
# Dataset Card for Swedish Machine Translated STS-B 

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** [stsb-mt-sv homepage](https://github.com/timpal0l/sts-benchmark-swedish)
- **Repository:** [stsb-mt-sv repository](https://github.com/timpal0l/sts-benchmark-swedish)
- **Paper:** [Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
](https://arxiv.org/abs/2009.03116)
- **Point of Contact:** [Tim Isbister](mailto:timisbisters@gmail.com)

### Dataset Summary

This dataset is a Swedish machine translated version for semantic textual similarity. 

### Supported Tasks and Leaderboards

This dataset can be used to evaluate text similarity on Swedish.

### Languages

The text in the dataset is in Swedish. The associated BCP-47 code is `sv`.

## Dataset Structure

### Data Instances

What a sample looks like:
```
{'score': '4.2',
 'sentence1': 'Undrar om jultomten kommer i år pga Corona..?',
 'sentence2': 'Jag undrar om jultomen kommer hit i år med tanke på covid-19',
}
```

### Data Fields

- `score`: a float representing the semantic similarity score. Where 0.0 is the lowest score and 5.0 is the highest.
- `sentence1`: a string representing a text
- `sentence2`: another string to compare the semantic with

### Data Splits

The data is split into a training, validation and test set. The final split sizes are as follow:

| Train  | Valid | Test |
| ------ | ----- | ---- |
| 5749   |  1500 | 1379 |

## Dataset Creation

### Curation Rationale

[Needs More Information]

### Source Data

#### Initial Data Collection and Normalization

[Needs More Information]

#### Who are the source language producers?

[Needs More Information]

### Annotations

#### Annotation process

[Needs More Information]

#### Who are the annotators?

[Needs More Information]

### Personal and Sensitive Information

[Needs More Information]

## Considerations for Using the Data

### Social Impact of Dataset

[Needs More Information]

### Discussion of Biases

[Needs More Information]

### Other Known Limitations

[Needs More Information]

## Additional Information

### Dataset Curators

The machine translated version were put together by @timpal0l

### Licensing Information

[Needs More Information]

### Citation Information

```
@article{isbister2020not,
  title={Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity},
  author={Isbister, Tim and Sahlgren, Magnus},
  journal={arXiv preprint arXiv:2009.03116},
  year={2020}
}
```

### Contributions

Thanks to [@timpal0l](https://github.com/timpal0l) for adding this dataset.
task_categories:text-classification task_ids:text-scoring task_ids:semantic-similarity-scoring annotations_creators:crowdsourced language_creators:crowdsourced language_creators:machine-generated multilinguality:monolingual size_categories:1K<n<10K source_datasets:extended|other-sts-b language:sv license:unknown arxiv:2009.03116 region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced", "machine-generated"], "language": ["sv"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["extended|other-sts-b"], "task_categories": ["text-classification"], "task_ids": ["text-scoring", "semantic-similarity-scoring"], "pretty_name": "Swedish Machine Translated STS-B", "dataset_info": {"features": [{"name": "sentence1", "dtype": "string"}, {"name": "sentence2", "dtype": "string"}, {"name": "score", "dtype": "float32"}], "config_name": "plain_text", "splits": [{"name": "test", "num_bytes": 171823, "num_examples": 1379}, {"name": "validation", "num_bytes": 218843, "num_examples": 1500}, {"name": "train", "num_bytes": 772847, "num_examples": 5749}], "download_size": 383047, "dataset_size": 1163513}}
TAGS
#task_categories-text-classification #task_ids-text-scoring #task_ids-semantic-similarity-scoring #annotations_creators-crowdsourced #language_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-sts-b #language-Swedish #license-unknown #arxiv-2009.03116 #region-us 

Dataset Card for Swedish Machine Translated STS-B
=================================================


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
-------------------


* Homepage: stsb-mt-sv homepage
* Repository: stsb-mt-sv repository
* Paper: Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity
* Point of Contact: Tim Isbister


### Dataset Summary


This dataset is a Swedish machine translated version for semantic textual similarity.


### Supported Tasks and Leaderboards


This dataset can be used to evaluate text similarity on Swedish.


### Languages


The text in the dataset is in Swedish. The associated BCP-47 code is 'sv'.


Dataset Structure
-----------------


### Data Instances


What a sample looks like:


### Data Fields


* 'score': a float representing the semantic similarity score. Where 0.0 is the lowest score and 5.0 is the highest.
* 'sentence1': a string representing a text
* 'sentence2': another string to compare the semantic with


### Data Splits


The data is split into a training, validation and test set. The final split sizes are as follow:


Train: 5749, Valid: 1500, Test: 1379


Dataset Creation
----------------


### Curation Rationale


### Source Data


#### Initial Data Collection and Normalization


#### Who are the source language producers?


### Annotations


#### Annotation process


#### Who are the annotators?


### Personal and Sensitive Information


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


### Discussion of Biases


### Other Known Limitations


Additional Information
----------------------


### Dataset Curators


The machine translated version were put together by @timpal0l


### Licensing Information


### Contributions


Thanks to @timpal0l for adding this dataset.



### Dataset Summary


This dataset is a Swedish machine translated version for semantic textual similarity. ### Supported Tasks and Leaderboards


This dataset can be used to evaluate text similarity on Swedish. ### Languages


The text in the dataset is in Swedish. The associated BCP-47 code is 'sv'.


Dataset Structure
----------------- ### Data Instances


What a sample looks like: ### Data Fields


* 'score': a float representing the semantic similarity score. Where 0.0 is the lowest score and 5.0 is the highest.
* 'sentence1': a string representing a text
* 'sentence2': another string to compare the semantic with ### Data Splits


The data is split into a training, validation and test set. The final split sizes are as follow:


Train: 5749, Valid: 1500, Test: 1379


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators


The machine translated version were put together by @timpal0l ### Licensing Information ### Contributions


Thanks to @timpal0l for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-text-scoring #task_ids-semantic-similarity-scoring #annotations_creators-crowdsourced #language_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-1K<n<10K #source_datasets-extended|other-sts-b #language-Swedish #license-unknown #arxiv-2009.03116 #region-us 
 ### Dataset Summary


This dataset is a Swedish machine translated version for semantic textual similarity. ### Supported Tasks and Leaderboards


This dataset can be used to evaluate text similarity on Swedish. ### Languages


The text in the dataset is in Swedish. The associated BCP-47 code is 'sv'.


Dataset Structure
----------------- ### Data Instances


What a sample looks like: ### Data Fields


* 'score': a float representing the semantic similarity score. Where 0.0 is the lowest score and 5.0 is the highest.
* 'sentence1': a string representing a text
* 'sentence2': another string to compare the semantic with ### Data Splits


The data is split into a training, validation and test set. The final split sizes are as follow:


Train: 5749, Valid: 1500, Test: 1379


Dataset Creation
---------------- ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations


Additional Information
---------------------- ### Dataset Curators


The machine translated version were put together by @timpal0l ### Licensing Information ### Contributions


Thanks to @timpal0l for adding this dataset.