

# SQuALITY - v1.3

> Original paper [here](https://arxiv.org/abs/2205.11465)

This is v1.3, the 'text' edition `.jsonl` files. See description from the [original repo](https://github.com/nyu-mll/SQuALITY):

> v1.3 fixes some bugs in v1.2. In v1.2, 10 out of 127 articles (each ~5k-word-long) are missing a few hundreds words each, so summaries may not be fully contained in the article. To fix this issue, we have updated the 10 articles.

## contents 

> again, this is taken from the repo

Each data file ({train/dev/test}.jsonl) is formatted as a JSON lines file. Each row in the data file is a JSON dictionary with the following fields:

- metadata: the Gutenberg story ID, an internal UID, and the Project Gutenberg license
- document: the Gutenberg story
questions: a list of questions and accompanying responses
  - question text
  - question number: the order in which that question was answered by the writers
  - responses: list of worker's response, where each response is a dictionary containing the (anonymized) worker ID, an internal UID, and their response to the question
 

### dataset contents


```python
DatasetDict({
    train: Dataset({
        features: ['metadata', 'document', 'questions'],
        num_rows: 50
    })
    test: Dataset({
        features: ['metadata', 'document', 'questions'],
        num_rows: 52
    })
    validation: Dataset({
        features: ['metadata', 'document', 'questions'],
        num_rows: 25
    })
})
```


task_categories:summarization task_categories:text2text-generation size_categories:n<1K language:en license:apache-2.0 summarization long-document arxiv:2205.11465 region:us
{"language": ["en"], "license": "apache-2.0", "size_categories": ["n<1K"], "task_categories": ["summarization", "text2text-generation"], "pretty_name": "SQuALITY v1.3", "tags": ["summarization", "long-document"]}
TAGS
#task_categories-summarization #task_categories-text2text-generation #size_categories-n<1K #language-English #license-apache-2.0 #summarization #long-document #arxiv-2205.11465 #region-us 



# SQuALITY - v1.3

> Original paper here

This is v1.3, the 'text' edition '.jsonl' files. See description from the original repo:

> v1.3 fixes some bugs in v1.2. In v1.2, 10 out of 127 articles (each ~5k-word-long) are missing a few hundreds words each, so summaries may not be fully contained in the article. To fix this issue, we have updated the 10 articles.

## contents 

> again, this is taken from the repo

Each data file ({train/dev/test}.jsonl) is formatted as a JSON lines file. Each row in the data file is a JSON dictionary with the following fields:

- metadata: the Gutenberg story ID, an internal UID, and the Project Gutenberg license
- document: the Gutenberg story
questions: a list of questions and accompanying responses
  - question text
  - question number: the order in which that question was answered by the writers
  - responses: list of worker's response, where each response is a dictionary containing the (anonymized) worker ID, an internal UID, and their response to the question
 

### dataset contents





# SQuALITY - v1.3

> Original paper here

This is v1.3, the 'text' edition '.jsonl' files. See description from the original repo:

> v1.3 fixes some bugs in v1.2. In v1.2, 10 out of 127 articles (each ~5k-word-long) are missing a few hundreds words each, so summaries may not be fully contained in the article. To fix this issue, we have updated the 10 articles. ## contents 

> again, this is taken from the repo

Each data file ({train/dev/test}.jsonl) is formatted as a JSON lines file. Each row in the data file is a JSON dictionary with the following fields:

- metadata: the Gutenberg story ID, an internal UID, and the Project Gutenberg license
- document: the Gutenberg story
questions: a list of questions and accompanying responses
  - question text
  - question number: the order in which that question was answered by the writers
  - responses: list of worker's response, where each response is a dictionary containing the (anonymized) worker ID, an internal UID, and their response to the question ### dataset contents
TAGS
#task_categories-summarization #task_categories-text2text-generation #size_categories-n<1K #language-English #license-apache-2.0 #summarization #long-document #arxiv-2205.11465 #region-us 
 # SQuALITY - v1.3

> Original paper here

This is v1.3, the 'text' edition '.jsonl' files. See description from the original repo:

> v1.3 fixes some bugs in v1.2. In v1.2, 10 out of 127 articles (each ~5k-word-long) are missing a few hundreds words each, so summaries may not be fully contained in the article. To fix this issue, we have updated the 10 articles. ## contents 

> again, this is taken from the repo

Each data file ({train/dev/test}.jsonl) is formatted as a JSON lines file. Each row in the data file is a JSON dictionary with the following fields:

- metadata: the Gutenberg story ID, an internal UID, and the Project Gutenberg license
- document: the Gutenberg story
questions: a list of questions and accompanying responses
  - question text
  - question number: the order in which that question was answered by the writers
  - responses: list of worker's response, where each response is a dictionary containing the (anonymized) worker ID, an internal UID, and their response to the question ### dataset contents
passage: TAGS
#task_categories-summarization #task_categories-text2text-generation #size_categories-n<1K #language-English #license-apache-2.0 #summarization #long-document #arxiv-2205.11465 #region-us 
# SQuALITY - v1.3

> Original paper here

This is v1.3, the 'text' edition '.jsonl' files. See description from the original repo:

> v1.3 fixes some bugs in v1.2. In v1.2, 10 out of 127 articles (each ~5k-word-long) are missing a few hundreds words each, so summaries may not be fully contained in the article. To fix this issue, we have updated the 10 articles.## contents 

> again, this is taken from the repo

Each data file ({train/dev/test}.jsonl) is formatted as a JSON lines file. Each row in the data file is a JSON dictionary with the following fields:

- metadata: the Gutenberg story ID, an internal UID, and the Project Gutenberg license
- document: the Gutenberg story
questions: a list of questions and accompanying responses
  - question text
  - question number: the order in which that question was answered by the writers
  - responses: list of worker's response, where each response is a dictionary containing the (anonymized) worker ID, an internal UID, and their response to the question### dataset contents