Update README.md

README.md

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   download_size: 81569780
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-# Dataset Card for "EQG-RACE-PLUS"
+# Dataset Card for "QGG-RACE Dataset"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+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.