-fold cross validation and average across multiple runs. Experiments with this split might differ slightly.
License
cc-by-4.0