  We present MEGAnno, a novel exploratory annotation framework designed for NLP
researchers and practitioners. Unlike existing labeling tools that focus on
data labeling only, our framework aims to support a broader, iterative ML
workflow including data exploration and model development. With MEGAnno's API,
users can programmatically explore the data through sophisticated search and
automated suggestion functions and incrementally update task schema as their
project evolve. Combined with our widget, the users can interactively sort,
filter, and assign labels to multiple items simultaneously in the same notebook
where the rest of the NLP project resides. We demonstrate MEGAnno's flexible,
exploratory, efficient, and seamless labeling experience through a sentiment
analysis use case.
