Check-COVID: Fact-Checking COVID-19 News Claims
Fact-checking COVID-19 news claims. Annotators verify claims against evidence, identify supporting/refuting spans, and provide verdicts with explanations. Based on the Check-COVID dataset targeting misinformation during the pandemic.
Configuration Fileconfig.yaml
This Potato config reproduces the annotation task. Save it as config.yaml and run potato start config.yaml to try it.
# Check-COVID: Fact-Checking COVID-19 News Claims
# Based on Wang et al., Findings ACL 2023
# Paper: https://aclanthology.org/2023.findings-acl.888/
# Dataset: https://github.com/posuer/Check-COVID
#
# This task verifies COVID-19 news claims against scientific evidence.
# Annotators determine if a claim is supported, refuted, or lacks
# sufficient evidence, and highlight relevant evidence spans.
#
# Verdict Labels:
# - Supported: Evidence confirms the claim
# - Refuted: Evidence contradicts the claim
# - Not Enough Evidence: Available evidence is insufficient to verify
#
# Annotation Guidelines:
# 1. Read the COVID-19 claim carefully
# 2. Read the evidence passage thoroughly
# 3. Determine whether the evidence supports or refutes the claim
# 4. Highlight the specific sentences/phrases in the evidence that
# are most relevant to your verdict
# 5. Write a brief explanation justifying your decision
# 6. Consider scientific nuance: preliminary findings vs established facts
# 7. Be careful with claims about causation vs correlation
annotation_task_name: "Check-COVID: Fact-Checking"
task_dir: "."
data_files:
- sample-data.json
item_properties:
id_key: "id"
text_key: "text"
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"
annotation_schemes:
# Step 1: Verdict
- annotation_type: radio
name: verdict
description: "Based on the evidence, is the COVID-19 claim supported, refuted, or is there not enough evidence?"
labels:
- "Supported"
- "Refuted"
- "Not Enough Evidence"
keyboard_shortcuts:
"Supported": "s"
"Refuted": "r"
"Not Enough Evidence": "n"
tooltips:
"Supported": "The evidence confirms or is consistent with the claim"
"Refuted": "The evidence directly contradicts the claim"
"Not Enough Evidence": "The evidence does not provide sufficient information to verify or refute the claim"
# Step 2: Evidence highlighting
- annotation_type: span
name: evidence_spans
description: "Highlight the sentence(s) in the evidence that are most relevant to your verdict"
labels:
- "Supporting Evidence"
- "Refuting Evidence"
label_colors:
"Supporting Evidence": "#22c55e"
"Refuting Evidence": "#ef4444"
tooltips:
"Supporting Evidence": "Text that supports or confirms the claim"
"Refuting Evidence": "Text that contradicts or refutes the claim"
allow_overlapping: false
# Step 3: Explanation
- annotation_type: text
name: explanation
description: "Briefly explain why the evidence supports, refutes, or is insufficient for the claim"
html_layout: |
<div style="margin-bottom: 10px; padding: 10px; background: #fef2f2; border-left: 4px solid #ef4444; border-radius: 4px;">
<strong>Claim:</strong> {{text}}
</div>
<div style="margin-bottom: 10px; padding: 10px; background: #f0fdf4; border-left: 4px solid #22c55e; border-radius: 4px;">
<strong>Evidence:</strong> {{evidence}}
</div>
<div style="padding: 6px; background: #f5f5f5; border-radius: 4px; font-size: 13px;">
<em>Source:</em> {{source}}
</div>
allow_all_users: true
instances_per_annotator: 60
annotation_per_instance: 3
allow_skip: true
skip_reason_required: false
Sample Datasample-data.json
[
{
"id": "covid_001",
"text": "Wearing masks significantly reduces the transmission of COVID-19.",
"evidence": "A large randomized trial in Bangladesh involving 342,000 participants found that surgical mask distribution and promotion reduced symptomatic SARS-CoV-2 seroprevalence by 11.2%. Villages where surgical masks were distributed showed a 35% reduction in symptomatic seroprevalence among individuals over 60 years old. Cloth masks showed a smaller, non-statistically significant reduction of 5%.",
"source": "Abaluck et al., Science 2022"
},
{
"id": "covid_002",
"text": "Hydroxychloroquine is an effective treatment for hospitalized COVID-19 patients.",
"evidence": "The RECOVERY trial, a large-scale randomized controlled trial conducted in the UK, enrolled 4,716 hospitalized COVID-19 patients. Patients receiving hydroxychloroquine showed no significant difference in 28-day mortality compared to usual care (27.0% vs 25.0%). There was also no evidence of benefit in terms of hospital stay duration or need for mechanical ventilation. The trial was stopped early due to lack of efficacy.",
"source": "Horby et al., NEJM 2020"
}
]
// ... and 8 more itemsGet This Design
Clone or download from the repository
Quick start:
git clone https://github.com/davidjurgens/potato-showcase.git cd potato-showcase/text/fact-verification/check-covid-fact-checking potato start config.yaml
Dataset & paper
Wang et al., Findings ACL 2023
Citation (BibTeX)
@inproceedings{wang-etal-2023-check-covid,
title = "Check-{COVID}: Fact-Checking {COVID}-19 News Claims with Scientific Evidence",
author = "Wang, Xia and Yao, Bingqian and Yao, Jiawei and Wang, Qi and Wang, Lu",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.888",
pages = "14078--14095"
}Details
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