README.md

metadata

languages:
  - en
paperswithcode_id: newsroom

Dataset Card for "newsroom"

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

• Homepage: https://summari.es
• Repository: More Information Needed
• Paper: More Information Needed
• Point of Contact: More Information Needed
• Size of downloaded dataset files: 0.00 MB
• Size of the generated dataset: 5057.49 MB
• Total amount of disk used: 5057.49 MB

Dataset Summary

NEWSROOM is a large dataset for training and evaluating summarization systems. It contains 1.3 million articles and summaries written by authors and editors in the newsrooms of 38 major publications.

Dataset features includes:

• text: Input news text.
• summary: Summary for the news. And additional features:
• title: news title.
• url: url of the news.
• date: date of the article.
• density: extractive density.
• coverage: extractive coverage.
• compression: compression ratio.
• density_bin: low, medium, high.
• coverage_bin: extractive, abstractive.
• compression_bin: low, medium, high.

This dataset can be downloaded upon requests. Unzip all the contents "train.jsonl, dev.josnl, test.jsonl" to the tfds folder.

Supported Tasks and Leaderboards

More Information Needed

Languages

More Information Needed

Dataset Structure

We show detailed information for up to 5 configurations of the dataset.

Data Instances

default

• Size of downloaded dataset files: 0.00 MB
• Size of the generated dataset: 5057.49 MB
• Total amount of disk used: 5057.49 MB

An example of 'train' looks as follows.

{
    "compression": 33.880001068115234,
    "compression_bin": "medium",
    "coverage": 1.0,
    "coverage_bin": "high",
    "date": "200600000",
    "density": 11.720000267028809,
    "density_bin": "extractive",
    "summary": "some summary 1",
    "text": "some text 1",
    "title": "news title 1",
    "url": "url.html"
}

Data Fields

The data fields are the same among all splits.

default

• text: a string feature.
• summary: a string feature.
• title: a string feature.
• url: a string feature.
• date: a string feature.
• density_bin: a string feature.
• coverage_bin: a string feature.
• compression_bin: a string feature.
• density: a float32 feature.
• coverage: a float32 feature.
• compression: a float32 feature.

Data Splits

name	train	validation	test
default	995041	108837	108862

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

More Information Needed

Who are the source language producers?

More Information Needed

Annotations

Annotation process

More Information Needed

Who are the annotators?

More Information Needed

Personal and Sensitive Information

More Information Needed

Considerations for Using the Data

Social Impact of Dataset

More Information Needed

Discussion of Biases

More Information Needed

Other Known Limitations

More Information Needed

Additional Information

Dataset Curators

More Information Needed

Licensing Information

More Information Needed

Citation Information

@inproceedings{N18-1065,
  author    = {Grusky, Max and Naaman, Mor and Artzi, Yoav},
  title     = {NEWSROOM: A Dataset of 1.3 Million Summaries
               with Diverse Extractive Strategies},
  booktitle = {Proceedings of the 2018 Conference of the
               North American Chapter of the Association for
               Computational Linguistics: Human Language Technologies},
  year      = {2018},
}

Contributions

Thanks to @lewtun, @patrickvonplaten, @yoavartzi, @thomwolf for adding this dataset.