
# preprocessed version of rcds/wikipedia-persons-masked

## Table of Contents

- [Table of Contents](#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 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:**
- **Repository:** 
- **Paper:** 
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

Contains ~70k pages from wikipedia, each describing a person. For each page, the person described in the text
is masked with a <mask> token. The ground truth for every mask is provided.
Each row contains a part of a wiki page, specified by the size parameter which limits the maximum size in number of tokens per text chunk.
for each chunk the expected name for each mask is given.

### Supported Tasks and Leaderboards

The dataset supports the tasks of fill-mask, but can also be used for other tasks such as question answering,
e.g. "Who is <mask>?"

### Languages

*english only*

## Dataset Structure

In /data find different versions of the full dataset, with original and paraphrased versions as well as chunked to 4096 and 512 tokens.

Use the dataset like this:
```python
from datasets import load_dataset

dataset = load_dataset('rcds/wikipedia-persons-masked', split='train', type='original', size='512')
```

### Data Fields

Columns are:
- texts: the text chunks
- masks: the names for each of the masks in the chunks

### Data Splits

There are no splits, only a default train.

## Dataset Creation

Created by using the tokenizer from allenai/longformer-base-4096 for the 4096 token per chunk version,
and the xml-roberta-large tokenizer for the 512 token version. Chunks are split to fit those token sizes,
with the splits ensuring no words are split in half.
Possible improvements: Last chunk of a page might be much shorter, could join part of the previous one to have more tokens
in the last chunk.

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]


### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

```
TODO add citation
```

### Contributions

Thanks to [@skatinger](https://github.com/skatinger) for adding this dataset.

task_categories:fill-mask annotations_creators:other language_creators:found multilinguality:multilingual size_categories:10M<n<100M source_datasets:original language:en license:cc-by-4.0 region:us
{"annotations_creators": ["other"], "language_creators": ["found"], "language": ["en"], "license": ["cc-by-4.0"], "multilinguality": ["multilingual"], "size_categories": ["10M<n<100M"], "source_datasets": ["original"], "task_categories": ["fill-mask"], "pretty_name": "wikipedia pages chunked for fill-mask"}
TAGS
#task_categories-fill-mask #annotations_creators-other #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-English #license-cc-by-4.0 #region-us 


# preprocessed version of rcds/wikipedia-persons-masked

## Table of Contents

- Table of Contents
- Dataset Description
    - Dataset Summary
    - Supported Tasks and Leaderboards
    - Languages
- Dataset Structure
    - 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:
- Repository: 
- Paper: 
- Leaderboard:
- Point of Contact:

### Dataset Summary

Contains ~70k pages from wikipedia, each describing a person. For each page, the person described in the text
is masked with a <mask> token. The ground truth for every mask is provided.
Each row contains a part of a wiki page, specified by the size parameter which limits the maximum size in number of tokens per text chunk.
for each chunk the expected name for each mask is given.

### Supported Tasks and Leaderboards

The dataset supports the tasks of fill-mask, but can also be used for other tasks such as question answering,
e.g. "Who is <mask>?"

### Languages

*english only*

## Dataset Structure

In /data find different versions of the full dataset, with original and paraphrased versions as well as chunked to 4096 and 512 tokens.

Use the dataset like this:


### Data Fields

Columns are:
- texts: the text chunks
- masks: the names for each of the masks in the chunks

### Data Splits

There are no splits, only a default train.

## Dataset Creation

Created by using the tokenizer from allenai/longformer-base-4096 for the 4096 token per chunk version,
and the xml-roberta-large tokenizer for the 512 token version. Chunks are split to fit those token sizes,
with the splits ensuring no words are split in half.
Possible improvements: Last chunk of a page might be much shorter, could join part of the previous one to have more tokens
in the last chunk.

### 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







### Contributions

Thanks to @skatinger for adding this dataset.

