# Dataset Card for "chatgpt-news-articles"

## Dataset Description
- **Homepage:**
- **Repository:** [ChatGPT CNN / DailyMail Dataset repository]()
- **Original Dataset Paper:** [Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond](https://papers.nips.cc/paper/5945-teaching-machines-to-read-and-comprehend.pdf), [Get To The Point: Summarization with Pointer-Generator Networks](https://www.aclweb.org/anthology/K16-1028.pdf)
- **Point of Contact:** [Sarthak Anand](mailto: isarth23@sgmail.com)


### Dataset Summary
The ChatGPT CNN / DailyMail Dataset is a small sample of the original CNN / DailyMaily English-language dataset containing 25k unique news articles. For each corresponding article written by journalists at CNN and the Daily Mail, there is an article written by ChatGPT using the highlights provided by human annotators. The current version supports can be used to study the language comparison between human and ChatGPT news writing. 

### Languages

The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.

## Dataset Structure

### Data Instances

For each instance, there is a string for the article, a string for the highlights, a string for the id, and a string for an article written by ChatGPT

```
{'article': "Michael Phelps has been crowned Male Athlete of the Year for a fifth time at the 2014 USA Swimming Golden Goggle Awards despite being suspended from competition for six months after a drunken driving arrest in September. Phelps was not at the New York ceremony where Keenan Robinson, an official from his training base, accepted the award on his behalf and confirmed Phelps had returned to the pool. The 18-time Olympic gold medallist stepped away from training in early October. Michael Phelps has been crowned Male Athlete of the Year at the 2014 USA Swimming Golden Goggle Awards . Phelps is the most decorated Olympian in sports history, winning 18 Olympic golds during his career . Olympic gold medallist and world record-holder Katie Ledecky capped her memorable 2014 season by claiming three awards, including USA Swimming's Female Athlete of the Year.",
 'highlights': 'Michael Phelps was not present at the New York ceremony . Phelps was handed a six-month suspension by USA Swimming following his arrest for allegedly drink driving last month . Phelps confirmed in October that he would be taking a break from\xa0swimming\xa0to focus on his personal issues . Phelps is the most successful Olympic athlete in history, with 22 medals in total including 18 golds .',
 'id': '95ef5b45d999dc9a78c5efa2de87e84f21912086',
 'chatgpt': 'Michael Phelps, the most successful Olympic athlete in history, was noticeably absent from a ceremony held in New York City yesterday. The reason for the absence is due to a recent six-month suspension handed to Phelps by USA Swimming following his arrest for allegedly drink driving last month. In October, Phelps confirmed that he would be taking a break from swimming in order to focus on his personal issues. The suspension now means that Phelps will not be able to compete in the upcoming World Championships in Kazan, Russia in August. This will be a disappointing blow to his fans across the world as Phelps holds the record for the most Olympic gold medals, with a total of 18. However, Phelps can take this time to focus on his health and address his personal concerns.'}
```

The average token count for the articles and the highlights are provided below:

| Feature    | Mean Word Count |
| ---------- | ---------------- |
| Article    | 358              |
| ChatGPT    | 352              |
| Highlights | 42               |

### Data Fields

- `id`: a string containing the heximal formated SHA1 hash of the url where the story was retrieved from
- `article`: a string containing the news article written by journalists
- `highlights`: a string containing the highlight of the article as written by the article author
- `chatgpt`: a string containing the news article written by ChatGPT

### Data Splits

The CNN/DailyMail dataset has 2 splits: _train_ and _test_. Below are the statistics of the dataset.

| Dataset Split | Number of Instances in Split                |
| ------------- | ------------------------------------------- |
| Train         | 20,000                                      |
| Test          |  5,000                                      |


## Dataset Creation

## ChatGPT Prompt 
The number of words for an article (N) was the same as the original article
```
openai.ChatCompletion.create(
      model="gpt-3.5-turbo",
      messages=[
      {"role": "system", "content": "You are a AI assistant that generates news articles from a summary."},
      {"role": "user", "content": f'Write a news article using the following summary: {HIGHLIGHTS} \n Write about {N} words only'}

        ],)
```


### Source Data

### Original Dataset Curators

The data was originally collected by Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom of Google DeepMind. Tomáš Kočiský and Phil Blunsom are also affiliated with the University of Oxford. They released scripts to collect and process the data into the question answering format. 

Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, and Bing Xiang of IMB Watson and Çağlar Gu̇lçehre of Université de Montréal modified Hermann et al's collection scripts to restore the data to a summary format. They also produced both anonymized and non-anonymized versions.

The code for the non-anonymized version is made publicly available by Abigail See of Stanford University, Peter J. Liu of Google Brain and Christopher D. Manning of Stanford University at <https://github.com/abisee/cnn-dailymail>. The work at Stanford University was supported by the DARPA DEFT ProgramAFRL contract no. FA8750-13-2-0040.


#### Who are the source language producers?

The text was written by journalists at CNN and the Daily Mail and ChatGPT

### Annotations

The dataset does not contain any additional annotations.

