Abstract: 

Obtaining high-quality labeled data to train and validate models faces two perennial challenges: quality and scalability. In this demo, we share iMerit's best practices for collaborating with an annotation partner. Our approach to collaborative annotation project design allows us to achieve quality at scale and at low cost, while also yielding additional insights to further enrich and refine your datasets and labeling requirements.

Bio: 

Dr. Teresa O’Neill is a Solutions Architect at iMerit specializing in language annotation services. Before joining iMerit, she worked for a decade in academia as an educator and researcher. At iMerit, she leverages her experience as a linguist with both theoretical and applied specializations to build custom human-in-the-loop annotation pipelines for customers with NLP/NLU use cases.