README.md

metadata

annotations_creators:
  - crowdsourced
  - expert-generated
language_creators:
  - found
languages:
  - en
licenses:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 1K<n<10K
source_datasets:
  - extended|wikipedia
  - original
task_categories:
  - text-classification
  - text-retrieval
  - text-scoring
task_ids:
  - fact-checking
  - fact-checking-retrieval
  - semantic-similarity-scoring

Dataset Card for ClimateFever

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: CLIMATE-FEVER homepage
• Repository: CLIMATE-FEVER repository
• Paper: CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims
• Leaderboard: [Needs More Information]
• Point of Contact: Thomas Diggelmann

Dataset Summary

A dataset adopting the FEVER methodology that consists of 1,535 real-world claims regarding climate-change collected on the internet. Each claim is accompanied by five manually annotated evidence sentences retrieved from the English Wikipedia that support, refute or do not give enough information to validate the claim totalling in 7,675 claim-evidence pairs. The dataset features challenging claims that relate multiple facets and disputed cases of claims where both supporting and refuting evidence are present.

Supported Tasks and Leaderboards

[Needs More Information]

Languages

The text in the dataset is in English, as found in real-world claims about climate-change on the Internet. The associated BCP-47 code is en.

Dataset Structure

Data Instances

{
  "claim_id": "0",
  "claim": "Global warming is driving polar bears toward extinction",
  "claim_label": 1,  # "SUPPORTS"
  "evidences": [
    {
     "evidence_id": "Extinction risk from global warming:170",
     "evidence_label": 2,  # "NOT_ENOUGH_INFO"
     "article": "Extinction risk from global warming",
     "evidence": "\"Recent Research Shows Human Activity Driving Earth Towards Global Extinction Event\".",
     "entropy": 0.6931471805599453,
     "votes": [
      "SUPPORTS",
      "NOT_ENOUGH_INFO",
      null,
      null,
      null
     ]
    },
    {
     "evidence_id": "Global warming:14",
     "evidence_label": 1,  # "SUPPORTS"
     "article": "Global warming",
     "evidence": "Environmental impacts include the extinction or relocation of many species as their ecosystems change, most immediately the environments of coral reefs, mountains, and the Arctic.",
     "entropy": 0.0,
     "votes": [
      "SUPPORTS",
      "SUPPORTS",
      null,
      null,
      null
     ]
    },
    {
     "evidence_id": "Global warming:178",
     "evidence_label": 2,  # "NOT_ENOUGH_INFO"
     "article": "Global warming",
     "evidence": "Rising temperatures push bees to their physiological limits, and could cause the extinction of bee populations.",
     "entropy": 0.6931471805599453,
     "votes": [
      "SUPPORTS",
      "NOT_ENOUGH_INFO",
      null,
      null,
      null
     ]
    },
    {
     "evidence_id": "Habitat destruction:61",
     "evidence_label": 1,  # "SUPPORTS"
     "article": "Habitat destruction",
     "evidence": "Rising global temperatures, caused by the greenhouse effect, contribute to habitat destruction, endangering various species, such as the polar bear.",
     "entropy": 0.0,
     "votes": [
      "SUPPORTS",
      "SUPPORTS",
      null,
      null,
      null
     ]
    },
    {
     "evidence_id": "Polar bear:1328",
     "evidence_label": 2,  # "NOT_ENOUGH_INFO"
     "article": "Polar bear",
     "evidence": "\"Bear hunting caught in global warming debate\".",
     "entropy": 0.6931471805599453,
     "votes": [
      "SUPPORTS",
      "NOT_ENOUGH_INFO",
      null,
      null,
      null
     ]
    }
  ]
}

Data Fields

• claim_id: a string feature, unique claim identifier.
• claim: a string feature, claim text.
• claim_label: a int feature, overall label assigned to claim (based on evidence majority vote). The label correspond to 0: "refutes", 1: "supports" and 2: "not enough info"
• evidences: a list of evidences with fields:
• evidence_id: a string feature, unique evidence identifier.
• evidence_label: a int feature, micro-verdict label. The label correspond to 0: "refutes", 1: "supports" and 2: "not enough info"
• article: a string feature, title of source article (Wikipedia page).
• evidence: a string feature, evidence sentence.
• entropy: a float32 feature, entropy reflecting uncertainty of evidence_label.
• votes: a list of string features, corresponding to individual votes.

Data Splits

This benchmark dataset currently consists of a single data split test that consists of 1,535 claims or 7,675 claim-evidence pairs.

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

@misc{diggelmann2020climatefever,
      title={CLIMATE-FEVER: A Dataset for Verification of Real-World Climate Claims},
      author={Thomas Diggelmann and Jordan Boyd-Graber and Jannis Bulian and Massimiliano Ciaramita and Markus Leippold},
      year={2020},
      eprint={2012.00614},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}