README.md

annotations_creators:

• machine-generated
• expert-generated language_creators:
• machine-generated
• crowdsourced languages:
• en licenses:
• cc-by-sa-3.0
• gpl-3.0 multilinguality:
• monolingual paperswithcode_id: fever pretty_name: '' size_categories:
• 100K<n<1M source_datasets:
• extended|fever task_categories:
• text-classification task_ids:
• fact-checking

Dataset Card for fever_gold_evidence

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • 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

Dataset Description

• Homepage: https://github.com/copenlu/fever-adversarial-attacks
• Repository: https://github.com/copenlu/fever-adversarial-attacks
• Paper: https://aclanthology.org/2020.emnlp-main.256/
• Leaderboard: [Needs More Information]
• Point of Contact: [Needs More Information]

Dataset Summary

Dataset for training classification-only fact checking with claims from FEVER dataset. This dataset is used in the paper "Generating Label Cohesive and Well-Formed Adversarial Claims", EMNLP 2020

The evidence is the gold evidence from the FEVER dataset for REFUTE and SUPPORT claims. For NEI claims, we extract evidence sentences with the system in "Christopher Malon. 2018. Team Papelo: Transformer Networks at FEVER. In Proceedings of the First Workshop on Fact Extraction and VERification (FEVER), pages 109113."

Supported Tasks and Leaderboards

[Needs More Information]

Languages

[Needs More Information]

Dataset Structure

Data Instances

[Needs More Information]

Data Fields

[Needs More Information]

Data Splits

[Needs More Information]

Dataset Creation

Curation Rationale

[Needs More Information]

Source Data

Initial Data Collection and Normalization

[Needs More Information]

Who are the source language producers?

[Needs More Information]

Annotations

Annotation process

[Needs More Information]

Who are the annotators?

[Needs More Information]

Personal and Sensitive Information

[Needs More Information]

Considerations for Using the Data

Social Impact of Dataset

[Needs More Information]

Discussion of Biases

[Needs More Information]

Other Known Limitations

[Needs More Information]

Additional Information

Dataset Curators

[Needs More Information]

Licensing Information

[Needs More Information]

Citation Information

[Needs More Information]