ryokamoi/wice
This repository contains the dataset and code for "WiCE: Real-World Entailment for Claims in Wikipedia" in EMNLP 2023.
This project offers a comprehensive dataset of claims from Wikipedia, paired with supporting or refuting evidence from cited articles. It helps fact-checkers, researchers, and content validators analyze how well a claim is supported by its sources. You input a Wikipedia sentence and its cited articles, and it outputs whether the claim is fully supported, partially supported, or not supported, along with the specific supporting sentences or unsupported parts of the claim.
No commits in the last 6 months.
Use this if you need to rigorously evaluate natural language models designed for fact-checking, claim verification, or evidence retrieval in a real-world context using Wikipedia as a source.
Not ideal if you're looking for a simple, pre-trained model for immediate, out-of-the-box fact-checking without needing to train or evaluate on a detailed dataset.
Stars
42
Forks
1
Language
Python
License
—
Category
Last pushed
Dec 15, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/ryokamoi/wice"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
luheng/deep_srl
Code and pre-trained model for: Deep Semantic Role Labeling: What Works and What's Next
sileod/tasksource
Datasets collection and preprocessings framework for NLP extreme multitask learning
loomchild/maligna
Bilingual sengence aligner
CK-Explorer/DuoSubs
Semantic subtitle aligner and merger for bilingual subtitle syncing.
coastalcph/lex-glue
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English