Update README.md

README.md

@@ -26,7 +26,7 @@ task_ids:
 - open-domain-qa
 ---
 
-# Dataset Card for Serbian Natural Questions (Subset) based on MaCoCu-sr
+# Dataset Card for MaCoCu-sr dataset
 
 ## Dataset Description
 
@@ -36,9 +36,7 @@ task_ids:
 
 ### 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.
+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
 
@@ -52,67 +50,22 @@ Considerable effort was devoted to cleaning the extracted text to provide a high
 - 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]
+[SmartCat]
 
 ### Licensing Information
 
-This dataset is licensed under CC-BY-4.0.
+This dataset is licensed under MIT licence.
 
 ### 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},
@@ -129,8 +82,7 @@ Additionally, please acknowledge the following projects and institutions:
 
 ### Contributions
 
-Thanks to Google for creating the original Natural Questions dataset and to the MaCoCu project for the Serbian web corpus.
-
+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: