
# Dataset Card for "wiki_dpr"

## 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

- **Repository:** https://github.com/facebookresearch/DPR
- **Paper:** https://arxiv.org/abs/2004.04906
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Size of downloaded dataset files:** 425.79 GB
- **Size of the generated dataset:** 470.52 GB
- **Total amount of disk used:** 978.05 GB

### Dataset Summary

This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.

The wikipedia dump is the one from Dec. 20, 2018.

There are two types of DPR embeddings based on two different models:
- `nq`: the model is trained on the Natural Questions dataset
- `multiset`: the model is trained on multiple datasets

Additionally, a FAISS index can be created from the embeddings:
- `exact`: with an exact FAISS index (high RAM usage)
- `compressed`: with a compressed FAISS index (approximate, but lower RAM usage)
- `no_index`: without FAISS index

Finally, there is the possibility of generating the dataset without the embeddings:
- `no_embeddings`

### Supported Tasks and Leaderboards

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Languages

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Dataset Structure

### Data Instances

Each instance contains a paragraph of at most 100 words, as well as the title of the wikipedia page it comes from, and the DPR embedding (a 768-d vector).

#### psgs_w100.multiset.compressed

- **Size of downloaded dataset files:** 70.97 GB
- **Size of the generated dataset:** 78.42 GB
- **Total amount of disk used:** 152.26 GB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [-0.07233893871307373,
   0.48035329580307007,
   0.18650995194911957,
   -0.5287084579467773,
   -0.37329429388046265,
   0.37622880935668945,
   0.25524479150772095,
   ...
   -0.336689829826355,
   0.6313082575798035,
   -0.7025573253631592]}
```

#### psgs_w100.multiset.exact

- **Size of downloaded dataset files:** 70.97 GB
- **Size of the generated dataset:** 78.42 GB
- **Total amount of disk used:** 187.38 GB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [-0.07233893871307373,
   0.48035329580307007,
   0.18650995194911957,
   -0.5287084579467773,
   -0.37329429388046265,
   0.37622880935668945,
   0.25524479150772095,
   ...
   -0.336689829826355,
   0.6313082575798035,
   -0.7025573253631592]}
```

#### psgs_w100.multiset.no_index

- **Size of downloaded dataset files:** 70.97 GB
- **Size of the generated dataset:** 78.42 GB
- **Total amount of disk used:** 149.38 GB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [-0.07233893871307373,
   0.48035329580307007,
   0.18650995194911957,
   -0.5287084579467773,
   -0.37329429388046265,
   0.37622880935668945,
   0.25524479150772095,
   ...
   -0.336689829826355,
   0.6313082575798035,
   -0.7025573253631592]}
```

#### psgs_w100.nq.compressed

- **Size of downloaded dataset files:** 70.97 GB
- **Size of the generated dataset:** 78.42 GB
- **Total amount of disk used:** 152.26 GB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [0.013342111371457577,
   0.582173764705658,
   -0.31309744715690613,
   -0.6991612911224365,
   -0.5583199858665466,
   0.5187504887580872,
   0.7152731418609619,
   ...
   -0.5385938286781311,
   0.8093984127044678,
   -0.4741983711719513]}
```

#### psgs_w100.nq.exact

- **Size of downloaded dataset files:** 70.97 GB
- **Size of the generated dataset:** 78.42 GB
- **Total amount of disk used:** 187.38 GB

An example of 'train' looks as follows.
```
This example was too long and was cropped:

{'id': '1',
 'text': 'Aaron Aaron ( or ; "Ahärôn") is a prophet, high priest, and the brother of Moses in the Abrahamic religions. Knowledge of Aaron, along with his brother Moses, comes exclusively from religious texts, such as the Bible and Quran. The Hebrew Bible relates that, unlike Moses, who grew up in the Egyptian royal court, Aaron and his elder sister Miriam remained with their kinsmen in the eastern border-land of Egypt (Goshen). When Moses first confronted the Egyptian king about the Israelites, Aaron served as his brother\'s spokesman ("prophet") to the Pharaoh. Part of the Law (Torah) that Moses received from'],
 'title': 'Aaron',
 'embeddings': [0.013342111371457577,
   0.582173764705658,
   -0.31309744715690613,
   -0.6991612911224365,
   -0.5583199858665466,
   0.5187504887580872,
   0.7152731418609619,
   ...
   -0.5385938286781311,
   0.8093984127044678,
   -0.4741983711719513]}
```

### Data Fields

The data fields are the same among all splits.