# preprocessed version of rcds/wikipedia-persons-masked ## Table of Contents

- Table of Contents
- Dataset Description
    - Dataset Summary
    - Supported Tasks and Leaderboards
    - Languages
- Dataset Structure
    - 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:
- Repository: 
- Paper: 
- Leaderboard:
- Point of Contact: ### Dataset Summary

Contains ~70k pages from wikipedia, each describing a person. For each page, the person described in the text
is masked with a <mask> token. The ground truth for every mask is provided.
Each row contains a part of a wiki page, specified by the size parameter which limits the maximum size in number of tokens per text chunk.
for each chunk the expected name for each mask is given. ### Supported Tasks and Leaderboards

The dataset supports the tasks of fill-mask, but can also be used for other tasks such as question answering,
e.g. "Who is <mask>?" ### Languages

*english only* ## Dataset Structure

In /data find different versions of the full dataset, with original and paraphrased versions as well as chunked to 4096 and 512 tokens.

Use the dataset like this: ### Data Fields

Columns are:
- texts: the text chunks
- masks: the names for each of the masks in the chunks ### Data Splits

There are no splits, only a default train. ## Dataset Creation

Created by using the tokenizer from allenai/longformer-base-4096 for the 4096 token per chunk version,
and the xml-roberta-large tokenizer for the 512 token version. Chunks are split to fit those token sizes,
with the splits ensuring no words are split in half.
Possible improvements: Last chunk of a page might be much shorter, could join part of the previous one to have more tokens
in the last chunk. ### 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 ### Contributions

Thanks to @skatinger for adding this dataset.
TAGS
#task_categories-fill-mask #annotations_creators-other #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-English #license-cc-by-4.0 #region-us 
 # preprocessed version of rcds/wikipedia-persons-masked ## Table of Contents

- Table of Contents
- Dataset Description
    - Dataset Summary
    - Supported Tasks and Leaderboards
    - Languages
- Dataset Structure
    - 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:
- Repository: 
- Paper: 
- Leaderboard:
- Point of Contact: ### Dataset Summary

Contains ~70k pages from wikipedia, each describing a person. For each page, the person described in the text
is masked with a <mask> token. The ground truth for every mask is provided.
Each row contains a part of a wiki page, specified by the size parameter which limits the maximum size in number of tokens per text chunk.
for each chunk the expected name for each mask is given. ### Supported Tasks and Leaderboards

The dataset supports the tasks of fill-mask, but can also be used for other tasks such as question answering,
e.g. "Who is <mask>?" ### Languages

*english only* ## Dataset Structure

In /data find different versions of the full dataset, with original and paraphrased versions as well as chunked to 4096 and 512 tokens.

Use the dataset like this: ### Data Fields

Columns are:
- texts: the text chunks
- masks: the names for each of the masks in the chunks ### Data Splits

There are no splits, only a default train. ## Dataset Creation

Created by using the tokenizer from allenai/longformer-base-4096 for the 4096 token per chunk version,
and the xml-roberta-large tokenizer for the 512 token version. Chunks are split to fit those token sizes,
with the splits ensuring no words are split in half.
Possible improvements: Last chunk of a page might be much shorter, could join part of the previous one to have more tokens
in the last chunk. ### 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 ### Contributions

Thanks to @skatinger for adding this dataset.
passage: TAGS
#task_categories-fill-mask #annotations_creators-other #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-English #license-cc-by-4.0 #region-us 
# preprocessed version of rcds/wikipedia-persons-masked## Table of Contents

- Table of Contents
- Dataset Description
    - Dataset Summary
    - Supported Tasks and Leaderboards
    - Languages
- Dataset Structure
    - 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:
- Repository: 
- Paper: 
- Leaderboard:
- Point of Contact:### Dataset Summary

Contains ~70k pages from wikipedia, each describing a person. For each page, the person described in the text
is masked with a <mask> token. The ground truth for every mask is provided.
Each row contains a part of a wiki page, specified by the size parameter which limits the maximum size in number of tokens per text chunk.
for each chunk the expected name for each mask is given.### Supported Tasks and Leaderboards

The dataset supports the tasks of fill-mask, but can also be used for other tasks such as question answering,
e.g. "Who is <mask>?"### Languages

*english only*## Dataset Structure

In /data find different versions of the full dataset, with original and paraphrased versions as well as chunked to 4096 and 512 tokens.

Use the dataset like this:### Data Fields

Columns are:
- texts: the text chunks
- masks: the names for each of the masks in the chunks### Data Splits

There are no splits, only a default train.