5. Fact Verification
[This project is a part of my tenure at University of South Carolina as an affiliate Researcher]
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Problem
Automatic fact verification has received significant attention recently. Traditional automatic fact-checking systems focus on estimating truthfulness using numerical scores which are not human-interpretable. Manual fact-checking is a time-consuming task. Professional fact-checkers take a considerable amount of time sometimes several days to verify a fact.
Proposed Solution
In this work, an automatic fact verification system is proposed using question answering based on 5W (Who, When, What, Where, Why) approach
Implementation
Data is collected from random a mixture of publicly available fake news dataset
Experimentation for finding 5Ws from a given claim is conducted using a previously implemented work.
Experimented with question and answering system to take the context from the claim and generate automatic 5W-based questions
This is to be followed by an information retrieval system and a textual entailment model to generate evidence so that a final verdict is predicted
My contribution
Ideation on the framework, managing the team
Experimentation on 5W SRL and question answering model and evaluating the results
Working on the manuscript
Uniqueness
It would be the first system proposed for 5W Aspect based fact verification and would have an added explainability through question answer generation framework
Results
We plan to publish this work at ACL'23 and due to confidentiality a lot of information couldn't be added into this project here at the moment.
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