#### psgs_w100.multiset.compressed
- `id`: a `string` feature.
- `text`: a `string` feature.
- `title`: a `string` feature.
- `embeddings`: a `list` of `float32` features.

#### psgs_w100.multiset.exact
- `id`: a `string` feature.
- `text`: a `string` feature.
- `title`: a `string` feature.
- `embeddings`: a `list` of `float32` features.

#### psgs_w100.multiset.no_index
- `id`: a `string` feature.
- `text`: a `string` feature.
- `title`: a `string` feature.
- `embeddings`: a `list` of `float32` features.

#### psgs_w100.nq.compressed
- `id`: a `string` feature.
- `text`: a `string` feature.
- `title`: a `string` feature.
- `embeddings`: a `list` of `float32` features.

#### psgs_w100.nq.exact
- `id`: a `string` feature.
- `text`: a `string` feature.
- `title`: a `string` feature.
- `embeddings`: a `list` of `float32` features.

### Data Splits

|            name             | train  |
|-----------------------------|-------:|
|psgs_w100.multiset.compressed|21015300|
|psgs_w100.multiset.exact     |21015300|
|psgs_w100.multiset.no_index  |21015300|
|psgs_w100.nq.compressed      |21015300|
|psgs_w100.nq.exact           |21015300|

## Dataset Creation

### Curation Rationale

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the source language producers?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Annotations

#### Annotation process

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

#### Who are the annotators?

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Personal and Sensitive Information

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Discussion of Biases

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Other Known Limitations

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

## Additional Information

### Dataset Curators

[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Licensing Information

DPR is CC-BY-NC 4.0 licensed: https://github.com/facebookresearch/DPR/blob/main/LICENSE

### Citation Information

```
@inproceedings{karpukhin-etal-2020-dense,
    title = "Dense Passage Retrieval for Open-Domain Question Answering",
    author = "Karpukhin, Vladimir and Oguz, Barlas and Min, Sewon and Lewis, Patrick and Wu, Ledell and Edunov, Sergey and Chen, Danqi and Yih, Wen-tau",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-main.550",
    doi = "10.18653/v1/2020.emnlp-main.550",
    pages = "6769--6781",
}
```


