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Semantic Textual Similarity in Python
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CLSS-data
MegaEXPERT-2016
SICK-data
STS-data
notebooks removed BEER feature Feb 3, 2016
other-data
rakusis added mwa Jan 29, 2017
sts2016-annotated
sts2016-english-v1.1 added left/right test Feb 1, 2016
README.md
USAAR-SHEFF_2015_modely_features.sh
clss-text.csv
clss_data.py
csv2tsv.py
mwa_prop.py
sts.csv
sts2016-test.DLS2014.csv
sts2016_test.stasis.csv
sts2016_train.stasis.csv
sts2017.csv
sts2017_data.py
sts_compose.py
sts_data.py added magic line Jan 18, 2017
sts_glove.py

README.md

Stasis - Python wrapper for Semantic Similarity datasets

Under the auspice of the EXPERT project (http://expert-itn.eu/), we have written a python wrapper to the STS datasets and we hope that it helps anyone with easy manipulation the datasets.

If you just need a tab-separated file, you can easily find the sts.csv available in the same repository. The repo also contains other (maybe) useful datasets that are manually compiled by the maintainer when they are free.

Disclaimer: The repository comes as it is. It should NOT be considered as the official SemEval's (Semantic Textual Similarity) STS data and it is not affiliated with the STS organizers. We've created this so that people can easily do something like pandas.read_csv('sts.csv') or graphlab.SFrame('sts.csv') and work with the dataframes with little hassle.

Datasets

Below is a list of datasets/wrappers you can find here

Contribute

Please feel free to add datasets/wrappers to the repository. Or post an issue to request for wrappers to the repository.

Cite

Please cite the respective references for the datasets when using them in your publication!

If you want to cite this repository, you can cite this paper where we created used the sts.csv in SemEval-2015

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