MEGAnno+: A Human-LLM Collaborative Annotation System

Hannah Kim, Kushan Mitra, Rafael Li Chen,Sajjadur Rahman,Dan Zhang

Conference of the European Chapter of the Association for Computational Linguistics(2024)

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摘要
Large language models (LLMs) can label data faster and cheaper than humans for various NLP tasks. Despite their prowess, LLMs may fall short in understanding of complex, sociocultural, or domain-specific context, potentially leading to incorrect annotations. Therefore, we advocate a collaborative approach where humans and LLMs work together to produce reliable and high-quality labels. We present MEGAnno+, a human-LLM collaborative annotation system that offers effective LLM agent and annotation management, convenient and robust LLM annotation, and exploratory verification of LLM labels by humans.
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