
# Dataset Card for CrosswordQA

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-instances)
  - [Data Splits](#data-instances)
- [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)

## Dataset Description

- **Homepage:** [Needs More Information]
- **Repository:** https://github.com/albertkx/Berkeley-Crossword-Solver
- **Paper:** [Needs More Information]
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Albert Xu](mailto:albertxu@usc.edu) and [Eshaan Pathak](mailto:eshaanpathak@berkeley.edu)

### Dataset Summary

The CrosswordQA dataset is a set of over 6 million clue-answer pairs scraped from the New York Times and many other crossword publishers. The dataset was created to train the Berkeley Crossword Solver's QA model. See our paper for more information. Answers are automatically segmented (e.g., BUZZLIGHTYEAR -> Buzz Lightyear), and thus may occasionally be segmented incorrectly.

### Supported Tasks and Leaderboards

[Needs More Information]

### Languages

[Needs More Information]

## Dataset Structure

### Data Instances

```
{
  "id": 0,
  "clue": "Clean-up target",
  "answer": "mess"
}
```

### Data Fields

[Needs More Information]

### Data Splits

[Needs More Information]

## 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

[Needs More Information]

### Licensing Information

[Needs More Information]

### Citation Information

[Needs More Information]
task_categories:question-answering task_ids:open-domain-qa annotations_creators:no-annotation language_creators:found multilinguality:monolingual size_categories:1M<n<10M language:en license:unknown region:us
{"annotations_creators": ["no-annotation"], "language_creators": ["found"], "language": ["en"], "license": ["unknown"], "multilinguality": ["monolingual"], "size_categories": ["1M<n<10M"], "task_categories": ["question-answering"], "task_ids": ["open-domain-qa"]}
TAGS
#task_categories-question-answering #task_ids-open-domain-qa #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #language-English #license-unknown #region-us 


# Dataset Card for CrosswordQA

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - 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

## Dataset Description

- Homepage: 
- Repository: URL
- Paper: 
- Leaderboard: 
- Point of Contact: Albert Xu and Eshaan Pathak

### Dataset Summary

The CrosswordQA dataset is a set of over 6 million clue-answer pairs scraped from the New York Times and many other crossword publishers. The dataset was created to train the Berkeley Crossword Solver's QA model. See our paper for more information. Answers are automatically segmented (e.g., BUZZLIGHTYEAR -> Buzz Lightyear), and thus may occasionally be segmented incorrectly.

### Supported Tasks and Leaderboards



### Languages



## Dataset Structure

### 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






# Dataset Card for CrosswordQA ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - 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 ## Dataset Description

- Homepage: 
- Repository: URL
- Paper: 
- Leaderboard: 
- Point of Contact: Albert Xu and Eshaan Pathak ### Dataset Summary

The CrosswordQA dataset is a set of over 6 million clue-answer pairs scraped from the New York Times and many other crossword publishers. The dataset was created to train the Berkeley Crossword Solver's QA model. See our paper for more information. Answers are automatically segmented (e.g., BUZZLIGHTYEAR -> Buzz Lightyear), and thus may occasionally be segmented incorrectly. ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### 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
TAGS
#task_categories-question-answering #task_ids-open-domain-qa #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #language-English #license-unknown #region-us 
 # Dataset Card for CrosswordQA ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - 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 ## Dataset Description

- Homepage: 
- Repository: URL
- Paper: 
- Leaderboard: 
- Point of Contact: Albert Xu and Eshaan Pathak ### Dataset Summary

The CrosswordQA dataset is a set of over 6 million clue-answer pairs scraped from the New York Times and many other crossword publishers. The dataset was created to train the Berkeley Crossword Solver's QA model. See our paper for more information. Answers are automatically segmented (e.g., BUZZLIGHTYEAR -> Buzz Lightyear), and thus may occasionally be segmented incorrectly. ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### 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
passage: TAGS
#task_categories-question-answering #task_ids-open-domain-qa #annotations_creators-no-annotation #language_creators-found #multilinguality-monolingual #size_categories-1M<n<10M #language-English #license-unknown #region-us 
# Dataset Card for CrosswordQA## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks
  - 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## Dataset Description

- Homepage: 
- Repository: URL
- Paper: 
- Leaderboard: 
- Point of Contact: Albert Xu and Eshaan Pathak### Dataset Summary

The CrosswordQA dataset is a set of over 6 million clue-answer pairs scraped from the New York Times and many other crossword publishers. The dataset was created to train the Berkeley Crossword Solver's QA model. See our paper for more information. Answers are automatically segmented (e.g., BUZZLIGHTYEAR -> Buzz Lightyear), and thus may occasionally be segmented incorrectly.### Supported Tasks and Leaderboards### Languages## Dataset Structure### 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