# AutoTrain Dataset for project: boolq

## Dataset Description

This dataset has been automatically processed by AutoTrain for project boolq.

### Languages

The BCP-47 code for the dataset's language is en.

## Dataset Structure

### Data Instances

A sample from this dataset looks as follows:

```json
[
  {
    "context": "is an abstract the same as a summary",
    "question": "Abstract (summary) -- An abstract is a brief summary of a research article, thesis, review, conference proceeding, or any in-depth analysis of a particular subject and is often used to help the reader quickly ascertain the paper's purpose. When used, an abstract always appears at the beginning of a manuscript or typescript, acting as the point-of-entry for any given academic paper or patent application. Abstracting and indexing services for various academic disciplines are aimed at compiling a body of literature for that particular subject.",
    "answers.text": [
      "757"
    ],
    "answers.answer_start": [
      -1
    ],
    "feat_id": null,
    "feat_title": null
  },
  {
    "context": "was the opening of jumeirah beach park in 2009",
    "question": "Jumeirah Beach Hotel -- Jumeirah Beach Hotel is a hotel in Dubai, United Arab Emirates. The hotel, which opened in 1997, is operated by the Dubai-based hotelier Jumeirah. The hotel contains 598 rooms and suites, 19 beachfront villas, and 20 restaurants and bars. This wave-shaped hotel complements the sail-shaped Burj Al Arab, which is adjacent to the Jumeirah Beach Hotel.",
    "answers.text": [
      "2817"
    ],
    "answers.answer_start": [
      -1
    ],
    "feat_id": null,
    "feat_title": null
  }
]
```

### Dataset Fields

The dataset has the following fields (also called "features"):

```json
{
  "context": "Value(dtype='string', id=None)",
  "question": "Value(dtype='string', id=None)",
  "answers.text": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
  "answers.answer_start": "Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None)",
  "feat_id": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)",
  "feat_title": "Sequence(feature=Value(dtype='string', id=None), length=-1, id=None)"
}
```

### Dataset Splits

This dataset is split into a train and validation split. The split sizes are as follow:

| Split name   | Num samples         |
| ------------ | ------------------- |
| train        | 10786 |
| valid        | 135411 |

language:en doi:10.57967/hf/0175 region:us
{"language": ["en"]}
TAGS
#language-English #doi-10.57967/hf/0175 #region-us 

AutoTrain Dataset for project: boolq
====================================


Dataset Description
-------------------


This dataset has been automatically processed by AutoTrain for project boolq.


### Languages


The BCP-47 code for the dataset's language is en.


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


### Data Instances


A sample from this dataset looks as follows:


### Dataset Fields


The dataset has the following fields (also called "features"):


### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:




### Languages


The BCP-47 code for the dataset's language is en.


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


A sample from this dataset looks as follows: ### Dataset Fields


The dataset has the following fields (also called "features"): ### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:
TAGS
#language-English #doi-10.57967/hf/0175 #region-us 
 ### Languages


The BCP-47 code for the dataset's language is en.


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


A sample from this dataset looks as follows: ### Dataset Fields


The dataset has the following fields (also called "features"): ### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow:
passage: TAGS
#language-English #doi-10.57967/hf/0175 #region-us 
### Languages


The BCP-47 code for the dataset's language is en.


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


A sample from this dataset looks as follows:### Dataset Fields


The dataset has the following fields (also called "features"):### Dataset Splits


This dataset is split into a train and validation split. The split sizes are as follow: