
# Dataset Card for "PAQ_pairs"

## 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:** [https://github.com/facebookresearch/PAQ](https://github.com/facebookresearch/PAQ)
- **Repository:** [More Information Needed](https://github.com/facebookresearch/PAQ)
- **Paper:** [More Information Needed](https://github.com/facebookresearch/PAQ)
- **Point of Contact:** [More Information Needed](https://github.com/facebookresearch/PAQ)
- **Size of downloaded dataset files:** 
- **Size of the generated dataset:** 
- **Total amount of disk used:** 21 Bytes

### Dataset Summary

Pairs questions and answers obtained from Wikipedia.

Disclaimer: The team releasing PAQ QA pairs did not upload the dataset to the Hub and did not write a dataset card. 
These steps were done by the Hugging Face team.

### Supported Tasks
- [Sentence Transformers](https://huggingface.co/sentence-transformers) training; useful for semantic search and sentence similarity. 
### Languages
- English.
## Dataset Structure
Each example in the dataset contains pairs of sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value". The first sentence is a question and the second an answer; thus, both sentences would be similar.

```
{"set": [sentence_1, sentence_2]}
{"set": [sentence_1, sentence_2]}
...
{"set": [sentence_1, sentence_2]}
```

This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.

### Usage Example

Install the 🤗 Datasets library with `pip install datasets` and load the dataset from the Hub with:
```python
from datasets import load_dataset
dataset = load_dataset("embedding-data/PAQ_pairs")
```
The dataset is loaded as a `DatasetDict` and has the format:
```python
DatasetDict({
    train: Dataset({
        features: ['set'],
        num_rows: 64371441
    })
})
```
Review an example `i` with:

```python
dataset["train"][i]["set"]
```



### Data Instances

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Data Fields

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Data Splits

[More Information Needed](https://github.com/facebookresearch/PAQ)

## Dataset Creation

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Curation Rationale

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/facebookresearch/PAQ)

#### Who are the source language producers?

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/facebookresearch/PAQ)

#### Who are the annotators?

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Personal and Sensitive Information

[More Information Needed](https://github.com/facebookresearch/PAQ)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Discussion of Biases

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Other Known Limitations

[More Information Needed](https://github.com/facebookresearch/PAQ)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/facebookresearch/PAQ)

### Licensing Information

The PAQ QA-pairs and metadata is licensed under [CC-BY-SA](https://creativecommons.org/licenses/by-sa/3.0/). 
Other data is licensed according to the accompanying license files.

### Citation Information

```
@article{lewis2021paq,
      title={PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them}, 
      author={Patrick Lewis and Yuxiang Wu and Linqing Liu and Pasquale Minervini and Heinrich Küttler and Aleksandra Piktus and Pontus Stenetorp and Sebastian Riedel},
      year={2021},
      eprint={2102.07033},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

```

### Contributions

Thanks to [@patrick-s-h-lewis](https://github.com/patrick-s-h-lewis) for adding this dataset.


task_categories:sentence-similarity task_ids:semantic-similarity-classification language:en license:mit arxiv:2102.07033 region:us
{"language": ["en"], "license": "mit", "task_categories": ["sentence-similarity", "paraphrase-mining"], "task_ids": ["semantic-similarity-classification"], "paperswithcode_id": "embedding-data/PAQ_pairs", "pretty_name": "PAQ_pairs"}
TAGS
#task_categories-sentence-similarity #task_ids-semantic-similarity-classification #language-English #license-mit #arxiv-2102.07033 #region-us 


# Dataset Card for "PAQ_pairs"

## 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: URL
- Repository: 
- Paper: 
- Point of Contact: 
- Size of downloaded dataset files: 
- Size of the generated dataset: 
- Total amount of disk used: 21 Bytes

### Dataset Summary

Pairs questions and answers obtained from Wikipedia.

Disclaimer: The team releasing PAQ QA pairs did not upload the dataset to the Hub and did not write a dataset card. 
These steps were done by the Hugging Face team.

### Supported Tasks
- Sentence Transformers training; useful for semantic search and sentence similarity. 
### Languages
- English.
## Dataset Structure
Each example in the dataset contains pairs of sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value". The first sentence is a question and the second an answer; thus, both sentences would be similar.



This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.

