# Extracting name entity from text

**URL:** <https://forum.rasa.com/t/extracting-name-entity-from-text/20114>\
**Category:** Rasa Open Source\
**Created:** [October 21, 2019, 12:13pm UTC](https://forum.rasa.com/t/extracting-name-entity-from-text/20114 "2019-10-21T12:13:25Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![IgNoRaNt23](https://dub1.discourse-cdn.com/flex013/user_avatar/forum.rasa.com/ignorant23/32/8029_2.png) [@IgNoRaNt23](https://forum.rasa.com/u/IgNoRaNt23)\
**Post date:** [October 22, 2019, 5:27am UTC](https://forum.rasa.com/t/extracting-name-entity-from-text/20114/2 "2019-10-22T05:27:07Z")

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Personal name recognition is a pain in the ass. Go with spaCy whenever you can.

You need to rely on you entity extractor to pick up the right entities. This gets easier for more formal enitites like emails (where you can use a regex to support the recognition). For general entity regocnition see

> **[Rasa NLU in Depth: Entity Recognition](https://rasa.com/blog/rasa-nlu-in-depth-part-2-entity-recognition/)**
>
> Part 2 of our Rasa NLU in Depth series covers entity recognition. Learn more about fuzzy entities, address extraction, and mapping of entities.

If youre using a FormAction, you can also make use of ‘from\_text’ mapping, which takes the whole input of the user as a slot value. In this case it might be necessary to postprocess the message in the validate\_{slotname}-function.

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