AFaCTA: Assisting the Annotation of Factual Claim Detection with Reliable LLM Annotators

arXiv:2402.11073v1 Announce Type: new
Abstract: With the rise of generative AI, automated fact-checking methods to combat misinformation are becoming more and more important. However, factual claim detection, the first step in a fact-checking pipeline, suffers from two key issues that limit its scalability and generalizability: (1) inconsistency in definitions of the task and what a claim is, and (2) the high cost of manual annotation. To address (1), we review the definitions in related work and propose a unifying definition …

abstract annotation arxiv automated claim cs.ai cs.cl detection fact-checking generative key llm misinformation pipeline scalability type