PhilipMay/stsb_multi_mt
Dataset Card for STSb Multi MT Dataset Summary STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums. (source) These are different multilingual translations and the English original of the STSbenchmark dataset. Translation has been done with deepl.com. It can be used to train sentence… See the full description on the dataset page: https://huggingface.co/datasets/PhilipMay/stsb_multi_mt.
Dataset Card for STSb Multi MT
Table of Contents
- Dataset Description
- Dataset Summary
- Supported Tasks and Leaderboards
- Languages
- Dataset Structure
- Data Instances
- Data Fields
- Data Splits
- Dataset Creation
- Curation Rationale
- Source Data
- Annotations
- Personal and Sensitive Information
- Considerations for Using the Data
- Social Impact of Dataset
- Discussion of Biases
- Other Known Limitations
- Additional Information
- Dataset Curators
- Licensing Information
- Citation Information
- Contributions
Dataset Description
- Repository: https://github.com/PhilipMay/stsb-multi-mt
- Homepage (original dataset): https://ixa2.si.ehu.es/stswiki/index.php/STSbenchmark
- Paper about original dataset: https://arxiv.org/abs/1708.00055
- Leaderboard: https://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark#Results
- Point of Contact: Open an issue on GitHub
Dataset Summary
STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums. (source)
These are different multilingual translations and the English original of the STSbenchmark dataset. Translation has been done with deepl.com. It can be used to train sentence embeddings like T-Systems-onsite/cross-en-de-roberta-sentence-transformer.
Examples of Use
Load German dev Dataset:
from datasets import load_dataset
dataset = load_dataset("stsb_multi_mt", name="de", split="dev")Load English train Dataset:
from datasets import load_dataset
dataset = load_dataset("stsb_multi_mt", name="en", split="train")Supported Tasks and Leaderboards
[More Information Needed]
Languages
Available languages are: de, en, es, fr, it, nl, pl, pt, ru, zh
Dataset Structure
Data Instances
This dataset provides pairs of sentences and a score of their similarity.
An example:
{
"sentence1": "A man is playing a large flute.",
"sentence2": "A man is playing a flute.",
"similarity_score": 3.8
}Data Fields
sentence1: The 1st sentence as astr.sentence2: The 2nd sentence as astr.similarity_score: The similarity score as afloatwhich is<= 5.0and>= 0.0.
Data Splits
- train with 5749 samples
- dev with 1500 samples
- test with 1379 sampples
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
See LICENSE and download at original dataset.
Citation Information
@InProceedings{huggingface:dataset:stsb_multi_mt,
title = {Machine translated multilingual STS benchmark dataset.},
author={Philip May},
year={2021},
url={https://github.com/PhilipMay/stsb-multi-mt}
}Contributions
Thanks to @PhilipMay for adding this dataset.