### Usage Example

Install the  Datasets library with 'pip install datasets' and load the dataset from the Hub with:

The dataset is loaded as a 'DatasetDict' and has the format:

Review an example 'i' with:





### Data Instances



### Data Fields



### Data Splits



## 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



### Licensing Information

The PAQ QA-pairs and metadata is licensed under CC-BY-SA. 
Other data is licensed according to the accompanying license files.





### Contributions

Thanks to @patrick-s-h-lewis for adding this dataset.


# Dataset Card for "PAQ_pairs" ## 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: URL
- Repository: 
- Paper: 
- Point of Contact: 
- Size of downloaded dataset files: 
- Size of the generated dataset: 
- Total amount of disk used: 21 Bytes ### Dataset Summary

Pairs questions and answers obtained from Wikipedia.

Disclaimer: The team releasing PAQ QA pairs did not upload the dataset to the Hub and did not write a dataset card. 
These steps were done by the Hugging Face team. ### Supported Tasks
- Sentence Transformers training; useful for semantic search and sentence similarity. ### Languages
- English. ## Dataset Structure
Each example in the dataset contains pairs of sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value". The first sentence is a question and the second an answer; thus, both sentences would be similar.



This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences. ### Usage Example

Install the  Datasets library with 'pip install datasets' and load the dataset from the Hub with:

The dataset is loaded as a 'DatasetDict' and has the format:

Review an example 'i' with: ### Data Instances ### Data Fields ### Data Splits ## 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 ### Licensing Information

The PAQ QA-pairs and metadata is licensed under CC-BY-SA. 
Other data is licensed according to the accompanying license files. ### Contributions

Thanks to @patrick-s-h-lewis for adding this dataset.
TAGS
#task_categories-sentence-similarity #task_ids-semantic-similarity-classification #language-English #license-mit #arxiv-2102.07033 #region-us 
 # Dataset Card for "PAQ_pairs" ## 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: URL
- Repository: 
- Paper: 
- Point of Contact: 
- Size of downloaded dataset files: 
- Size of the generated dataset: 
- Total amount of disk used: 21 Bytes ### Dataset Summary

Pairs questions and answers obtained from Wikipedia.

Disclaimer: The team releasing PAQ QA pairs did not upload the dataset to the Hub and did not write a dataset card. 
These steps were done by the Hugging Face team. ### Supported Tasks
- Sentence Transformers training; useful for semantic search and sentence similarity. ### Languages
- English. ## Dataset Structure
Each example in the dataset contains pairs of sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value". The first sentence is a question and the second an answer; thus, both sentences would be similar.



This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences. ### Usage Example

Install the  Datasets library with 'pip install datasets' and load the dataset from the Hub with:

The dataset is loaded as a 'DatasetDict' and has the format:

Review an example 'i' with: ### Data Instances ### Data Fields ### Data Splits ## 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 ### Licensing Information

The PAQ QA-pairs and metadata is licensed under CC-BY-SA. 
Other data is licensed according to the accompanying license files. ### Contributions

Thanks to @patrick-s-h-lewis for adding this dataset.
passage: TAGS
#task_categories-sentence-similarity #task_ids-semantic-similarity-classification #language-English #license-mit #arxiv-2102.07033 #region-us 
# Dataset Card for "PAQ_pairs"## 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: URL
- Repository: 
- Paper: 
- Point of Contact: 
- Size of downloaded dataset files: 
- Size of the generated dataset: 
- Total amount of disk used: 21 Bytes### Dataset Summary

Pairs questions and answers obtained from Wikipedia.

Disclaimer: The team releasing PAQ QA pairs did not upload the dataset to the Hub and did not write a dataset card. 
These steps were done by the Hugging Face team.### Supported Tasks
- Sentence Transformers training; useful for semantic search and sentence similarity.### Languages
- English.## Dataset Structure
Each example in the dataset contains pairs of sentences and is formatted as a dictionary with the key "set" and a list with the sentences as "value". The first sentence is a question and the second an answer; thus, both sentences would be similar.



This dataset is useful for training Sentence Transformers models. Refer to the following post on how to train models using similar pairs of sentences.### Usage Example

Install the  Datasets library with 'pip install datasets' and load the dataset from the Hub with:

The dataset is loaded as a 'DatasetDict' and has the format:

Review an example 'i' with:### Data Instances### Data Fields### Data Splits## Dataset Creation