metadata

license: apache-2.0
multilinguality: monolingual
size_categories:
  - 10K<n<100K
language: ro
task_categories:
  - sentence-similarity
pretty_name: ROSTSC

RO-STS-Cupidon

Overview

RoSTSC is a Romanian Semantic Textual Similarity (STS) dataset designed for evaluating and training sentence embedding models. It contains pairs of Romanian sentences along with similarity scores that indicate the degree of semantic equivalence between them.

Dataset Structure

sentence1: The first sentence in the pair.
sentence2: The second sentence in the pair.
score: A numerical value representing the semantic similarity between the two sentences, normalized between 0 and 1.

Dataset Composition

Source Dataset	Split	Number of Pairs
mteb/sts17-crosslingual-sts	en-en	250
mteb/sts12-sts	train	2225
mteb/sts12-sts	test	3029
mteb/biosses-sts	test	100
mteb/sts16-sts	test	1184
mteb/sts15-sts	test	2992
mteb/sts14-sts	test	3749
mteb/sts13-sts	test	1498
mteb/sickr-sts	test	9927
dumitrescustefan/ro_sts	full	8628
andyP/ro-paraphrase-bible	train	30000
manual/generated	hand	7012
Total		70594

Data Collection and Processing

The data has been collected from existing datasets, primarily in English, and translated into Romanian. Some datasets were originally in Romanian and were used either in full or in part.

Usage

This dataset can be used for:

Fine-tuning and evaluating sentence embedding models for Romanian.
Research on semantic textual similarity and natural language understanding (NLU) in Romanian.

How to Load the Dataset

You can load the dataset using the datasets library from Hugging Face:

from datasets import load_dataset

dataset = load_dataset("BlackKakapo/RoSTSC")

# Access the train split
train_data = dataset["train"]

# View an example
print(train_data[0])

Alternatively, if you have the dataset as a CSV file, you can load it using pandas:

import pandas as pd

df = pd.read_csv("RoSTSC.csv")
print(df.head())

This allows you to easily integrate the dataset into your training or evaluation pipeline.

License

This dataset is licensed under Apache 2.0.

Citation

If you use RO-STS-Corpus in your research, please cite this dataset as follows:

@misc{ro_sts_corpus,
  title={RoSTSC: A Romanian STS Cupidon},
  author={BlackKakapo},
  year={2025},
}

Acknowledgments

We acknowledge contributions from various resources used in compiling and annotating this dataset.

Further details and additional metadata will be added in future versions.