Making the Most of Your Annotation Partnership
Making the Most of Your Annotation Partnership


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.


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.

Open Data Science




Open Data Science
One Broadway
Cambridge, MA 02142

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Consent to display content from - Youtube
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google