#### Annotation process

[N/A]

#### Who are the annotators?

[N/A]

### Personal and Sensitive Information

The original dataset is not anonymized, therefore individuals' names can be found in this dataset as well.

## Considerations for Using the Data

### Social Impact of Dataset

The purpose of this dataset is to access the quality and writing style of ChatGPT for writing news articles using highlights provided by humans and further study the biases if present.

### Discussion of Biases

There have been studies measuring gender bias in the original dataset which could be interesting [Bordia and Bowman (2019)](https://www.aclweb.org/anthology/N19-3002.pdf) 


### Licensing Information

The ChatGPT CNN / Daily Mail dataset uses the same licence as the original dataset, which is  [Apache-2.0 License](http://www.apache.org/licenses/LICENSE-2.0). 



region:us
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TAGS
#region-us 

Dataset Card for "chatgpt-news-articles"
========================================


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


* Homepage:
* Repository: ChatGPT CNN / DailyMail Dataset repository
* Original Dataset Paper: Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond, Get To The Point: Summarization with Pointer-Generator Networks
* Point of Contact: Sarthak Anand


### Dataset Summary


The ChatGPT CNN / DailyMail Dataset is a small sample of the original CNN / DailyMaily English-language dataset containing 25k unique news articles. For each corresponding article written by journalists at CNN and the Daily Mail, there is an article written by ChatGPT using the highlights provided by human annotators. The current version supports can be used to study the language comparison between human and ChatGPT news writing.


### Languages


The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.


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


### Data Instances


For each instance, there is a string for the article, a string for the highlights, a string for the id, and a string for an article written by ChatGPT


The average token count for the articles and the highlights are provided below:



### Data Fields


* 'id': a string containing the heximal formated SHA1 hash of the url where the story was retrieved from
* 'article': a string containing the news article written by journalists
* 'highlights': a string containing the highlight of the article as written by the article author
* 'chatgpt': a string containing the news article written by ChatGPT


### Data Splits


The CNN/DailyMail dataset has 2 splits: *train* and *test*. Below are the statistics of the dataset.



Dataset Creation
----------------


ChatGPT Prompt
--------------


The number of words for an article (N) was the same as the original article


### Source Data


### Original Dataset Curators


The data was originally collected by Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom of Google DeepMind. Tomáš Kočiský and Phil Blunsom are also affiliated with the University of Oxford. They released scripts to collect and process the data into the question answering format.


Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, and Bing Xiang of IMB Watson and Çağlar Gu̇lçehre of Université de Montréal modified Hermann et al's collection scripts to restore the data to a summary format. They also produced both anonymized and non-anonymized versions.


The code for the non-anonymized version is made publicly available by Abigail See of Stanford University, Peter J. Liu of Google Brain and Christopher D. Manning of Stanford University at <URL The work at Stanford University was supported by the DARPA DEFT ProgramAFRL contract no. FA8750-13-2-0040.


#### Who are the source language producers?


The text was written by journalists at CNN and the Daily Mail and ChatGPT


### Annotations


The dataset does not contain any additional annotations.


#### Annotation process


[N/A]


#### Who are the annotators?


[N/A]


### Personal and Sensitive Information


The original dataset is not anonymized, therefore individuals' names can be found in this dataset as well.


Considerations for Using the Data
---------------------------------


### Social Impact of Dataset


The purpose of this dataset is to access the quality and writing style of ChatGPT for writing news articles using highlights provided by humans and further study the biases if present.


### Discussion of Biases


There have been studies measuring gender bias in the original dataset which could be interesting Bordia and Bowman (2019)


### Licensing Information


The ChatGPT CNN / Daily Mail dataset uses the same licence as the original dataset, which is Apache-2.0 License.



### Dataset Summary


The ChatGPT CNN / DailyMail Dataset is a small sample of the original CNN / DailyMaily English-language dataset containing 25k unique news articles. For each corresponding article written by journalists at CNN and the Daily Mail, there is an article written by ChatGPT using the highlights provided by human annotators. The current version supports can be used to study the language comparison between human and ChatGPT news writing. ### Languages


The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.


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


For each instance, there is a string for the article, a string for the highlights, a string for the id, and a string for an article written by ChatGPT


The average token count for the articles and the highlights are provided below: ### Data Fields


* 'id': a string containing the heximal formated SHA1 hash of the url where the story was retrieved from
* 'article': a string containing the news article written by journalists
* 'highlights': a string containing the highlight of the article as written by the article author
* 'chatgpt': a string containing the news article written by ChatGPT ### Data Splits


The CNN/DailyMail dataset has 2 splits: *train* and *test*. Below are the statistics of the dataset.



Dataset Creation
----------------


ChatGPT Prompt
--------------


The number of words for an article (N) was the same as the original article ### Source Data ### Original Dataset Curators


The data was originally collected by Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom of Google DeepMind. Tomáš Kočiský and Phil Blunsom are also affiliated with the University of Oxford. They released scripts to collect and process the data into the question answering format.


Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, and Bing Xiang of IMB Watson and Çağlar Gu̇lçehre of Université de Montréal modified Hermann et al's collection scripts to restore the data to a summary format. They also produced both anonymized and non-anonymized versions.


