
# Dataset Card for "nq"

## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
- [Additional Information](#additional-information)
  - [Licensing Information](#licensing-information)

## Dataset Description


- **Homepage:** [https://ai.google.com/research/NaturalQuestions](https://ai.google.com/research/NaturalQuestions)

### Dataset Summary

This is a modified version of the original Natural Questions (nq) dataset for qa tasks. The original is availabe [here](https://ai.google.com/research/NaturalQuestions).

Each sample was preprocessed into a squadlike format. The context was shortened from an entire wikipedia article into the passage containing the answer. 
## Dataset Structure

### Data Instances

An example of 'train' looks as follows.

```json
{
    "context": "The 2017 Major League Baseball All - Star Game was the 88th edition of the Major League Baseball All Star Game. The game was",
    "question": "where is the 2017 baseball all-star game being played",
    "answers":
        {
          "text":["Marlins Park"],
          "answer_start":[171]
        }
}
```

### Data Fields

The data fields are the same among all splits.

- `question`: a `string` feature.
- `context`: a `string` feature.
- `answers`: a dictionary feature containing:
  - `text`: a `string` feature.
  - `answer_start`: a `int32` feature.

## Additional Information

### Licensing Information

This dataset is distributed under the cc-by-sa-3.0 license.
task_categories:question-answering task_categories:sentence-similarity task_categories:feature-extraction language:en license:cc-by-sa-3.0 region:us
{"language": ["en"], "license": "cc-by-sa-3.0", "task_categories": ["question-answering", "sentence-similarity", "feature-extraction"]}
TAGS
#task_categories-question-answering #task_categories-sentence-similarity #task_categories-feature-extraction #language-English #license-cc-by-sa-3.0 #region-us 


# Dataset Card for "nq"

## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
  - Data Instances
  - Data Fields
- Additional Information
  - Licensing Information

## Dataset Description


- Homepage: URL

### Dataset Summary

This is a modified version of the original Natural Questions (nq) dataset for qa tasks. The original is availabe here.

Each sample was preprocessed into a squadlike format. The context was shortened from an entire wikipedia article into the passage containing the answer. 
## Dataset Structure

### Data Instances

An example of 'train' looks as follows.



### Data Fields

The data fields are the same among all splits.

- 'question': a 'string' feature.
- 'context': a 'string' feature.
- 'answers': a dictionary feature containing:
  - 'text': a 'string' feature.
  - 'answer_start': a 'int32' feature.

## Additional Information

### Licensing Information

This dataset is distributed under the cc-by-sa-3.0 license.
# Dataset Card for "nq" ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
  - Data Instances
  - Data Fields
- Additional Information
  - Licensing Information ## Dataset Description


- Homepage: URL ### Dataset Summary

This is a modified version of the original Natural Questions (nq) dataset for qa tasks. The original is availabe here.

Each sample was preprocessed into a squadlike format. The context was shortened from an entire wikipedia article into the passage containing the answer. ## Dataset Structure ### Data Instances

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

The data fields are the same among all splits.

- 'question': a 'string' feature.
- 'context': a 'string' feature.
- 'answers': a dictionary feature containing:
  - 'text': a 'string' feature.
  - 'answer_start': a 'int32' feature. ## Additional Information ### Licensing Information

This dataset is distributed under the cc-by-sa-3.0 license.
TAGS
#task_categories-question-answering #task_categories-sentence-similarity #task_categories-feature-extraction #language-English #license-cc-by-sa-3.0 #region-us 
 # Dataset Card for "nq" ## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
  - Data Instances
  - Data Fields
- Additional Information
  - Licensing Information ## Dataset Description


- Homepage: URL ### Dataset Summary

This is a modified version of the original Natural Questions (nq) dataset for qa tasks. The original is availabe here.

Each sample was preprocessed into a squadlike format. The context was shortened from an entire wikipedia article into the passage containing the answer. ## Dataset Structure ### Data Instances

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

The data fields are the same among all splits.

- 'question': a 'string' feature.
- 'context': a 'string' feature.
- 'answers': a dictionary feature containing:
  - 'text': a 'string' feature.
  - 'answer_start': a 'int32' feature. ## Additional Information ### Licensing Information

This dataset is distributed under the cc-by-sa-3.0 license.
passage: TAGS
#task_categories-question-answering #task_categories-sentence-similarity #task_categories-feature-extraction #language-English #license-cc-by-sa-3.0 #region-us 
# Dataset Card for "nq"## Table of Contents
- Table of Contents
- Dataset Description
  - Dataset Summary
- Dataset Structure
  - Data Instances
  - Data Fields
- Additional Information
  - Licensing Information## Dataset Description


- Homepage: URL### Dataset Summary

This is a modified version of the original Natural Questions (nq) dataset for qa tasks. The original is availabe here.

Each sample was preprocessed into a squadlike format. The context was shortened from an entire wikipedia article into the passage containing the answer.## Dataset Structure### Data Instances

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

The data fields are the same among all splits.

- 'question': a 'string' feature.
- 'context': a 'string' feature.
- 'answers': a dictionary feature containing:
  - 'text': a 'string' feature.
  - 'answer_start': a 'int32' feature.## Additional Information### Licensing Information

This dataset is distributed under the cc-by-sa-3.0 license.