---
license: mit
task_categories:
- translation
- sentence-similarity
language:
- sr
- en
pretty_name: MaCoCu Sebian-English Parallel Dataset
size_categories:
- 1M<n<10M
---

---
language:
- sr
license: cc-by-4.0
pretty_name: "Serbian Natural Questions (Subset) based on MaCoCu-sr"
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
---

# Dataset Card for MaCoCu-sr dataset

## Dataset Description

- **Repository:** [Hugging Face Dataset](https://huggingface.co/datasets/smartcat/MaCoCu_sr_en)
- **Point of Contact:** [SmartCat]
- **Source:** https://www.clarin.si/repository/xmlui/handle/11356/1807

### Dataset Summary

The Serbian web corpus MaCoCu-sr 1.0 was built by crawling the ".rs" and ".срб" internet top-level domains in 2021 and 2022, extending the crawl dynamically to other domains. This high-quality web corpus is characterized by extensive metadata, making it highly useful for corpus linguistics studies, as well as for training language models and other language technologies.

### Source Data

The source data for the Serbian translations is derived from the MaCoCu-sr 1.0 corpus, which was built by crawling the ".rs" and ".срб" internet top-level domains in 2021 and 2022, extending the crawl dynamically to other domains. The crawler is available at https://github.com/macocu/MaCoCu-crawler.

#### Data Collection and Processing

Considerable effort was devoted to cleaning the extracted text to provide a high-quality web corpus. This was achieved by:
- Removing boilerplate using [Justext](https://corpus.tools/wiki/Justext)
- Removing near-duplicated paragraphs using [Onion](https://corpus.tools/wiki/Onion)
- Discarding very short texts and texts not in the target language
- Applying extensive metadata filtering using [Monotextor](https://github.com/bitextor/monotextor)


## Additional Information

### Dataset Curators

[SmartCat]

### Licensing Information

This dataset is licensed under MIT licence.

### Citation Information

If you use this dataset, please cite the following:

```
@misc{macocu-sr,
  title={MaCoCu-sr 1.0},
  author={Connecting Europe Facility (CEF) Telecom},
  year={2022},
  howpublished={\url{https://www.clarin.si/repository/xmlui/handle/11356/1807}}
}
```

Additionally, please acknowledge the following projects and institutions:

- Connecting Europe Facility (CEF) Telecom INEA/CEF/ICT/A2020/2278341 "MaCoCu - Massive collection and curation of monolingual and bilingual data: focus on under-resourced languages"
- ARRS (Slovenian Research Agency) P6-0411 "Language Resources and Technologies for Slovene"
- Jožef Stefan Institute CLARIN "CLARIN.SI"

### Contributions

Thanks to CLARIN.SI for creating this dataset.
### Notice and Takedown

Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please:

1. Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted.
2. Clearly identify the copyrighted work claimed to be infringed.
3. Clearly identify the material that is claimed to be infringing and information reasonably sufficient to allow us to locate the material.
4. Please write to the contact person for this resource whose email is available in the full item record.

We will comply with legitimate requests by removing the affected sources from the next release of the corpus.

## Disclaimer

This action has received funding from the European Union's Connecting Europe Facility 2014-2020 - CEF Telecom, under Grant Agreement No. INEA/CEF/ICT/A2020/2278341. This communication reflects only the author's view. The Agency is not responsible for any use that may be made of the information it contains.

## Loading the Dataset

Here's a Python code example to load the dataset using the Hugging Face `datasets` library:

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("smartcat/MaCoCu_sr_en")

```