### Contributions

Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@lhoestq](https://github.com/lhoestq) for adding this dataset.
task_categories:fill-mask task_categories:text-generation task_ids:language-modeling task_ids:masked-language-modeling annotations_creators:no-annotation language_creators:crowdsourced multilinguality:multilingual size_categories:10M<n<100M source_datasets:original language:en license:cc-by-nc-4.0 text-search arxiv:2004.04906 region:us
{"annotations_creators": ["no-annotation"], "language_creators": ["crowdsourced"], "language": ["en"], "license": "cc-by-nc-4.0", "multilinguality": ["multilingual"], "size_categories": ["10M<n<100M"], "source_datasets": ["original"], "task_categories": ["fill-mask", "text-generation"], "task_ids": ["language-modeling", "masked-language-modeling"], "pretty_name": "Wiki-DPR", "tags": ["text-search"], "dataset_info": [{"config_name": "psgs_w100.nq.exact", "features": [{"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "embeddings", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 78419281788, "num_examples": 21015300}], "download_size": 70965697456, "dataset_size": 78419281788}, {"config_name": "psgs_w100.nq.compressed", "features": [{"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "embeddings", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 78419281788, "num_examples": 21015300}], "download_size": 70965697456, "dataset_size": 78419281788}, {"config_name": "psgs_w100.nq.no_index", "features": [{"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "embeddings", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 78419281788, "num_examples": 21015300}], "download_size": 70965697456, "dataset_size": 78419281788}, {"config_name": "psgs_w100.multiset.exact", "features": [{"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "embeddings", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 78419281788, "num_examples": 21015300}], "download_size": 70965697456, "dataset_size": 78419281788}, {"config_name": "psgs_w100.multiset.compressed", "features": [{"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "embeddings", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 78419281788, "num_examples": 21015300}], "download_size": 70965697456, "dataset_size": 78419281788}, {"config_name": "psgs_w100.multiset.no_index", "features": [{"name": "id", "dtype": "string"}, {"name": "text", "dtype": "string"}, {"name": "title", "dtype": "string"}, {"name": "embeddings", "sequence": "float32"}], "splits": [{"name": "train", "num_bytes": 78419281788, "num_examples": 21015300}], "download_size": 70965697456, "dataset_size": 78419281788}]}
TAGS
#task_categories-fill-mask #task_categories-text-generation #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-no-annotation #language_creators-crowdsourced #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-English #license-cc-by-nc-4.0 #text-search #arxiv-2004.04906 #region-us 

Dataset Card for "wiki\_dpr"
============================


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


* Repository: URL
* Paper: URL
* Point of Contact:
* Size of downloaded dataset files: 425.79 GB
* Size of the generated dataset: 470.52 GB
* Total amount of disk used: 978.05 GB


### Dataset Summary


This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.


The wikipedia dump is the one from Dec. 20, 2018.


There are two types of DPR embeddings based on two different models:


* 'nq': the model is trained on the Natural Questions dataset
* 'multiset': the model is trained on multiple datasets


Additionally, a FAISS index can be created from the embeddings:


* 'exact': with an exact FAISS index (high RAM usage)
* 'compressed': with a compressed FAISS index (approximate, but lower RAM usage)
* 'no\_index': without FAISS index


Finally, there is the possibility of generating the dataset without the embeddings:


* 'no\_embeddings'


### Supported Tasks and Leaderboards


### Languages


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


### Data Instances


Each instance contains a paragraph of at most 100 words, as well as the title of the wikipedia page it comes from, and the DPR embedding (a 768-d vector).


#### psgs\_w100.multiset.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows.


#### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows.


#### psgs\_w100.multiset.no\_index


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 149.38 GB


An example of 'train' looks as follows.


#### psgs\_w100.nq.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows.


#### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows.


### Data Fields


The data fields are the same among all splits.


#### psgs\_w100.multiset.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.


#### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.


#### psgs\_w100.multiset.no\_index


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.


#### psgs\_w100.nq.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.


#### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.


### 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


DPR is CC-BY-NC 4.0 licensed: URL


### Contributions


Thanks to @thomwolf, @lewtun, @lhoestq for adding this dataset.



### Dataset Summary


This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.


The wikipedia dump is the one from Dec. 20, 2018.


There are two types of DPR embeddings based on two different models:


* 'nq': the model is trained on the Natural Questions dataset
* 'multiset': the model is trained on multiple datasets


Additionally, a FAISS index can be created from the embeddings:


* 'exact': with an exact FAISS index (high RAM usage)
* 'compressed': with a compressed FAISS index (approximate, but lower RAM usage)
* 'no\_index': without FAISS index


Finally, there is the possibility of generating the dataset without the embeddings:


* 'no\_embeddings' ### Supported Tasks and Leaderboards ### Languages


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


Each instance contains a paragraph of at most 100 words, as well as the title of the wikipedia page it comes from, and the DPR embedding (a 768-d vector). #### psgs\_w100.multiset.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows. #### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows. #### psgs\_w100.multiset.no\_index


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 149.38 GB


An example of 'train' looks as follows. #### psgs\_w100.nq.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows. #### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### psgs\_w100.multiset.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.multiset.no\_index


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.nq.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. ### 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


DPR is CC-BY-NC 4.0 licensed: URL ### Contributions


Thanks to @thomwolf, @lewtun, @lhoestq for adding this dataset.
TAGS
#task_categories-fill-mask #task_categories-text-generation #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-no-annotation #language_creators-crowdsourced #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-English #license-cc-by-nc-4.0 #text-search #arxiv-2004.04906 #region-us 
 ### Dataset Summary


This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.


