# Annotating text with multiple labels simultaneously

**URL:** <https://support.prodi.gy/t/annotating-text-with-multiple-labels-simultaneously/2807>\
**Category:** Uncategorized\
**Tags:** usage, ner, solved\
**Created:** [April 20, 2020, 6:22pm UTC](https://support.prodi.gy/t/annotating-text-with-multiple-labels-simultaneously/2807 "2020-04-20T18:22:08Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![konstantinidis.alexa](https://avatars.discourse-cdn.com/v4/letter/k/85e7bf/32.png) [@konstantinidis.alexa](https://support.prodi.gy/u/konstantinidis.alexa)\
**Post date:** [April 20, 2020, 6:22pm UTC](https://support.prodi.gy/t/annotating-text-with-multiple-labels-simultaneously/2807/1 "2020-04-20T18:22:08Z")

</div>

Can I use Prodigy to apply different labels to different spans of the document I am viewing and annotating?

E.g. "Merk is a pharmaceutical company with revenues of $x and profits that exceeded $y. The CEO of the company John Smith presented his new plans for restructuring the company is the Board meeting that took place in 2020/02/10"

I might want to apply several labels in the short document for the following tokens: 'Merk', 'pharmaceutical', 'x', 'y', 'John Smith', '2020/02/10'.

Would that be possible?

---

<div class="post-metadata">

**Author:** ![ines](https://sea2.discourse-cdn.com/flex020/user_avatar/support.prodi.gy/ines/32/3_2.png) [@ines](https://support.prodi.gy/u/ines)\
**Post date:** [April 20, 2020, 7:01pm UTC](https://support.prodi.gy/t/annotating-text-with-multiple-labels-simultaneously/2807/2 "2020-04-20T19:01:23Z")

</div>

Sure, that's no problem and a pretty common use case for NER annotation. In case you haven't seen it yet, the NER documentation has a bunch of examples of the different workflows and interfaces:

> **[Named Entity Recognition · Prodigy · An annotation tool for AI, Machine...](https://prodi.gy/docs/named-entity-recognition/)**
>
> A downloadable annotation tool for NLP and computer vision tasks such as named entity recognition, text classification, object detection, image segmentation, A/B evaluation and more.