MEGAnno combines the power of large language models (LLMs) with human expertise to streamline and enhance the data labeling process with a data annotation framework. Throughout this article, we’ll showcase MEGAnno’s capabilities as we provide detailed code snippets.
We introduce our human-LLM collaborative annotation tool, MEGAnno+, addressing the challenges in LLM annotation by integrating human expertise with LLM capabilities.
In this blog post, we present MEGAnno, our flexible, exploratory, efficient, and seamless labeling framework for NLP researchers and practitioners. In short, MEGAnno aims to reduce costs while improving the quality of labeling.
Megagon Labs has released several open-source frameworks for human-AI collaboration, including MEGAnno (an annotation framework combining LLMs with human expertise), Lapras (a multi-step human-LLM collaborative
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Instead of completely replacing human annotators with LLMs, we need to leverage the strengths of both sides to obtain accurate and reliable annotations. This article will discuss how to effectively utilize LLMs as collaborators for data annotation.
We discuss how to leverage LLMs as data annotation agents and the practical challenges that may arise. We briefly introduce our LLM annotation tool, MEGAnno+.
