Update README.md

README.md

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----
-license: mit
----
+---
+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 Serbian Natural Questions (Subset) based on MaCoCu-sr
+
+## 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
+
+This dataset comprises the first 8,000 examples of Google's Natural Questions (NQ) dataset, automatically translated to Serbian using the MaCoCu-sr corpus as a reference. All queries have their corresponding IDs, allowing them to be traced back to the original data. The translation was performed automatically using the "gpt-3.5-turbo-0125" model. This dataset is designed for evaluating embedding models on Question Answering (QA) and Information Retrieval (IR) tasks in Serbian.
+
+The original NQ corpus contains questions from real users and requires QA systems to read and comprehend entire Wikipedia articles that may or may not contain the answer to the question. The inclusion of real user questions and the requirement to read entire pages make NQ a more realistic and challenging task compared to prior QA datasets.
+
+### 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)
+
+### Data Structure
+
+Each document in the XML format of the MaCoCu-sr corpus is accompanied by the following metadata:
+- Title
+- Crawl date
+- URL
+- Domain
+- File type of the original document
+- Distribution of languages inside the document
+- Fluency score based on a language model
+
+Each paragraph contains metadata on:
+- Whether it is a heading
+- Paragraph quality (labels such as "short" or "good")
+- Fluency score (between 0 and 1)
+- Automatically identified language
+- Presence of sensitive information
+
+### Data Instances
+
+Each instance in our dataset contains:
+- `id`: The original Natural Questions question ID
+- `question`: The question translated to Serbian
+- `article`: The corresponding Wikipedia article translated to Serbian
+- `short_answer`: The short answer (if available) translated to Serbian
+- `long_answer`: The long answer (paragraph containing the answer) translated to Serbian
+
+### Data Fields
+
+- `id`: string
+- `question`: string
+- `article`: string
+- `short_answer`: string (nullable)
+- `long_answer`: string
+
+### Data Splits
+
+The dataset consists of 8,000 examples. There are no predefined train/validation/test splits.
+
+## Additional Information
+
+### Dataset Curators
+
+[Your Name or Organization]
+
+### Licensing Information
+
+This dataset is licensed under CC-BY-4.0.
+
+### Citation Information
+
+If you use this dataset, please cite the following:
+
+```
+@misc{serbian-nq-subset,
+  title={Serbian Natural Questions Subset based on MaCoCu-sr},
+  author={[Your Name]},
+  year={2024},
+  howpublished={\url{https://huggingface.co/datasets/your-username/serbian-nq-subset}}
+}
+
+@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 Google for creating the original Natural Questions dataset and to the MaCoCu project for the Serbian web corpus.
+
+### 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")
+
+```