The code for the non-anonymized version is made publicly available by Abigail See of Stanford University, Peter J. Liu of Google Brain and Christopher D. Manning of Stanford University at <URL The work at Stanford University was supported by the DARPA DEFT ProgramAFRL contract no. FA8750-13-2-0040. #### Who are the source language producers?


The text was written by journalists at CNN and the Daily Mail and ChatGPT ### Annotations


The dataset does not contain any additional annotations. #### Annotation process


[N/A] #### Who are the annotators?


[N/A] ### Personal and Sensitive Information


The original dataset is not anonymized, therefore individuals' names can be found in this dataset as well.


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset


The purpose of this dataset is to access the quality and writing style of ChatGPT for writing news articles using highlights provided by humans and further study the biases if present. ### Discussion of Biases


There have been studies measuring gender bias in the original dataset which could be interesting Bordia and Bowman (2019) ### Licensing Information


The ChatGPT CNN / Daily Mail dataset uses the same licence as the original dataset, which is Apache-2.0 License.
TAGS
#region-us 
 ### Dataset Summary


The ChatGPT CNN / DailyMail Dataset is a small sample of the original CNN / DailyMaily English-language dataset containing 25k unique news articles. For each corresponding article written by journalists at CNN and the Daily Mail, there is an article written by ChatGPT using the highlights provided by human annotators. The current version supports can be used to study the language comparison between human and ChatGPT news writing. ### Languages


The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.


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


For each instance, there is a string for the article, a string for the highlights, a string for the id, and a string for an article written by ChatGPT


The average token count for the articles and the highlights are provided below: ### Data Fields


* 'id': a string containing the heximal formated SHA1 hash of the url where the story was retrieved from
* 'article': a string containing the news article written by journalists
* 'highlights': a string containing the highlight of the article as written by the article author
* 'chatgpt': a string containing the news article written by ChatGPT ### Data Splits


The CNN/DailyMail dataset has 2 splits: *train* and *test*. Below are the statistics of the dataset.



Dataset Creation
----------------


ChatGPT Prompt
--------------


The number of words for an article (N) was the same as the original article ### Source Data ### Original Dataset Curators


The data was originally collected by Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom of Google DeepMind. Tomáš Kočiský and Phil Blunsom are also affiliated with the University of Oxford. They released scripts to collect and process the data into the question answering format.


Ramesh Nallapati, Bowen Zhou, Cicero dos Santos, and Bing Xiang of IMB Watson and Çağlar Gu̇lçehre of Université de Montréal modified Hermann et al's collection scripts to restore the data to a summary format. They also produced both anonymized and non-anonymized versions.


The code for the non-anonymized version is made publicly available by Abigail See of Stanford University, Peter J. Liu of Google Brain and Christopher D. Manning of Stanford University at <URL The work at Stanford University was supported by the DARPA DEFT ProgramAFRL contract no. FA8750-13-2-0040. #### Who are the source language producers?


The text was written by journalists at CNN and the Daily Mail and ChatGPT ### Annotations


The dataset does not contain any additional annotations. #### Annotation process


[N/A] #### Who are the annotators?


[N/A] ### Personal and Sensitive Information


The original dataset is not anonymized, therefore individuals' names can be found in this dataset as well.


Considerations for Using the Data
--------------------------------- ### Social Impact of Dataset


The purpose of this dataset is to access the quality and writing style of ChatGPT for writing news articles using highlights provided by humans and further study the biases if present. ### Discussion of Biases


There have been studies measuring gender bias in the original dataset which could be interesting Bordia and Bowman (2019) ### Licensing Information


The ChatGPT CNN / Daily Mail dataset uses the same licence as the original dataset, which is Apache-2.0 License.
passage: TAGS
#region-us 
### Dataset Summary


The ChatGPT CNN / DailyMail Dataset is a small sample of the original CNN / DailyMaily English-language dataset containing 25k unique news articles. For each corresponding article written by journalists at CNN and the Daily Mail, there is an article written by ChatGPT using the highlights provided by human annotators. The current version supports can be used to study the language comparison between human and ChatGPT news writing.### Languages


The BCP-47 code for English as generally spoken in the United States is en-US and the BCP-47 code for English as generally spoken in the United Kingdom is en-GB. It is unknown if other varieties of English are represented in the data.


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


For each instance, there is a string for the article, a string for the highlights, a string for the id, and a string for an article written by ChatGPT


The average token count for the articles and the highlights are provided below:### Data Fields


* 'id': a string containing the heximal formated SHA1 hash of the url where the story was retrieved from
* 'article': a string containing the news article written by journalists
* 'highlights': a string containing the highlight of the article as written by the article author
* 'chatgpt': a string containing the news article written by ChatGPT### Data Splits


The CNN/DailyMail dataset has 2 splits: *train* and *test*. Below are the statistics of the dataset.



Dataset Creation
----------------


ChatGPT Prompt
--------------


The number of words for an article (N) was the same as the original article### Source Data