README.md

metadata

YAML tags: null
annotations_creators:
  - crowdsourced
language_creators:
  - found
languages:
  - ru
  - ru-RU
  - en
licenses:
  - cc0-1.0
multilinguality:
  - multilingual
pretty_name: HeadlineCause
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids:
  - multi-class-classification
  - causal-reasoning

Dataset Card for HeadlineCause

Table of Contents

• 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://github.com/IlyaGusev/HeadlineCause
• Paper: HeadlineCause: A Dataset of News Headlines for Detecting Casualties
• Point of Contact: Ilya Gusev

Dataset Summary

A dataset for detecting implicit causal relations between pairs of news headlines. The dataset includes over 5000 headline pairs from English news and over 9000 headline pairs from Russian news labeled through crowdsourcing. The pairs vary from totally unrelated or belonging to the same general topic to the ones including causation and refutation relations.

Usage

Loading Russian Simple task:

from datasets import load_dataset
dataset = load_dataset("IlyaGusev/headline_cause", "ru_simple")

Supported Tasks and Leaderboards

[More Information Needed]

Languages

This dataset consists of two parts, Russian and English.

Dataset Structure

Data Instances

There is an URL, a title, and a timestamp for each of the two headlines in every data instance. A label is presented in three fields. 'Result' field is a textual label, 'label' field is a numeric label, and the 'agreement' field shows the majority vote agreement between annotators. Additional information includes instance ID and the presence of the link between two articles.

{
    'left_url': 'https://www.kommersant.ru/doc/4347456',
    'right_url': 'https://tass.ru/kosmos/8488527',
    'left_title': 'NASA: информация об отказе сотрудничать с Россией по освоению Луны некорректна',
    'right_title': 'NASA назвало некорректными сообщения о нежелании США включать РФ в соглашение по Луне',
    'left_timestamp': datetime.datetime(2020, 5, 15, 19, 46, 20),
    'right_timestamp': datetime.datetime(2020, 5, 15, 19, 21, 36),
    'label': 0,
    'result': 'not_cause',
    'agreement': 1.0,
    'id': 'ru_tg_101',
    'has_link': True
}

Data Splits

Dataset	Split	Number of Instances
ru_simple	train	7,641
ru_simple	validation	955
ru_simple	test	957
en_simple	train	4,332
en_simple	validation	542
en_simple	test	542
ru_full	train	5,713
ru_full	validation	715
ru_full	test	715
en_full	train	2,009
en_full	validation	251
en_full	test	252

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

The data was collected by Ilya Gusev.

Licensing Information

[More Information Needed]

Citation Information

[More Information Needed]

Contributions

[More Information Needed]