Abstract
In this talk I will give an overview of our work on fact extraction and verification. I will first introduce the first fact extraction and verification shared task on unstructured information (text) from Wikipedia and how we constructed the first large-scale dataset for it. I will then discuss how we incorporated structured inference to achieve improved robustness while maintaining state-of-the-art accuracy in fact verification. Following this, I will describe our work on correcting factual errors in claims. I will conclude this talk by presenting our recent dataset and shared task on fact extraction and verification on both structured (tables) and unstructured (tables) information.
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