# NLU training data - json vs markdown

**URL:** <https://forum.rasa.com/t/nlu-training-data-json-vs-markdown/938>\
**Category:** Rasa Open Source\
**Created:** [September 7, 2018, 9:25am UTC](https://forum.rasa.com/t/nlu-training-data-json-vs-markdown/938 "2018-09-07T09:25:51Z")\
**Posts on this page:** 3\
**Page:** 1

<div class="post-metadata">

**Author:** ![sfinnie](https://avatars.discourse-cdn.com/v4/letter/s/e79b87/32.png) [@sfinnie](https://forum.rasa.com/u/sfinnie)\
**Post date:** [September 7, 2018, 9:25am UTC](https://forum.rasa.com/t/nlu-training-data-json-vs-markdown/938/1 "2018-09-07T09:25:51Z")

</div>

I’m looking at how to embed entities in my NLU training data. The quickstart uses markdown for mapping utterances to intent. However, it doesn’t include any examples with embedded entities. The [examples](https://github.com/RasaHQ/rasa_core/tree/master/examples) on github use json which does show entity identification. So, two questions please:

1. Is one format recommended over the other, or are both equally supported?
2. Is there any documentation on specifying entities in markdown?

Thanks.

---

<div class="post-metadata">

**Author:** ![akelad](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/akelad/32/69_2.png) [@akelad](https://forum.rasa.com/u/akelad)\
**Post date:** [September 7, 2018, 12:16pm UTC](https://forum.rasa.com/t/nlu-training-data-json-vs-markdown/938/2 "2018-09-07T12:16:20Z")

</div>

Hmm, have you looked at this documentation? there’s examples of the markdown format at the very start [http://rasa.com/docs/nlu/dataformat/](http://rasa.com/docs/nlu/dataformat/) They’re both equally supported, markdown is the recommended option because it’s a lot easier to read

---

<div class="post-metadata">

**Author:** ![sfinnie](https://avatars.discourse-cdn.com/v4/letter/s/e79b87/32.png) [@sfinnie](https://forum.rasa.com/u/sfinnie)\
**Post date:** [September 7, 2018, 12:20pm UTC](https://forum.rasa.com/t/nlu-training-data-json-vs-markdown/938/3 "2018-09-07T12:20:07Z")

</div>

Thanks @akelad. Hiding in plain view :(. I was looking for details under the “entity extraction” section. Didn’t spot the separate section. Thanks for the pointer.