# Question about annotator management
**URL:** https://support.prodi.gy/t/question-about-annotator-management/2948
**Category:** Uncategorized
**Tags:** usage
**Created:** [May 28, 2020, 8:53am UTC](https://support.prodi.gy/t/question-about-annotator-management/2948 "2020-05-28T08:53:02Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@a\_tarun](https://support.prodi.gy/u/a_tarun)
#### Post date: [May 28, 2020, 8:53am UTC](https://support.prodi.gy/t/question-about-annotator-management/2948/1 "2020-05-28T08:53:02Z")
I using Doccano and considering moving to Prodigy. Is there a way to allow a team of 10-20 people to annotate but only have 3 people at most annotate a text? Also is there a way to assign one of the of person as a "approver" or verifier of annotations?
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### Author:  [@honnibal](https://support.prodi.gy/u/honnibal)
#### Post date: [May 30, 2020, 11:45am UTC](https://support.prodi.gy/t/question-about-annotator-management/2948/2 "2020-05-30T11:45:45Z")
When we were laying out the design for Prodigy, there are some features that we decided didn't belong so naturally within the design of a command-line oriented, interactive tool. Intricate annotator management and task-allocation policies is one of those features, because once you're working with a lot of annotators like that, the balance of considerations shifts in a different direction.
We're building Prodigy Teams as a separate product to provide features like annotator accounts, task allocations, starting and stopping annotation tasks from a GUI, review and conflict resolution, etc. The primary difference is that current Prodigy (which I guess we can call "Prodigy Standalone" in contrast) doesn't ask to be wrapped in a container, hosted on a server, and connected to a hosted database. You're often running it yourself with Python scripts and a local SQLite database.
All that said, there are some features that let you do what you want with Prodigy. You can set up a different feed for different annotators, and have each annotator visit a different URL, [differentiated via query string](https://prodi.gy/docs/api-web-app#multi-user-sessions). You could even have a web server in front that authenticated the users separately.
Prodigy also features `review` recipes designed for the conflict resolution (and these are the same recipes we'll be using ourselves in Prodigy Teams --- so they'll stay updated and improved). By default, the recipe expects to be run in a batch-wise fashion, I don't think it constantly pulls new updates as they're pushed to the individual datasets. So if you wanted to leave the task up persistently, you'd need to modify the recipe a bit. Alternatively you can start and stop the service at discrete intervals.