The wikipedia dump is the one from Dec. 20, 2018.


There are two types of DPR embeddings based on two different models:


* 'nq': the model is trained on the Natural Questions dataset
* 'multiset': the model is trained on multiple datasets


Additionally, a FAISS index can be created from the embeddings:


* 'exact': with an exact FAISS index (high RAM usage)
* 'compressed': with a compressed FAISS index (approximate, but lower RAM usage)
* 'no\_index': without FAISS index


Finally, there is the possibility of generating the dataset without the embeddings:


* 'no\_embeddings' ### Supported Tasks and Leaderboards ### Languages


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


Each instance contains a paragraph of at most 100 words, as well as the title of the wikipedia page it comes from, and the DPR embedding (a 768-d vector). #### psgs\_w100.multiset.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows. #### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows. #### psgs\_w100.multiset.no\_index


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 149.38 GB


An example of 'train' looks as follows. #### psgs\_w100.nq.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows. #### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows. ### Data Fields


The data fields are the same among all splits. #### psgs\_w100.multiset.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.multiset.no\_index


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.nq.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. #### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features. ### 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


DPR is CC-BY-NC 4.0 licensed: URL ### Contributions


Thanks to @thomwolf, @lewtun, @lhoestq for adding this dataset.
passage: TAGS
#task_categories-fill-mask #task_categories-text-generation #task_ids-language-modeling #task_ids-masked-language-modeling #annotations_creators-no-annotation #language_creators-crowdsourced #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-English #license-cc-by-nc-4.0 #text-search #arxiv-2004.04906 #region-us 
### Dataset Summary


This is the wikipedia split used to evaluate the Dense Passage Retrieval (DPR) model.
It contains 21M passages from wikipedia along with their DPR embeddings.
The wikipedia articles were split into multiple, disjoint text blocks of 100 words as passages.


The wikipedia dump is the one from Dec. 20, 2018.


There are two types of DPR embeddings based on two different models:


* 'nq': the model is trained on the Natural Questions dataset
* 'multiset': the model is trained on multiple datasets


Additionally, a FAISS index can be created from the embeddings:


* 'exact': with an exact FAISS index (high RAM usage)
* 'compressed': with a compressed FAISS index (approximate, but lower RAM usage)
* 'no\_index': without FAISS index


Finally, there is the possibility of generating the dataset without the embeddings:


* 'no\_embeddings'### Supported Tasks and Leaderboards### Languages


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


Each instance contains a paragraph of at most 100 words, as well as the title of the wikipedia page it comes from, and the DPR embedding (a 768-d vector).#### psgs\_w100.multiset.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows. passage: #### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows.#### psgs\_w100.multiset.no\_index


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 149.38 GB


An example of 'train' looks as follows.#### psgs\_w100.nq.compressed


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 152.26 GB


An example of 'train' looks as follows.#### psgs\_w100.URL


* Size of downloaded dataset files: 70.97 GB
* Size of the generated dataset: 78.42 GB
* Total amount of disk used: 187.38 GB


An example of 'train' looks as follows.### Data Fields


The data fields are the same among all splits.#### psgs\_w100.multiset.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.#### psgs\_w100.URL


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.#### psgs\_w100.multiset.no\_index


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.#### psgs\_w100.nq.compressed


* 'id': a 'string' feature.
* 'text': a 'string' feature.
* 'title': a 'string' feature.
* 'embeddings': a 'list' of 'float32' features.