---
dataset_info:
  features:
  - name: questions
    list:
    - name: answer
      struct:
      - name: answer_index
        dtype: int64
      - name: answer_text
        dtype: string
    - name: options
      sequence: string
    - name: question
      dtype: string
    - name: question_type
      dtype: string
  - name: article
    dtype: string
  - name: id
    dtype: string
  splits:
  - name: train_all
    num_bytes: 63952721
    num_examples: 25137
  - name: train_middle
    num_bytes: 12480455
    num_examples: 6409
  - name: dev_high
    num_bytes: 2790766
    num_examples: 1021
  - name: dev_middle
    num_bytes: 712198
    num_examples: 368
  - name: test_middle
    num_bytes: 714595
    num_examples: 362
  - name: train_high
    num_bytes: 51472267
    num_examples: 18728
  - name: test_high
    num_bytes: 2850894
    num_examples: 1045
  download_size: 33312158
  dataset_size: 134973896
---
# Dataset Card for "QGG-RACE Dataset"

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

- GitHub Repository: N/A
- Paper: N/A
- Leaderboard: N/A
- Point of Contact: N/A

## Dataset Summary

QGG-RACE Dataset is a subset of RACE, containing three types of questions: Factoid, Cloze, and Summarization.

Dataset Download: [GitHub Release](https://github.com/p208p2002/QGG-RACE-dataset/releases/download/v1.0/qgg-dataset.zip)

Data Statistics:

Types         | Examples                                   | Train | Dev  | Test
------------- | ------------------------------------------ | ----- | ---- | ----
Cloze         | Yingying is Wangwang's _ .                 | 43167 | 2405 | 2462
Factiod       | What can Mimi do?                          | 18405 | 1030 | 944 
Summarization | According to this passage we know that _ . | 3004  | 175  | 184 


## Supported Tasks and Leaderboards

- Question Generation
- Reading Comprehension
- Text Summarization

## Languages

The dataset is in English.

## Dataset Structure

### Data Instances

An example data instance from the dataset is shown below:

```json
{
    "answers": [
        "D",
        "A",
        "B",
        "C"
    ],
    "options": [
        [
            "States",
            "Doubts",
            "Confirms",
            "Removes"
        ],
        [
            "shows the kind of male birds females seek out.",
            "indicates the wandering albatross is the most faithful.",
            "is based on Professor Stutchbury's 20 years' research.",
            "suggests that female birds select males near their home."
        ],
        [
            "young birds' quality depends on their feather.",
            "some male birds care for others' young as their own.",
            "female birds go to find males as soon as autumn comes.",
            "female birds are responsible for feeding the hungry babies."
        ],
        [
            "A book about love-birds.",
            "Birds' living habits and love life",
            "The fact that birds don't love their mates forever.",
            "The factors that influence birds to look for another mate."
        ]
    ],
    "questions": [
        "What does the underline word \"dispels\" mean?",
        "The book The Private Lives of Birds _ .",
        "According to the passage, we can infer that _ .",
        "What is the passage mainly about?"
    ],
    "article": "Birds are not as loyal to their partners as you might think ...",
    "id": "high11327.txt",
    "factoid_questions": [
        "What does the underline word \"dispels\" mean?"
    ],
    "cloze_questions": [
        "The book The Private Lives of Birds _ ."
    ],
    "summarization_questions": [
        "According to the passage, we can infer that _ ."
    ]
}

```

## Data Fields

- id: Unique identifier for the example.
- article: The main text passage.
- questions: List of questions related to the passage.
- options: List of answer options for each question.
- answers: Indexes of the correct answers for each question.
- factoid_questions: List of factoid questions.
- cloze_questions: List of cloze questions.
- summarization_questions: List of summarization questions.

### Data Splits

- Train: Contains 65,576 examples.
- Dev: Contains 3,610 examples.
- Test: Contains 3,590 examples.

## Dataset Creation

### Curation Rationale

QGG-RACE dataset is created as a subset of RACE, focusing on three types of questions: Factoid, Cloze, and Summarization. This dataset is intended to facilitate research in question generation and reading comprehension.

### Source Data

#### Initial Data Collection and Normalization

QGG-RACE dataset is derived from RACE dataset.

#### Who are the source language producers?

The source language producers are the authors of the RACE dataset.

### Annotations

#### Annotation process

The dataset is annotated with questions and their corresponding answer options.

#### Who are the annotators?

The annotators are the authors of the RACE dataset.

### Personal and Sensitive Information

The dataset does not contain any personal or sensitive information.

## Considerations for Using the Data

### Social Impact of Dataset

The QGG-RACE dataset can be used for research in question generation and reading comprehension, leading to improvements in these fields.

### Discussion of Biases

The dataset may inherit some biases from the RACE dataset as it is a subset of it.

### Other Known Limitations

No other known limitations.

## Additional Information

### Dataset Curators

The QGG-RACE dataset is curated by the authors of the QGG-RACE dataset GitHub repository.

### Licensing Information

The dataset is released under the [CC BY 4.0 License](https://creativecommons.org/licenses/by/4.0/).

### Citation Information

No citation information is available for the QGG-RACE dataset.

### Contributions

Thanks to @p208p2002 for creating the QGG-RACE dataset.